* Simple fix for #9339 - upgrade the underlying library and cache the azure storage client (#9965)
* fix - use constants for caching azure storage client
---------
Co-authored-by: Adrian Lyjak <adrian@chatmeter.com>
* feat(schema.prisma): initial commit adding aggregate table for team spend
allows team spend to be visible at 1m+ logs
* feat(db_spend_update_writer.py): support logging aggregate team spend
allows usage dashboard to work at 1m+ logs
* feat(litellm-proxy-extras/): add new migration file
* fix(db_spend_update_writer.py): fix return type
* build: bump requirements
* fix: fix ruff error
* fix(openai.py): ensure openai file object shows up on logs
* fix(managed_files.py): return unified file id as b64 str
allows retrieve file id to work as expected
* fix(managed_files.py): apply decoded file id transformation
* fix: add unit test for file id + decode logic
* fix: initial commit for litellm_proxy support with CRUD Endpoints
* fix(managed_files.py): support retrieve file operation
* fix(managed_files.py): support for DELETE endpoint for files
* fix(managed_files.py): retrieve file content support
supports retrieve file content api from openai
* fix: fix linting error
* test: update tests
* fix: fix linting error
* feat(managed_files.py): support reading / writing files in DB
* feat(managed_files.py): support deleting file from DB on delete
* test: update testing
* fix(spend_tracking_utils.py): ensure each file create request is logged correctly
* fix(managed_files.py): fix storing / returning managed file object from cache
* fix(files/main.py): pass litellm params to azure route
* test: fix test
* build: add new prisma migration
* build: bump requirements
* test: add more testing
* refactor: cleanup post merge w/ main
* fix: fix code qa errors
* feat(internal_user_endpoints.py): return 'total_tokens' in `/user/daily/analytics`
* test(test_internal_user_endpoints.py): add unit test to assert spend metrics and dailyspend metadata always report the same fields
* build(schema.prisma): record success + failure calls to daily user table
allows understanding why model requests might exceed provider requests (e.g. user hit rate limit error)
* fix(internal_user_endpoints.py): report success / failure requests in API
* fix(proxy/utils.py): default to success
status can be missing or none at times for successful requests
* feat(new_usage.tsx): show success/failure calls on UI
* style(new_usage.tsx): ui cleanup
* fix: fix linting error
* fix: fix linting error
* feat(litellm-proxy-extras/): add new migration files
* build(README.md): initial commit adding a separate folder for additional proxy files. Meant to reduce size of core package
* build(litellm-proxy-extras/): new pip package for storing migration files
allows litellm proxy to use migration files, without adding them to core repo
* build(litellm-proxy-extras/): cleanup pyproject.toml
* build: move prisma migration files inside new proxy extras package
* build(run_migration.py): update script to write to correct folder
* build(proxy_cli.py): load in migration files from litellm-proxy-extras
Closes https://github.com/BerriAI/litellm/issues/9558
* build: add MIT license to litellm-proxy-extras
* test: update test
* fix: fix schema
* bump: version 0.1.0 → 0.1.1
* build(publish-proxy-extras.sh): add script for publishing new proxy-extras version
* build(liccheck.ini): add litellm-proxy-extras to authorized packages
* fix(litellm-proxy-extras/utils.py): move prisma migrate logic inside extra proxy pkg
easier since migrations folder already there
* build(pre-commit-config.yaml): add litellm_proxy_extras to ci tests
* docs(config_settings.md): document new env var
* build(pyproject.toml): bump relevant files when litellm-proxy-extras version changed
* build(pre-commit-config.yaml): run poetry check on litellm-proxy-extras as well
* 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
* update sentry_sdk to latest version (#8588)
* Add anthropic thinking + reasoning content support (#8778)
* feat(anthropic/chat/transformation.py): add anthropic thinking param support
* feat(anthropic/chat/transformation.py): support returning thinking content for anthropic on streaming responses
* feat(anthropic/chat/transformation.py): return list of thinking blocks (include block signature)
allows usage in tool call responses
* fix(types/utils.py): extract and map reasoning_content from anthropic as content str
* test: add testing to ensure thinking_blocks are returned at the root
* fix(anthropic/chat/handler.py): return thinking blocks on streaming - include signature
* feat(factory.py): handle anthropic thinking blocks translation if in assistant response
* test: handle openai internal instability
* test: handle openai audio instability
* ci: pin anthropic dep
* test: handle openai audio instability
* fix: fix linting error
* refactor(anthropic/chat/transformation.py): refactor function to remain <50 LOC
* fix: fix linting error
* fix: fix linting error
* fix: fix linting error
* fix: fix linting error
* test: handle index error
* bump: version 1.61.15 → 1.61.16
---------
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>
Co-authored-by: stephaneminisini <stephane.minisini@gmail.com>
* 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
* feat(azure/realtime): initial working commit for proxy azure openai realtime endpoint support
Adds support for passing /v1/realtime calls via litellm proxy
* feat(realtime_api/main.py): abstraction for handling openai realtime api calls
* feat(router.py): add `arealtime()` endpoint in router for realtime api calls
Allows using `model_list` in proxy for realtime as well
* fix: make realtime api a private function
Structure might change based on feedback. Make that clear to users.
* build(requirements.txt): add websockets to the requirements.txt
* feat(openai/realtime): add openai /v1/realtime api support
* Upgrade dependencies in dockerfile
* Change apt-get to apk for alpine image
* Set requirements file to same as dockerfile
---------
Co-authored-by: Jacob Hagstedt <wcgs@novonordisk.com>
