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https://github.com/BerriAI/litellm.git
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* fix - using on python 3.9
* [⚡️ Python SDK Import] - 2 second faster import times (#12135)
* speedup - move wb logger to conditional
* fix import path
* docs(index.md): initial pre-release note
* 🧹 Refactor init.py to use a model registry (#12138)
* fix - refactor init to use a registry
* # noqa: PLR0915
* fix import loc
* test whitelisted models
* Revert "🧹 Refactor init.py to use a model registry (#12138)" (#12141)
This reverts commit f93326a214.
* [⚡️ Python SDK import] - reduce python sdk import time by .3s (#12140)
* use 1 file for KeyManagementSystem
* move key management settings
* fix import locs
* test_proxy_types_not_imported
* test the import loc
* fix import item
* fix imports
* fix import loc
* fix imports
* fix imports
* fix - revert list team changes
* fix for o-series param checks
* bump poetry
* docs(index.md): update release note with cleaner table for updated models
* `/v1/messages` - Remove hardcoded model name on streaming + Tags - enable setting custom header tags (#12131)
* fix(anthropic/experimental_pass_through): use given model name when returning streaming chunks
don't harcode model name on streaming
confusing for user
* fix(anthropic/streaming_iterator.py): remove scope of import
* feat(litellm_logging.py): allow admin to specify additional headers for using as spend tags
Closes https://github.com/BerriAI/litellm/issues/12129
* test(test_litellm_logging.py): add unit tests
* feat(openweb_ui.md): add custom tag tutorial to docs
* docs(cost_tracking.md): add tag based usage UI screenshot
* test: update test
* fix: fix import
* docs - update release notes
* Benefits of using gemini-cli with LiteLLM
* UI QA Fixes - prevent team model reset on model add + return team-only models on /v2/model/info + render team member budget correctly (#12144)
* fix(team_endpoints.py): prevent overwriting current list of team models on new model add
* fix(networking.tsx): fix default proxy base url
* fix(proxy_server.py): include team only models when retrieving all deployments on `/v2/model/info` helper util
ensures team only models are shown to user
* fix(router.py): check model name by team public model name when team id given
Fixes issue where team member could not see team only models when clicking into that team on `Models + Endpoints`
* fix(team_member_view.tsx): fix rendering team member budget, when budget is set
* test: update tests
* test: update unit test
* docs gemini cli x litellm
* docs: index.md
release note cleanup
* docs(index.md): add more hyperlinks to docs
* docs(index.md): add batch api cost tracking to docs
* docs(index.md): update docs
* VertexAI Anthropic - streaming cost tracking w/ prompt caching fixes (#12188)
* fix(rebuild-usage-object---ensure-cache_tokens-is-set): Ensures cache tokens is correctly set
Fixes https://github.com/BerriAI/litellm/issues/12149
* test(test_stream_chunk_builder_utils.py): add unit test to ensure cached tokens is part of stream chunk builder
Ensures standardized values are used
* Fix rendering ui on non-root images (#12226)
* fix(proxy_server.py): only rewrite server_root_path if path set
Fixes UI rendering issue on non-root images
* docs(custom_root_ui.md): clarify custom root path doesn't work on non-root images
* build(pyproject.toml): version rc2
* fix(streaming_handler.py): store finish reason, even if is_finished is false - allows storing early gemini finish reasons (#12250)
Fixes https://github.com/BerriAI/litellm/issues/12249
---------
Co-authored-by: Ishaan Jaff <ishaanjaffer0324@gmail.com>
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# LITELLM PROXY DEPENDENCIES #
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anyio==4.8.0 # openai + http req.
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httpx==0.28.1
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openai==1.81.0 # openai req.
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fastapi==0.115.5 # server dep
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backoff==2.2.1 # server dep
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pyyaml==6.0.2 # server dep
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uvicorn==0.29.0 # server dep
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gunicorn==23.0.0 # server dep
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uvloop==0.21.0 # uvicorn dep, gives us much better performance under load
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boto3==1.34.34 # aws bedrock/sagemaker calls
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redis==5.2.1 # redis caching
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prisma==0.11.0 # for db
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mangum==0.17.0 # for aws lambda functions
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pynacl==1.5.0 # for encrypting keys
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google-cloud-aiplatform==1.47.0 # for vertex ai calls
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google-genai==1.22.0
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anthropic[vertex]==0.54.0
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mcp==1.9.3 # for MCP server
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google-generativeai==0.5.0 # for vertex ai calls
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async_generator==1.10.0 # for async ollama calls
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langfuse==2.45.0 # for langfuse self-hosted logging
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prometheus_client==0.20.0 # for /metrics endpoint on proxy
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ddtrace==2.19.0 # for advanced DD tracing / profiling
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orjson==3.10.12 # fast /embedding responses
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apscheduler==3.10.4 # for resetting budget in background
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fastapi-sso==0.16.0 # admin UI, SSO
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pyjwt[crypto]==2.9.0
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python-multipart==0.0.18 # admin UI
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Pillow==11.0.0
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azure-ai-contentsafety==1.0.0 # for azure content safety
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azure-identity==1.16.1 # for azure content safety
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azure-storage-file-datalake==12.20.0 # for azure buck storage logging
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opentelemetry-api==1.25.0
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opentelemetry-sdk==1.25.0
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opentelemetry-exporter-otlp==1.25.0
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sentry_sdk==2.21.0 # for sentry error handling
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detect-secrets==1.5.0 # Enterprise - secret detection / masking in LLM requests
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cryptography==43.0.1
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tzdata==2025.1 # IANA time zone database
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litellm-proxy-extras==0.2.6 # for proxy extras - e.g. prisma migrations
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### LITELLM PACKAGE DEPENDENCIES
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python-dotenv==1.0.0 # for env
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tiktoken==0.8.0 # for calculating usage
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importlib-metadata==6.8.0 # for random utils
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tokenizers==0.20.2 # for calculating usage
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click==8.1.7 # for proxy cli
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rich==13.7.1 # for litellm proxy cli
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jinja2==3.1.6 # for prompt templates
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aiohttp==3.10.2 # for network calls
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aioboto3==12.3.0 # for async sagemaker calls
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tenacity==8.2.3 # for retrying requests, when litellm.num_retries set
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pydantic==2.10.2 # proxy + openai req.
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jsonschema==4.22.0 # validating json schema
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websockets==13.1.0 # for realtime API
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########################
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# LITELLM ENTERPRISE DEPENDENCIES
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########################
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litellm-enterprise==0.1.10
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