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* refactor SSO handler * render sso JWT on ui * docs debug sso * fix sso login flow use await * fix ui sso debug JWT * test ui sso * remove redis vl * fix redisvl==0.5.1 * fix ml dtypes * fix redisvl * fix redis vl * fix debug_sso_callback * fix linting error * fix redis semantic caching dep * working graph api assignment * test msft sso handler openid * testing for msft group assignment * fix debug graph api sso flow * fix linting errors * add_user_to_teams_from_sso_response * ui sso fix team assignments * linting fix _get_group_ids_from_graph_api_response * add MicrosoftServicePrincipalTeam * create_litellm_teams_from_service_principal_team_ids * create_litellm_teams_from_service_principal_team_ids * docs MICROSOFT_SERVICE_PRINCIPAL_ID * fix linting errors |
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.. | ||
_experimental | ||
analytics_endpoints | ||
anthropic_endpoints | ||
auth | ||
batches_endpoints | ||
common_utils | ||
config_management_endpoints | ||
credential_endpoints | ||
db | ||
example_config_yaml | ||
fine_tuning_endpoints | ||
guardrails | ||
health_endpoints | ||
hooks | ||
management_endpoints | ||
management_helpers | ||
middleware | ||
openai_files_endpoints | ||
pass_through_endpoints | ||
rerank_endpoints | ||
response_api_endpoints | ||
spend_tracking | ||
swagger | ||
types_utils | ||
ui_crud_endpoints | ||
vertex_ai_endpoints | ||
.gitignore | ||
__init__.py | ||
_logging.py | ||
_new_new_secret_config.yaml | ||
_new_secret_config.yaml | ||
_super_secret_config.yaml | ||
_types.py | ||
cached_logo.jpg | ||
caching_routes.py | ||
common_request_processing.py | ||
custom_prompt_management.py | ||
custom_sso.py | ||
custom_validate.py | ||
enterprise | ||
health_check.py | ||
lambda.py | ||
litellm_pre_call_utils.py | ||
llamaguard_prompt.txt | ||
logo.jpg | ||
mcp_tools.py | ||
model_config.yaml | ||
openapi.json | ||
post_call_rules.py | ||
prisma_migration.py | ||
proxy_cli.py | ||
proxy_config.yaml | ||
proxy_server.py | ||
README.md | ||
route_llm_request.py | ||
schema.prisma | ||
start.sh | ||
utils.py |
litellm-proxy
A local, fast, and lightweight OpenAI-compatible server to call 100+ LLM APIs.
usage
$ pip install litellm
$ litellm --model ollama/codellama
#INFO: Ollama running on http://0.0.0.0:8000
replace openai base
import openai # openai v1.0.0+
client = openai.OpenAI(api_key="anything",base_url="http://0.0.0.0:8000") # set proxy to base_url
# request sent to model set on litellm proxy, `litellm --model`
response = client.chat.completions.create(model="gpt-3.5-turbo", messages = [
{
"role": "user",
"content": "this is a test request, write a short poem"
}
])
print(response)
See how to call Huggingface,Bedrock,TogetherAI,Anthropic, etc.
Folder Structure
Routes
proxy_server.py
- all openai-compatible routes -/v1/chat/completion
,/v1/embedding
+ model info routes -/v1/models
,/v1/model/info
,/v1/model_group_info
routes.health_endpoints/
-/health
,/health/liveliness
,/health/readiness
management_endpoints/key_management_endpoints.py
- all/key/*
routesmanagement_endpoints/team_endpoints.py
- all/team/*
routesmanagement_endpoints/internal_user_endpoints.py
- all/user/*
routesmanagement_endpoints/ui_sso.py
- all/sso/*
routes