litellm/litellm/proxy
2024-01-05 17:28:27 +05:30
..
_experimental refactor: add black formatting 2023-12-25 14:11:20 +05:30
example_config_yaml feat(utils.py): support google kms for secret management 2023-12-26 15:39:40 +05:30
hooks refactor: add black formatting 2023-12-25 14:11:20 +05:30
queue refactor: add black formatting 2023-12-25 14:11:20 +05:30
secret_managers fix(google_kms.py): support enums for key management system 2023-12-27 13:19:33 +05:30
tests (test) proxy - load test 2024-01-03 16:16:18 +05:30
.gitignore fix(gitmodules): remapping to new proxy 2023-10-12 21:23:53 -07:00
__init__.py refactor: add black formatting 2023-12-25 14:11:20 +05:30
_types.py feat(proxy_server.py): allow admins to update config via /config/update endpoint 2024-01-03 17:18:33 +05:30
admin_ui.py feat(admin_ui.py): support creating keys on admin ui 2023-12-28 16:59:11 +05:30
health_check.py feat(health_check.py): more detailed health check calls 2023-12-28 09:12:57 +05:30
lambda.py Add mangum. 2023-11-23 00:04:47 -05:00
openapi.json (feat) add swagger.json for litellm proxy 2023-10-13 20:41:04 -07:00
otel_config.yaml (feat) proxy: otel logging 2023-12-01 21:04:08 -08:00
proxy_cli.py (fix) proxy - raise error when user missing litellm[proxy] 2023-12-28 13:07:44 +05:30
proxy_config.yaml (docs) config with cloudflare exampel 2024-01-04 10:25:35 +05:30
proxy_server.py (fix) reading cache params on proxy 2024-01-05 13:36:48 +05:30
README.md (docs) update readme proxy server 2023-11-17 17:40:44 -08:00
schema.prisma feat(proxy_server.py): abstract config update/writing and support persisting config in db 2024-01-04 14:44:59 +05:30
start.sh fix(factory.py): fixing llama-2 non-chat models prompt templating 2023-11-07 21:33:54 -08:00
utils.py (ci/cd) proxy print_verbose on failing insert_data 2024-01-05 17:28:27 +05:30

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.