litellm-mirror/litellm/proxy
2023-12-11 09:06:27 -08:00
..
example_config_yaml (docs) add example config.yaml 2023-12-04 18:08:57 -08:00
hooks fix(proxy_server.py): support for streaming 2023-12-09 16:23:04 -08:00
queue (chore) linting fix 2023-12-05 13:23:35 -08:00
tests test: remove local test 2023-12-05 12:45:52 -08:00
.gitignore fix(gitmodules): remapping to new proxy 2023-10-12 21:23:53 -07:00
__init__.py update proxy cli 2023-09-28 16:24:41 -07:00
_types.py fix(proxy_server.py): fix /model/new adding new model issue 2023-12-09 22:44:11 -08:00
custom_auth.py test: fix test imports 2023-12-06 17:21:47 -08:00
custom_callbacks.py fix(proxy_server.py): fix pydantic version errors 2023-12-09 12:09:49 -08:00
health_check.py feat(proxy_server.py): enable background health checks 2023-12-07 19:40:06 -08:00
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: fix run_ollama_serve to only run if api base is none 2023-12-09 21:31:46 -08:00
proxy_config.yaml (docs) - proxy_config.yaml 2023-12-11 09:06:27 -08:00
proxy_server.py fix(proxy_server.py): fix /model/new adding new model issue 2023-12-09 22:44:11 -08:00
README.md (docs) update readme proxy server 2023-11-17 17:40:44 -08:00
schema.prisma fix(proxy_server.py): enable pre+post-call hooks and max parallel request limits 2023-12-08 17:11:30 -08:00
start.sh fix(factory.py): fixing llama-2 non-chat models prompt templating 2023-11-07 21:33:54 -08:00
utils.py fix(proxy_server.py): support for streaming 2023-12-09 16:23:04 -08:00

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.