litellm/litellm/proxy
2023-12-02 21:33:54 -08:00
..
example_config_yaml (docs) proxy: add example OTEL config yaml 2023-12-02 11:22:40 -08:00
queue (fix) linting 2023-12-01 14:08:19 -08:00
tests fix(proxy_server.py): hash keys 2023-12-02 19:30:03 -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
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 (feat) --health for checking config models 2023-11-27 12:13:21 -08:00
proxy_config.yaml (fix) general proxy config yaml 2023-12-02 11:32:29 -08:00
proxy_server.py fix(proxy_server.py): support model info augmenting for azure models 2023-12-02 21:33:54 -08:00
README.md (docs) update readme proxy server 2023-11-17 17:40:44 -08:00
schema.prisma fix(proxy_server.py): hash keys 2023-12-02 19:30:03 -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: fix linting issues 2023-12-02 19:30:03 -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.