Skip to main content

LiteLLM Proxy (LLM Gateway)

tip

LiteLLM Providers a self hosted proxy server (AI Gateway) to call all the LLMs in the OpenAI format

LiteLLM Proxy is OpenAI compatible, you just need the litellm_proxy/ prefix before the model

Required Variables

os.environ["LITELLM_PROXY_API_KEY"] = "" # "sk-1234" your litellm proxy api key 
os.environ["LITELLM_PROXY_API_BASE"] = "" # "http://localhost:4000" your litellm proxy api base

Usage (Non Streaming)

import os 
import litellm
from litellm import completion

os.environ["LITELLM_PROXY_API_KEY"] = ""

# set custom api base to your proxy
# either set .env or litellm.api_base
# os.environ["LITELLM_PROXY_API_BASE"] = ""
litellm.api_base = "your-openai-proxy-url"


messages = [{ "content": "Hello, how are you?","role": "user"}]

# litellm proxy call
response = completion(model="litellm_proxy/your-model-name", messages)

Usage - passing api_base, api_key per request

If you need to set api_base dynamically, just pass it in completions instead - completions(...,api_base="your-proxy-api-base")

import os 
import litellm
from litellm import completion

os.environ["LITELLM_PROXY_API_KEY"] = ""

messages = [{ "content": "Hello, how are you?","role": "user"}]

# litellm proxy call
response = completion(
model="litellm_proxy/your-model-name",
messages,
api_base = "your-litellm-proxy-url",
api_key = "your-litellm-proxy-api-key"
)

Usage - Streaming

import os 
import litellm
from litellm import completion

os.environ["LITELLM_PROXY_API_KEY"] = ""

messages = [{ "content": "Hello, how are you?","role": "user"}]

# openai call
response = completion(
model="litellm_proxy/your-model-name",
messages,
api_base = "your-litellm-proxy-url",
stream=True
)

for chunk in response:
print(chunk)

Usage with Langchain, LLamaindex, OpenAI Js, Anthropic SDK, Instructor

Follow this doc to see how to use litellm proxy with langchain, llamaindex, anthropic etc