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)