a light package to simplify calling OpenAI, Azure, Cohere, Anthropic, Huggingface API Endpoints. It manages:
- translating inputs to the provider's completion and embedding endpoints
- guarantees consistent output, text responses will always be available at
['choices'][0]['message']['content'] - exception mapping - common exceptions across providers are mapped to the OpenAI exception types
Demo - https://litellm.ai/
Read the docs - https://litellm.readthedocs.io/en/latest/
pip install litellm
from litellm import completion
messages = [{ "content": "Hello, how are you?","role": "user"}]
# openai call
response = completion(model="gpt-3.5-turbo", messages=messages)
# cohere call
response = completion("command-nightly", messages)
# azure openai call
response = completion("chatgpt-test", messages, azure=True)
# hugging face call
response = completion(model="stabilityai/stablecode-completion-alpha-3b-4k", messages=messages, hugging_face=True)
# openrouter call
response = completion("google/palm-2-codechat-bison", messages)Code Sample: Getting Started Notebook
Stable version
pip install litellm==0.1.345
liteLLM supports streaming the model response back, pass stream=True to get a streaming iterator in response.
Streaming is supported for OpenAI, Azure, Anthropic models
response = completion(model="gpt-3.5-turbo", messages=messages, stream=True)
for chunk in response:
print(chunk['choices'][0]['delta'])
# claude 2
result = completion('claude-2', messages, stream=True)
for chunk in result:
print(chunk['choices'][0]['delta'])- Our calendar 👋
- Community Discord 💭
- Our numbers 📞 +1 (770) 8783-106 / +1 (412) 618-6238
- Our emails ✉️ [email protected] / [email protected]
- Need for simplicity: Our code started to get extremely complicated managing & translating calls between Azure, OpenAI, Cohere