Library to easily interface with LLM API providers
Project description
🚅 litellm
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a simple & light package to call OpenAI, Azure, Cohere, Anthropic API Endpoints
litellm manages:
- translating inputs to completion and embedding endpoints
- guarantees consistent output, text responses will always be available at
['choices'][0]['message']['content']
usage
Read the docs - https://litellm.readthedocs.io/en/latest/
quick start
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
Streaming Queries
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'])
hosted version
why did we build this
- Need for simplicity: Our code started to get extremely complicated managing & translating calls between Azure, OpenAI, Cohere
Support
Contact us at ishaan@berri.ai / krrish@berri.ai
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