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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

## set ENV variables
# ENV variables can be set in .env file, too. Example in .env.example
os.environ["OPENAI_API_KEY"] = "openai key"
os.environ["COHERE_API_KEY"] = "cohere key"

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)

# openrouter call
response = completion("google/palm-2-codechat-bison", messages)

Code Sample: Getting Started Notebook

Stable version

pip install litellm==0.1.1

Streaming Queries

liteLLM supports streaming the model response back, pass stream=True to get a streaming iterator in response.

response = completion(model="gpt-3.5-turbo", messages=messages, stream=True)
for chunk in response:
    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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