litellm 0.1.781

Library to easily interface with LLM API providers

🚅 LiteLLM

Call all LLM APIs using the OpenAI format [Anthropic, Huggingface, Cohere, TogetherAI, Azure, OpenAI, etc.]

Docs

Discord

100+ Supported Models

LiteLLM manages - Translating inputs to the provider's completion and embedding endpoints - Guarantees [consistent output](https://docs.litellm.ai/docs/completion/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

Usage

By default we provide a free $10 key to try all providers supported on LiteLLM. Try it now 👇

pip install litellm

from litellm import completion
import os

## We provide a free $10 key to try all providers supported on LiteLLM.
## set ENV variables 
os.environ["OPENAI_API_KEY"] = "sk-litellm-5b46387675a944d2" # [OPTIONAL] replace with your openai key
os.environ["COHERE_API_KEY"] = "sk-litellm-5b46387675a944d2" # [OPTIONAL] replace with your 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(model="command-nightly", messages=messages)
print(response)

Streaming

liteLLM supports streaming the model response back, pass stream=True to get a streaming iterator in response. Streaming is supported for OpenAI, Azure, Anthropic, Huggingface 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'])

OpenAI Proxy Server

Spin up a local server to translate openai api calls to any non-openai model (e.g. Huggingface, TogetherAI, Ollama, etc.)

This works for async + streaming as well.

litellm --model <model_name>

Running your model locally or on a custom endpoint ? Set the --api-base parameter see how

Contributing

To contribute: Clone the repo locally -> Make a change -> Submit a PR with the change.

Here's how to modify the repo locally: Step 1: Clone the repo

git clone https://github.com/BerriAI/litellm.git

Step 2: Navigate into the project, and install dependencies:

cd litellm
poetry install

Step 3: Test your change:

cd litellm/tests # pwd: Documents/litellm/litellm/tests
pytest .

Step 4: Submit a PR with your changes! 🚀

• push your fork to your github repo
• submit a PR from there

Learn more on how to make a PR

Support / talk with founders

• Schedule Demo 👋
• Community Discord 💭
• Our numbers 📞 [phone] / ‭[phone]‬
• Our emails ✉️ [e-mail] / [e-mail]

Why did we build this

• Need for simplicity: Our code started to get extremely complicated managing & translating calls between Azure, OpenAI, Cohere

Contributors