Call all LLM APIs using the OpenAI format [Anthropic, Huggingface, Cohere, TogetherAI, Azure, OpenAI, etc.]
📣1-click deploy your own LLM proxy server. Grab time, if you're interested!
LiteLLM 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
pip install litellm
from litellm import completion
import os
## set ENV variables
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(model="command-nightly", messages=messages)Don't have a key? We'll give you access 👉 https://docs.litellm.ai/docs/proxy_api
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'])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
- Schedule Demo 👋
- 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