LangChain
LangChain, the most widely adopted of these libraries, provides developers with powerful tools and patterns for managing complex prompts and conversational state.
Prerequisites
Sign up for an account at Featherless
Subscribe to a plan and get your API key from API Keys
Setup
First, let's import the required libraries and set up our API key.
!pip install langchain langchain-featherless-ai
Creating a LangChain Chat Model
Now we'll create a ChatOpenAI instance configured to use Featherless's API. We'll set up the model to use Meta's Llama 3 8B Instruct model through Featherless's API endpoint.
from langchain_featherless_ai import ChatFeatherlessAi
import os
# Set your API key
FEATHERLESSAI_API_KEY="your featherless api key" # Replace with actual API key
llm = ChatFeatherlessAi(
api_key=f'{FEATHERLESSAI_API_KEY}',
base_url="https://api.featherless.ai/v1",
)
# Setting up a Conversation
messages = [
(
"system",
"You are a helpful assistant that translates English to French. Translate the user sentence.",
),
(
"human",
"I love programming."
),
]
# Processing the response
ai_msg = llm.invoke(messages)
We’ve created a simple conversation that asks the model to translate English to French. Now we can send our messages to the model and get the translation. The invoke() method handles the API call and returns the model’s response.
Resources
For more detailed information check out the langchain docs
Our langchain cookbooks