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The Forefront platform gives you the ability to fine-tune and use open-source Large Language Models (LLMs). This notebook goes over how to use LangChain with ForefrontAI.

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Imports

import os

from langchain_classic.chains import LLMChain
from langchain_community.llms import ForefrontAI
from langchain_core.prompts import PromptTemplate

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Set the environment API Key

Make sure to get your API key from ForefrontAI. You are given a 5 day free trial to test different models. 
# get a new token: https://docs.forefront.ai/forefront/api-reference/authentication

from getpass import getpass

FOREFRONTAI_API_KEY = getpass()

os.environ["FOREFRONTAI_API_KEY"] = FOREFRONTAI_API_KEY

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Create the ForefrontAI instance

You can specify different parameters such as the model endpoint url, length, temperature, etc. You must provide an endpoint url. 
llm = ForefrontAI(endpoint_url="YOUR ENDPOINT URL HERE")

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Create a Prompt template

We will create a prompt template for Question and Answer. 
template = """Question: {question}

Answer: Let's think step by step."""

prompt = PromptTemplate.from_template(template)

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Initiate the LLMChain

llm_chain = LLMChain(prompt=prompt, llm=llm)

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Run the LLMChain

Provide a question and run the LLMChain. 
question = "What NFL team won the Super Bowl in the year Justin Beiber was born?"

llm_chain.run(question)
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