ForefrontAI

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.

Imports

import os

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

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

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")

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)

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

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)

Connect these docs programmatically to Claude, VSCode, and more via MCP for real-time answers.