ForefrontAI
The Forefront platform gives you the ability to fine-tune and use open-source large language models.
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
API Reference:
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
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")
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)
Initiate the LLMChain
llm_chain = LLMChain(prompt=prompt, llm=llm)
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)