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# 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.llms import ForefrontAI
    from langchain import PromptTemplate, LLMChain

## 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(template=template, input_variables=["question"])

## 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)