langchain/docs/modules/models/llms/integrations/forefrontai_example.ipynb

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

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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.

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# get a new token: https://docs.forefront.ai/forefront/api-reference/authentication

from getpass import getpass

FOREFRONTAI_API_KEY = getpass()

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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.

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llm = ForefrontAI(endpoint_url="YOUR ENDPOINT URL HERE")

Create a Prompt Template

We will create a prompt template for Question and Answer.

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template = """Question: {question}

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

prompt = PromptTemplate(template=template, input_variables=["question"])

Initiate the LLMChain

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

Run the LLMChain

Provide a question and run the LLMChain.

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question = "What NFL team won the Super Bowl in the year Justin Beiber was born?"

llm_chain.run(question)