function.py

from langchain.prompts import PromptTemplate
from langchain.llms import HuggingFaceHub
from langchain.chains import LLMChain, SequentialChain
from dotenv import load_dotenv
import os

# Load environment variables from .env file
load_dotenv()

# Hugging Face Hub API token
huggingfacehub_api_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")

# Configuration for language model
config = {'max_new_tokens': 512, 'temperature': 0.6}

def GetLLMResponse(selected_topic_level, selected_topic, num_quizzes):
    # Ensure that the Hugging Face Hub API token is available
    if huggingfacehub_api_token is None:
        raise ValueError("HUGGINGFACEHUB_API_TOKEN environment variable is not set. Set the API token and try again.")

    # Initialize Hugging Face Hub with API token
    llm = HuggingFaceHub(
        repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1",
        model_kwargs=config,
        huggingfacehub_api_token=huggingfacehub_api_token
    )

    # Create LLM Chaining for generating questions
    questions_template = "Generate a {selected_topic_level} math quiz on the topic of {selected_topic}. Generate only {num_quizzes} questions not more and without providing answers. The Question should not be in image format/link"
    questions_prompt = PromptTemplate(input_variables=["selected_topic_level", "selected_topic", "num_quizzes"],
                                      template=questions_template)
    questions_chain = LLMChain(llm=llm, prompt=questions_prompt, output_key="questions")

    # Create LLM Chaining for generating answers
    answer_template = "I want you to become a teacher and answer this specific Question:\n{questions}\n\nYou should give me a straightforward and concise explanation and answer to each one of them."
    answer_prompt = PromptTemplate(input_variables=["questions"], template=answer_template)
    answer_chain = LLMChain(llm=llm, prompt=answer_prompt, output_key="answer")

    # Create Sequential Chaining
    seq_chain = SequentialChain(chains=[questions_chain, answer_chain],
                                input_variables=['selected_topic_level', 'selected_topic', 'num_quizzes'],
                                output_variables=['questions', 'answer'])

    # Execute the chained prompts
    response = seq_chain({
        'selected_topic_level': selected_topic_level,
        'selected_topic': selected_topic,
        'num_quizzes': num_quizzes
    })

    # Print the response for debugging purposes
    print(response)

    # Return the response
    return response