Arhashmi/Math_Quiz_app

1from langchain.prompts import PromptTemplate2from langchain.llms import HuggingFaceHub3from langchain.chains import LLMChain, SequentialChain4from dotenv import load_dotenv5import os6 7# Load environment variables from .env file8load_dotenv()9 10# Hugging Face Hub API token11huggingfacehub_api_token = os.getenv("HUGGINGFACEHUB_API_TOKEN")12 13# Configuration for language model14config = {'max_new_tokens': 512, 'temperature': 0.6}15 16def GetLLMResponse(selected_topic_level, selected_topic, num_quizzes):17    # Ensure that the Hugging Face Hub API token is available18    if huggingfacehub_api_token is None:19        raise ValueError("HUGGINGFACEHUB_API_TOKEN environment variable is not set. Set the API token and try again.")20 21    # Initialize Hugging Face Hub with API token22    llm = HuggingFaceHub(23        repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1",24        model_kwargs=config,25        huggingfacehub_api_token=huggingfacehub_api_token26    )27 28    # Create LLM Chaining for generating questions29    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"30    questions_prompt = PromptTemplate(input_variables=["selected_topic_level", "selected_topic", "num_quizzes"],31                                      template=questions_template)32    questions_chain = LLMChain(llm=llm, prompt=questions_prompt, output_key="questions")33 34    # Create LLM Chaining for generating answers35    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."36    answer_prompt = PromptTemplate(input_variables=["questions"], template=answer_template)37    answer_chain = LLMChain(llm=llm, prompt=answer_prompt, output_key="answer")38 39    # Create Sequential Chaining40    seq_chain = SequentialChain(chains=[questions_chain, answer_chain],41                                input_variables=['selected_topic_level', 'selected_topic', 'num_quizzes'],42                                output_variables=['questions', 'answer'])43 44    # Execute the chained prompts45    response = seq_chain({46        'selected_topic_level': selected_topic_level,47        'selected_topic': selected_topic,48        'num_quizzes': num_quizzes49    })50 51    # Print the response for debugging purposes52    print(response)53 54    # Return the response55    return response56 57