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https://github.com/mohdrasmil7/document-smartsummarizer-quizgenerator-using-llm

Transform your documents into concise summaries and engaging quizzes with the power of Large Language Models (LLM). 📄✨ Whether you’re a student, educator, or professional, this tool helps you quickly grasp key points and test your knowledge. Simplify your learning and make studying fun with our smart summarizer and quiz generator! 🎓📝🚀
https://github.com/mohdrasmil7/document-smartsummarizer-quizgenerator-using-llm

generative-ai groq langchain-python llm nlp python streamlit-webapp

Last synced: about 1 month ago
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Transform your documents into concise summaries and engaging quizzes with the power of Large Language Models (LLM). 📄✨ Whether you’re a student, educator, or professional, this tool helps you quickly grasp key points and test your knowledge. Simplify your learning and make studying fun with our smart summarizer and quiz generator! 🎓📝🚀

Awesome Lists containing this project

README 

        
# Unleash Your Knowledge Wizard: Summaries and Quizzes Made Easy! 📚✨



## Overview



This project is an Educational Assistant powered by Large Language Models (LLM). It enables users to generate summaries and quizzes from uploaded PDFs, leveraging the advanced capabilities of the LLM model to deliver enhanced performance. 🤖📝



![](assets/Demo1.png) ![](assets/Demo2.png)



## Table of Contents



1. [Introduction](#introduction)

2. [Features](#features)

3. [Technologies Used](#technologies-used)

4. [Setup and Installation](#setup-and-installation)

5. [Usage](#usage)

6. [Code Explanation](#code-explanation)

7. [Future Enhancements](#future-enhancements)

8. [Contact](#contact)



## Introduction



This Educational Assistant is designed to simplify the process of summarizing and generating quizzes from PDF documents. Users can upload their documents, and the assistant will provide concise summaries and quizzes based on the content.



## Features



- Utilizes LLM for natural language understanding and generation.

- Allows users to generate quizzes and summaries from uploaded PDFs.

- Provides accurate and concise responses.

- User-friendly interface for seamless interaction. 🖥️



## Technologies Used



- **Python** 

- **Streamlit**: For building the web interface

- **LangChain**: For implementing the RAG model

- **PyPDF2**: For processing PDF documents

- **FAISS**: For efficient similarity search

- **Google Generative AI**: For generating embeddings

- **Groq API**: For advanced LLM functionalities

- **Llama3 Model**



## Setup and Installation



1. **Clone the repository:**



   ```bash

   git clone https://github.com/your-repo/Document-SmartSummarizer-QuizGenerator-using-LLM.git

   cd Document-SmartSummarizer-QuizGenerator-using-LLM



2. **Install the required packages:**



   bash

   pip install -r requirements.txt

   



3. **Set up environment variables:**



   Create a `.env` file in the root directory and add your API keys:



   

   GROQ_API_KEY=your_groq_api_key

   



4. **Run the Streamlit application:**



   bash

   streamlit run app.py



## Usage

1. Open the application in your web browser.

2. Upload your PDF document via the sidebar.

3. Select "Generate Summary" or "Generate Quiz" based on your needs. 📄🔍



## Code Explanation



### Importing Required Libraries



import streamlit as st

from langchain_community.document_loaders import PyPDFLoader

from dotenv import load_dotenv

from langchain.prompts import ChatPromptTemplate

from langchain_core.output_parsers import StrOutputParser

from langchain_groq import ChatGroq



load_dotenv()

import os

os.environ["GROQ_API_KEY"] = os.getenv("GROQ_API_KEY")



### Streamlit UI Elements



st.title('Educational Assistant')

st.header('Summary and Quiz Generator')

st.sidebar.title('Drop your PDF here')

user_file_upload = st.sidebar.file_uploader(label='', type='pdf')

summary_clicked = st.button('Generate Summary')

quiz_clicked = st.button('Generate Quiz')



### Handling PDF Upload and Loading



if user_file_upload:

    pdf_data = user_file_upload.read()

    with open("temp_pdf_file.pdf", "wb") as f:

        f.write(pdf_data)

    loader = PyPDFLoader("temp_pdf_file.pdf")

    data = loader.load_and_split()



### Prompt Templates for Summary and Quiz Generation



prompt_1 = ChatPromptTemplate.from_messages([

    ("system", "you are a smart assistant. Give a summary to the user's PDF. I will tip you 10000 dollars if the user finds it helpful. Be polite to the user"),

    ("user", "{data}")

])



prompt_2 = ChatPromptTemplate.from_messages([

    ("system", "you are a smart assistant. Give 10 quizzes and answers to the user's PDF. I will tip you 10000 dollars if the user finds it helpful. Be polite to the user"),

    ("user", "{data}")

])



llm = ChatGroq(model="llama3-70b-8192")

output_parser = StrOutputParser()

chain_1 = prompt_1 | llm | output_parser

chain_2 = prompt_2 | llm | output_parser



### Generating Summary or Quiz Based on User Input



if summary_clicked:

    st.write(chain_1.invoke({'data': data}))

elif quiz_clicked:

    st.write(chain_2.invoke({'data': data}))



## Future Enhancements



- **Expand Document Corpus:** Include more legal documents and case studies for broader coverage.

- **Advanced Query Handling:** Implement more sophisticated natural language processing techniques for better understanding and response.

- **User Authentication:** Add user login and history tracking for personalized experiences.

- **Mobile Support:** Optimize the application for mobile devices. 📱💡



## Contact



For any inquiries or feedback, please contact [Muhammed Rasmil] at [[email protected]].📧