Insight: Learning Resource Generator

This project allows users to generate learning resources such as summaries, flashcards, and quizzes from different input formats like documents and audio files. The generated content can be exported and shared, offering versatile educational support across multiple subjects.

Table of Contents

1. Project Overview
2. Features
3. Prerequisites
4. Local Setup Instructions
5. Running the Application

Project Overview

The project processes documents and media files to create study material using AI techniques. It supports:

• Text and audio-to-summary conversion
• Flashcard and quiz generation
• Exporting of results as .docx files

Features

• Input text, audio, or files to generate learning resources
• Export content as .docx files
• User-friendly interface with responsive design

Prerequisites

Ensure you have the following installed on your system:

1. Python 3.10+
2. Node.js (v16+ recommended)
3. npm (Node package manager)
4. Google Cloud SDK (configured for Speech-to-Text)
5. Google Cloud service account JSON file

Local Setup Instructions

Follow these steps to get the project running locally:

1. Clone the Repository

git clone https://github.com/your-username/insight.git
cd insight

2. Create a Python Virtual Environment

cd backend
python3 -m venv venv
source venv/bin/activate

3. Install Backend Dependencies

Install all the necessary Python dependencies using requirements.txt:

pip install -r requirements.txt

4. Install Frontend Dependencies

cd ../frontend
npm install

5. Configure Google Cloud Credentials

To run this project, you need to set up your own Google Cloud credentials. Here's how:

1. Create a Google Cloud Project

   • Go to the Google Cloud Console.
   • Create a new project or select an existing one.

2. Enable Required APIs

   • Enable the following APIs:
     • Speech-to-Text API
     • Cloud Storage API

3. Create a Service Account

   • Go to IAM & Admin > Service Accounts.
   • Create a new service account and download the JSON key.

4. Set Up Your Environment

   • Place the downloaded JSON key (e.g., your-service-account-key.json) in the backend folder.
   • Update the path to this file in your speech_to_text.py script, if necessary:

   credentials = service_account.Credentials.from_service_account_file('your-service-account-key.json')

   • Set the environment variable in your .bashrc file to point to this key:

   export GOOGLE_APPLICATION_CREDENTIALS="/path/to/your-service-account-key.json"

   • Reload the .bashrc file to apply changes:

   source ~/.bashrc

6. Create .env Files

In the backend folder, create a .env file to store any environment variables such as API keys or sensitive information.

touch .env

Running the Application

1. Run the Backend

cd backend
source venv/bin/activate
python backend.py

This will start the Flask development server on http://127.0.0.1:5000.

2. Run the Frontend

In a new terminal, run the following commands:

cd frontend
npm run dev

This will start the frontend on http://localhost:3000.

3. Access the Application

Open your browser and navigate to:

http://localhost:3000

You should now be able to interact with the web application.