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App README

📚 Easy Work - Auto Lecture Notes Generator

Transform your audio lectures into structured, professional notes automatically using AI

Version Python Streamlit

🌟 What is Easy Work?

Easy Work is an AI-powered application that automatically converts your lecture recordings into beautifully structured notes. Simply upload an audio file or record live, and let AI do the heavy lifting!

✨ Key Features

  • —🎤 Multi-format Audio Support: MP3, WAV, OGG, M4A, FLAC, WEBM
  • —🌍 Multi-language: English and Urdu support
  • —🎙️ Live Recording: Record lectures directly in the app
  • —🤖 AI-Powered Processing: Uses Groq's latest models for transcription and text generation
  • —📝 Structured Output: Get organized notes with sections, summaries, and key points
  • —❓ Auto-Generated Questions: Study questions with answers for review
  • —💾 Export Options: Download as PDF or DOCX
  • —📊 Analytics Dashboard: Track your processing history

🚀 How It Works

1. Upload Audio → 2. Select Language → 3. Process → 4. Download Notes

Behind the scenes:

  1. 1.Audio Transcription: Groq's Whisper model converts speech to text
  2. 2.Text Cleaning: AI removes filler words and formats the text
  3. 3.Content Structuring: Llama model organizes content into sections
  4. 4.Question Generation: AI creates study questions based on content
  5. 5.Document Creation: Professional PDF/DOCX files are generated

📦 Installation

Prerequisites

Local Setup

  1. 1.Clone the repository
bash
git clone <your-repo-url>
cd easy-work
  1. 1.Create virtual environment
bash
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
  1. 1.Install dependencies
bash
pip install -r requirements.txt
  1. 1.Set up environment variables Create a .env file in the root directory:
env
GROQ_API_KEY=your_groq_api_key_here
  1. 1.Run the application
bash
streamlit run app.py

The app will open in your browser at http://localhost:8501

☁️ Deploy on Hugging Face Spaces

Step 1: Prepare Your Hugging Face Account

  1. 1.Go to huggingface.co and sign up/login
  2. 2.Navigate to your profile → Spaces → Create new Space

Step 2: Create Your Space

  1. 1.Space name: easy-work-notes (or your preferred name)
  2. 2.License: Choose appropriate license (MIT recommended)
  3. 3.Space SDK: Select Streamlit
  4. 4.Space hardware: Start with CPU basic (free tier)
  5. 5.Click Create Space

Step 3: Upload Your Files

You have two options:

Option A: Git (Recommended)

bash
# Clone your space
git clone https://huggingface.co/spaces/YOUR_USERNAME/easy-work-notes
cd easy-work-notes

# Copy all project files
cp -r /path/to/your/project/* .

# Commit and push
git add .
git commit -m "Initial commit"
git push

Option B: Web Interface

  1. 1.In your Space, click Files → Add file → Upload files
  2. 2.Upload these files:
  3. 3.app.py
  4. 4.requirements.txt
  5. 5.utils/ folder (all files inside)

Step 4: Configure Secrets

  1. 1.Go to Settings tab in your Space
  2. 2.Scroll to Repository secrets
  3. 3.Click New secret
  4. 4.Name: GROQ_API_KEY
  5. 5.Value: Your Groq API key
  6. 6.Click Add secret

Step 5: Build and Run

  • —Hugging Face will automatically detect Streamlit and start building
  • —Wait 2-3 minutes for the build to complete
  • —Your app will be live at: https://huggingface.co/spaces/YOUR_USERNAME/easy-work-notes

Step 6: Share Your App! 🎉

Your app is now live and accessible to anyone with the URL!

🎯 Usage Guide

For a 20-Year-Old User (Simple Explanation)

Think of this app as your AI study buddy that never gets tired!

  1. 1.Get Your Audio Ready
  2. 2.Record your lecture on your phone/laptop
  3. 3.Or upload a lecture recording you already have
  4. 4.Supports: English, Urdu, or mixed
  1. 1.Upload to Easy Work
  2. 2.Click "Start Processing" on dashboard
  3. 3.Choose "Upload Audio File" or "Record Live"
  4. 4.Select your language and detail level
  1. 1.Let AI Work Its Magic ⚡
  2. 2.The app transcribes the audio (speech → text)
  3. 3.Then organizes everything into neat sections
  4. 4.Creates a summary, key points, and study questions
  5. 5.Takes about 2-3 minutes for a 1-hour lecture
  1. 1.Download Your Notes
  2. 2.Get a professional PDF or Word document
  3. 3.Share with friends or print for studying
  4. 4.Use the auto-generated questions for review

Pro Tips:

  • —Upload clear audio for best results
  • —Use "Detailed" mode for important lectures
  • —Check the Analytics page to track your study progress
  • —Questions section is great for exam prep!

🛠️ Project Structure

easy-work/
├── app.py                      # Main Streamlit application
├── requirements.txt            # Python dependencies
├── .gitignore                 # Git ignore rules
├── README.md                  # This file
└── utils/                     # Utility modules
    ├── __init__.py           # Package initializer
    ├── audio_processor.py    # Audio transcription (Groq Whisper)
    ├── text_processor.py     # Text cleaning & structuring (Groq Llama)
    ├── document_generator.py # PDF & DOCX generation
    └── analytics.py          # Usage statistics

🔧 Configuration

Groq Models Used

  • —Whisper Large V3: Audio transcription
  • —Llama 3.3 70B: Text processing and note generation

Customization Options

Edit app.py to customize:

  • —UI colors and styling (CSS section)
  • —Detail levels and their word counts
  • —Section organization logic
  • —Export formatting

🐛 Troubleshooting

Common Issues

1. "GROQ_API_KEY not found"

  • —Make sure you've set the environment variable
  • —For Hugging Face: Add it in Space settings → Secrets
  • —For local: Create a .env file with your key

2. Audio upload fails

  • —Check file format (MP3, WAV, etc.)
  • —Ensure file is not corrupted
  • —Try a smaller file (< 25MB recommended)

3. Transcription is inaccurate

  • —Ensure audio quality is good
  • —Select the correct language
  • —Remove background noise if possible

4. App is slow

  • —Processing time depends on audio length
  • —1-hour lecture ≈ 2-3 minutes processing
  • —Consider upgrading Hugging Face Space hardware

🙏 Acknowledgments

  • —Groq for providing amazing AI models
  • —Streamlit for the awesome framework
  • —Anthropic Claude for development assistance

Made with ❤️ by AI Engineers for Students Everywhere

Welcome to Streamlit!

Edit /src/streamlit_app.py to customize this app to your heart's desire. :heart:

If you have any questions, checkout our documentation and community forums.