VoiceCraft Studio 🎙️

VoiceCraft Studio is a modern web application that transforms research papers and PDF documents into engaging podcast-style audio content. Built with React for the frontend and Python Flask for the backend, it offers a seamless experience for converting academic content into accessible audio formats.

Video Demonstration

You can view the video of the application here.

Features

• 📄 Multiple PDF upload support
• 🎨 Customizable content styles (concise, elaborate, balanced, formal, casual, professional)
• ⏱️ Flexible podcast duration options
• 🔊 Real-time audio preview
• 💾 MP3 download capability
• 📱 Responsive design for all devices

Tech Stack

Frontend

• React
• Material-UI (MUI)
• Eleven Labs API for text-to-speech
• Axios for API calls
• React-Dropzone for file handling

Backend

• Python Flask
• PyTesseract for OCR
• PDF2Image for PDF processing
• OpenAI's Mistral model for text processing
• CORS for cross-origin support

Prerequisites

Before you begin, ensure you have installed:

• Node.js (v14 or higher)
• Python (v3.8 or higher)
• Tesseract OCR
• Poppler (for PDF processing)

Environment Variables

Frontend (.env)

VITE_ELEVEN_LABS_API_KEY=your_eleven_labs_api_key
VITE_ELEVEN_LABS_VOICE_ID=your_voice_id

Backend (.env)

FLASK_APP=app.py
FLASK_ENV=development

Installation

Frontend Setup

1. Clone the repository

git clone <repository-url>
cd voicecraft-studio

2. Install dependencies

npm install

3. Start the development server

npm run dev

Backend Setup

1. Navigate to the backend directory

cd backend

2. Create and activate a virtual environment

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install Python dependencies

pip install -r requirements.txt

4. Start the Flask server

python real_server.py

Usage

1. Access the application at http://localhost:5173 (or your Vite default port)
2. Upload PDF files using the drag-and-drop interface
3. Select your desired content style and podcast duration
4. Click "Generate Podcast" to process your files
5. Use the audio controls to preview the generated content
6. Download the final audio as MP3

API Endpoints

POST /generate

Processes PDF files and generates podcast script

• Request: Multipart form data
  • pdfs: PDF files (multiple)
  • contentStyle: String
  • duration: String
• Response: JSON with generated script and metadata

GET /get_summary/:result_id

Retrieves a previously generated summary

• Parameters: result_id (UUID)
• Response: JSON with summary data

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details

Acknowledgments

• Eleven Labs for text-to-speech API
• Material-UI for the component library
• Mistral AI for the language model
• All contributors and maintainers

Support

For support, please open an issue in the GitHub repository or contact the maintainers.