🎙️ PaperBiceps — AI-Powered Podcaster

Paper Biceps is an AI tool that transforms any written content — research papers, articles, blogs, or documents — into realistic podcast conversations. It uses LLMs and TTS to simulate an actual podcast episode between a host and an expert.

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🚀 Features

v0.2.0 (Current)

• 🌐 Chrome Extension - Browser-based podcast generation with floating microphone
• 🔊 Voice Explanations - Smart query input for specific 'section' and 'Image' explanations ("Explain figure 1.2", "Read abstract")
• 🎧 Built-in Audio Player - With download functionality
• 🖱️ Context Menu - Right-click for quick podcast generation
• 🧠 Gemini-powered - Advanced summarization and script generation
• 🎤 Dynamic Dialogue - Host-expert style Podcast conversations
• 🗂️ Multiple Input Formats - PDF, TXT, DOCX, or URL
• 🎙️ Dual-speaker Audio - Using Deepgram TTS

v0.1.0 (Legacy)

• 🧠 Gemini-powered summarization and script generation
• 🎤 Dynamic host-expert style dialogue like a real podcast
• 🗂️ Accepts PDF, TXT, DOCX, or URL input
• 🎧 Dual-speaker audio generation using Deepgram TTS
• 🎙️ Option to use Streamlit UI or FastAPI API
• 🔊 Final podcast exported as an .mp3

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🧰 Tech Stack

Backend

• Python 3.10+ - Core language
• FastAPI - Modern web framework
• Pydantic - Data validation
• Uvicorn - ASGI server
• HTTPX/Requests - HTTP clients
• Python-dotenv - Environment management

AI/ML Services

• Google Gemini API - LLM for script generation
• Deepgram TTS - Text-to-speech synthesis
• spaCy - Natural language processing

Document Processing

• PyMuPDF - PDF text extraction
• python-docx - DOCX text extraction
• trafilatura - Web content extraction

Audio Processing

• Pydub - Audio manipulation

Frontend

• Chrome Extension (Manifest v3)
• Tailwind CSS - Extension styling
• JavaScript - Extension logic

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🏗️ Project Structure

PaperBiceps/
├── app/                          # Modular backend application
│   ├── main.py                   # FastAPI app entry point
│   ├── config.py                 # Configuration settings
│   ├── requirements.txt          # Python dependencies
│   ├── models/                   # Pydantic models
│   │   └── explain_request.py    # Request models
│   ├── routes/                   # API endpoints
│   │   ├── podcast.py            # Podcast generation endpoints
│   │   ├── explain.py            # Explanation endpoints
│   │   └── health.py             # Health check endpoints
│   ├── services/                 # Business logic
│   │   ├── gemini_service.py     # Gemini AI integration
│   │   ├── deepgram_service.py   # Deepgram TTS integration
│   │   └── scraping_service.py   # Web scraping service
│   └── utils/                    # Utility functions
│       ├── text_cleaning.py      # Text preprocessing
│       └── file_utils.py         # File handling utilities
├── extension/                    # Chrome extension
│   ├── manifest.json             # Extension manifest
│   ├── popup.html/js             # Extension UI
│   ├── content.js                # Content script
│   └── background.js             # Background service worker
├── .env                          # Environment variables
├── .gitignore                    # Git ignore rules
├── LICENSE                       # MIT License
├── paperbiceps_logo.jpg          # Project logo
└── README.md                     # This file

🧪 How to Run Locally

1. Clone the repo

   git clone https://github.com/yourusername/PaperBiceps.git
   cd PaperBiceps

2. Create a virtual environment

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

3. Install dependencies

   pip install -r app/requirements.txt

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

   GEMINI_API_KEY=your_gemini_key_here
   DEEPGRAM_API_KEY=your_deepgram_key_here

5. Run the backend API

   cd app
   uvicorn main:app --reload --host 0.0.0.0 --port 8000

   The API will be available at http://localhost:8000

   • API documentation: http://localhost:8000/docs
   • Health check: http://localhost:8000/health

6. Load Chrome Extension

   • Open chrome://extensions/
   • Enable "Developer mode"
   • Click "Load unpacked" and select the extension/ folder
   • The extension microphone will appear on webpages

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🛠️ Known Limitations

• 🐢 Script + Audio generation can be a little slow, especially for long files or limited bandwidth.
• 🤖 Gemini API occasionally throws rate/resource errors if overused or overloaded if using under free tier

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🤝 Contributing

This is an open source project, and contributions are warmly welcome!
If you're interested in:

• 🏗️ Improving the modular architecture - Adding new services, optimizing existing ones
• ⚡ Performance optimization - Speeding up script generation and audio synthesis
• 🎭 Voice enhancement - Adding emotion and style using TTS attributes
• 🌍 Multi-language support - Extending to non-English content

Feel free to open a pull request or issue 🙌

Start by forking the repo, creating a new branch, and submitting a PR.

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🧠 Ideal Use Cases

• Listen to any important documnet on the go.
• Turn research papers into explainable podcast summaries
• Convert blog posts or newsletters into audio for listeners
• Build your own AI-powered podcast channel
• Help visually impaired users "listen" to any document

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📜 License

Licensed under the MIT License.