WhisperForge v3.0.0 🌌

Transform audio into structured, intelligent content with AI-powered processing

WhisperForge is a powerful Streamlit application that converts audio files into comprehensive content packages including transcripts, insights, articles, and social media posts. Now with revolutionary large file processing supporting files up to 2GB.

✨ Key Features

• 🎙️ Audio Transcription - High-quality speech-to-text using OpenAI Whisper
• 💡 Wisdom Extraction - AI-powered insights and key takeaways
• 📋 Content Outline - Structured organization and flow
• 📰 Article Generation - Complete written content from audio
• 📱 Social Media Posts - Platform-optimized content
• 📚 Notion Integration - Automatic publishing to Notion workspace
• 📂 Knowledge Base - Add custom context from your files
• 📝 Custom Prompts - Personalize AI output
• 🚀 Large File Processing - Handle files up to 2GB with intelligent chunking
• 🌊 Real-time Streaming - Watch content generate step-by-step
• 🎨 Aurora Theme - Beautiful bioluminescent UI design

🏗️ Project Structure

whisperforge--prime/
├── app_simple.py          # Main Streamlit application (v3.0.0)
├── app.py                 # Redirect to main app
├── core/                  # Core functionality modules
│   ├── content_generation.py
│   ├── file_upload.py     # Enhanced large file processing
│   ├── supabase_integration.py
│   └── ...
├── prompts/               # Custom AI prompts
├── static/                # CSS, JS, and assets
├── tests/                 # Test suite
├── docs/                  # Documentation
└── requirements.txt       # Dependencies

🚀 Quick Start

Prerequisites

• Python 3.8+
• Supabase account (for data storage)
• OpenAI API key (for AI processing)

Installation

1. Clone the repository

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

2. Set up virtual environment

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

3. Install dependencies

   pip install -r requirements.txt

4. Configure environment variables

   cp env.example .env
   # Edit .env with your API keys

5. Run the application

   streamlit run app_simple.py

🔧 Configuration

Create a .env file with your API keys:

# Required
SUPABASE_URL=your_supabase_url
SUPABASE_ANON_KEY=your_supabase_anon_key
OPENAI_API_KEY=your_openai_api_key

# Optional
NOTION_API_KEY=your_notion_api_key
NOTION_DATABASE_ID=your_notion_database_id

🎯 Usage

1. Upload Audio - Support for MP3, WAV, M4A, and video files up to 2GB
2. Choose Processing Mode - Standard (≤25MB) or Enhanced Large File (≤2GB)
3. Watch Real-time Processing - See content generate step-by-step
4. Review Results - Comprehensive content package with all outputs
5. Auto-publish - Optional Notion integration for seamless publishing

🧪 Testing

Before running tests, make sure all dependencies are installed:

pip install -r requirements.txt

You can also use the helper script scripts/setup_test_env.sh to create a virtual environment with the required packages.

Run the test suite:

# Run all tests
pytest

# Run specific test categories
pytest -m unit          # Unit tests only
pytest -m integration   # Integration tests only
pytest tests/test_basic_functionality.py -v  # Specific test file

📚 Documentation

• Large File Processing Guide
• Development Workflow
• API Documentation

🤝 Contributing

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

📄 License

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

🙏 Acknowledgments

• OpenAI for Whisper and GPT models
• Supabase for backend infrastructure
• Streamlit for the amazing web framework
• The open-source community for inspiration and tools

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WhisperForge v3.0.0 - Transform your audio into intelligent content 🌌

🎯 Architecture Overview

├── app_simple.py          # Main Streamlit application (v3.0.0)
├── app.py                 # Redirect to main app
├── core/
│   ├── streaming_pipeline.py    # Step-by-step content processing
│   ├── streaming_results.py     # Real-time content display
│   ├── content_generation.py    # AI content generation functions
│   ├── supabase_integration.py  # Database operations
│   ├── visible_thinking.py      # AI thinking bubbles
│   ├── session_manager.py       # User session handling
│   └── styling.py              # Aurora UI components
└── prompts/                # Default and custom AI prompts

🌊 Core Features

1. Real-Time Audio Processing

• Upload audio files (MP3, WAV, M4A, FLAC, etc.)
• Automatic transcription using OpenAI Whisper
• Progressive content generation with live updates

2. Enhanced AI Content Pipeline

1. Transcription - Speech-to-text conversion
2. Wisdom Extraction - Key insights and takeaways
3. Outline Creation - Structured content organization
4. Article Generation - Complete written content
5. Social Media - Platform-optimized posts
6. 🌌 Notion Publishing - Auto-publish to Notion with beautiful formatting
7. Database Storage - Persistent content library with Supabase

3. Modern Aurora Interface

• Bioluminescent 2025 design system
• Real-time progress indicators
• Animated content cards
• Responsive Aurora color scheme

🔧 Technical Stack

• Frontend: Streamlit with custom Aurora CSS
• Backend: Supabase (PostgreSQL)
• AI Models: OpenAI GPT-4
• Audio Processing: OpenAI Whisper
• Authentication: Supabase Auth + OAuth
• Deployment: Streamlit Cloud ready

🚀 Getting Started

1. Clone Repository

   git clone <repository-url>
   cd whisperforge--prime

2. Install Dependencies

   python -m venv venv
   source venv/bin/activate  # or `venv\Scripts\activate` on Windows
   pip install -r requirements.txt

3. Environment Setup Create .env file or set environment variables:

   # Required - Supabase Database
   SUPABASE_URL=your_supabase_url
   SUPABASE_ANON_KEY=your_supabase_anon_key
   SUPABASE_SERVICE_ROLE_KEY=your_service_role_key  # Optional for admin features
   
   # Required - AI Provider
   OPENAI_API_KEY=your_openai_key
   
   # Notion Integration - Auto-Publishing
   NOTION_API_KEY=your_notion_integration_token
   NOTION_DATABASE_ID=your_notion_database_id
   
   # Optional - OAuth & Integrations
   OAUTH_REDIRECT_URL=http://localhost:8501  # For OAuth flows
   
   # Optional - Security & Monitoring
   JWT_SECRET=your_jwt_secret_key
   SENTRY_DSN=your_sentry_dsn  # For error tracking
   
   # Optional - Development
   DEBUG=true
   LOG_LEVEL=INFO
   ENVIRONMENT=development  # or 'production'

4. Run Application

   ./start_app.sh                 # development (default)
   ./start_app.sh production      # production mode

🎨 Aurora Design System

The WhisperForge UI uses a custom Aurora design system featuring:

• Bioluminescent Effects: Glowing borders and animations
• Gradient Backgrounds: Dynamic color transitions
• Glass Morphism: Backdrop blur effects
• Responsive Cards: Animated content containers
• Progress Streams: Real-time processing indicators

📊 Database Schema

Core Tables

• users - User accounts and settings
• content - Generated content and metadata
• prompts - Custom AI prompts
• knowledge_base - User-uploaded files
• api_keys - Encrypted API credentials

🔐 Security Features

• Encrypted Storage: API keys and sensitive data
• Session Management: Secure user sessions
• Input Validation: File size and type restrictions
• Rate Limiting: API usage controls

🛡 Current Known Issues

1. Database Content Retrieval: 26 processed files not displaying in history (investigating field name mismatches)
2. Real-time Streaming: Content shows but not truly real-time like cursor chat
3. Session Persistence: Authentication doesn't persist across refreshes consistently
4. Prompt Saving: Custom prompts saving but not loading properly
5. Thinking Bubbles: AI thinking stream not integrating smoothly

🔄 Debugging Tools

The content history page includes debug information:

• Database connection status
• Raw record samples
• Session state inspection
• Content structure analysis

📈 Roadmap

Immediate Fixes

• Fix content history display issues
• Implement true real-time streaming
• Resolve session persistence
• Debug prompt saving/loading

Enhancements

• Batch audio processing
• Export to multiple formats
• Advanced AI model selection
• Team collaboration features

💡 Contributing

This is currently a private project focused on creating the best audio-to-content transformation experience with a beautiful, modern interface.

📄 License

MIT License - See LICENSE file for details.

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WhisperForge - Transforming audio into actionable insights with the beauty of Aurora. 🌌

🏗 Architecture (Simplified)

Session Management

# Simple, reliable pattern
if 'authenticated' not in st.session_state:
    st.session_state.authenticated = False

@st.cache_resource  
def init_supabase():
    return get_supabase_client()

Database Pattern

• Supabase Client: Cached with @st.cache_resource
• User Data: Loaded fresh each session (not cached in session state)
• Content Storage: Direct to database, no complex state management

Authentication Flow

1. User enters credentials → Verify against Supabase
2. Set simple session state flags → No tokens or complex persistence
3. Load user preferences from database → Use @st.cache_data for performance