🎙️ Gemini TTS Podcast Generator

A comprehensive podcast generation toolkit using Google's Gemini API for text-to-speech conversion with multi-speaker support and professional audio processing.

🌟 Features

Core TTS Functionality

• Single Speaker TTS: Convert text to speech with 6 different voices
• Multi-Speaker Interviews: Create podcast conversations with multiple speakers
• Script Generation: AI-powered podcast script creation
• Professional Audio: Automatic format conversion with proper headers
• Streaming Audio: Real-time audio generation with chunk processing

Voice Selection

• Zephyr: Natural, conversational tone
• Puck: Friendly, engaging voice
• Charon: Professional, authoritative
• Kore: Warm, approachable
• Uranus: Distinctive, memorable
• Fenrir: Strong, dramatic

Technical Features

• Multiple Audio Formats: WAV, MP3 with proper formatting
• REST API Integration: Complete API testing infrastructure
• Command-Line Interface: Professional CLI tools
• Comprehensive Testing: Multi-layer testing strategy
• Production Ready: Enterprise-grade implementation

🚀 Quick Start

1. Environment Setup

# Load environment variables
export $(cat .env | xargs)

# Activate virtual environment
source venv/bin/activate

2. List Available Voices

python3 scripts/podcast_cli.py voices

3. Generate Single Speaker Audio

python3 scripts/podcast_cli.py single "Hello world!" -v Zephyr

4. Create Multi-Speaker Interview

SCRIPT="Speaker 1: Welcome!\nSpeaker 2: Thanks for having me!"
python3 scripts/podcast_cli.py multi "$SCRIPT" -s "Speaker 1:Zephyr" "Speaker 2:Puck"

5. Generate Script First

python3 scripts/podcast_cli.py script "AI in Healthcare" -s interview

🏗️ Project Structure

├── .env                              # Environment variables (API keys)
├── .gitignore                       # Git ignore rules
├── requirements.txt                 # Python dependencies
├── README.md                        # This file
├── SETUP_GUIDE.md                   # Detailed setup instructions
├── venv/                           # Python virtual environment
├── .tmp/                           # Temporary files and testing
│   ├── audio_outputs/              # Generated audio files
│   └── curl_audio_outputs/         # CURL-generated audio files
├── scripts/                        # Main application code
│   ├── gemini_tts.py               # Core TTS wrapper class
│   └── podcast_cli.py              # Command-line interface
└── tests/                          # Test files and suites

🔧 Installation

Prerequisites

• Python 3.7+
• Git
• GitHub CLI (for repository management)
• curl (for API testing)

Setup

1. Clone the repository
2. Create virtual environment: python3 -m venv venv
3. Activate virtual environment: source venv/bin/activate
4. Install dependencies: pip install -r requirements.txt
5. Set up environment variables in .env
6. Run tests to verify installation

📖 Documentation

• SETUP_GUIDE.md - Complete installation and usage guide
• API Documentation - Official Gemini API docs
• Audio Guide - Audio-specific documentation

🧪 Testing

Run All Tests

# Run comprehensive test suite
bash .tmp/auth_testing_master.sh

# Run CURL tests
bash .tmp/test_curl_tts.sh

# Run REST API tests
bash .tmp/test_rest_api.sh

Test Specific Functionality

# Test single speaker
python3 .tmp/test_gemini_tts.py

# Test multi-speaker
bash .tmp/raw_curl_2speaker_mp3.sh

🔐 Authentication

The system supports multiple authentication methods:

• API Key Authentication: Primary method via environment variables
• Bearer Token: Alternative authentication method
• Comprehensive Testing: Authentication validation suite

📊 API Usage

Direct REST API

# Test with curl
curl -X POST \
  -H "Content-Type: application/json" \
  "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-pro-preview-tts:streamGenerateContent?key=YOUR_API_KEY" \
  -d @request.json

Python Integration

from scripts.gemini_tts import GeminiTTS

tts = GeminiTTS()
audio_file = tts.generate_speech("Hello world!", voice_name="Zephyr")

🎯 Success Criteria

✅ Audio Generation: Real, listenable audio files ✅ Multi-Speaker Support: Natural conversation flow ✅ Professional Quality: High-quality audio output ✅ Comprehensive Testing: Multi-layer validation ✅ Production Ready: Enterprise-grade implementation

🔍 Troubleshooting

Common Issues

1. API Rate Limits: Check usage at https://ai.google.dev/usage
2. Authentication Errors: Verify API key in .env file
3. Audio Format Issues: Check MIME type handling
4. Network Connectivity: Ensure HTTPS access to Google APIs

Debug Mode

# Enable debug logging
export DEBUG=true
python3 scripts/podcast_cli.py single "test" -v Zephyr

🚀 Advanced Usage

Custom Voice Configuration

speaker_configs = [
    {"speaker": "Host", "voice": "Zephyr"},
    {"speaker": "Guest", "voice": "Puck"}
]
tts.generate_podcast_interview(script, speaker_configs)

Batch Processing

# Generate multiple files
for voice in Zephyr Puck Charon Kore Uranus Fenrir; do
    python3 scripts/podcast_cli.py single "Testing voice $voice" -v $voice -o "voice_$voice"
done

📈 Performance

• Streaming Processing: Real-time audio generation
• Efficient Memory Usage: Chunk-based processing
• Multi-format Support: Automatic format conversion
• Error Recovery: Robust error handling

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add comprehensive tests
5. Submit a pull request

📄 License

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

🙏 Acknowledgments

• Google AI: For the amazing Gemini API
• GitHub: For providing the platform
• Python Community: For excellent libraries
• Open Source: For making this possible

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Generated with ❤️ and 🐱 supervision in mom's basement