Disbord - Discord Voice Chat Quote Bot

An advanced AI-powered Discord bot that continuously records, analyzes, and curates memorable quotes from voice channel conversations using persistent 120-second audio clips.

Features

Core Functionality

• Continuous Voice Recording: Records 120-second rolling audio clips from voice channels
• AI-Powered Quote Analysis: Uses multiple AI providers to analyze and score quotes
• Speaker Recognition: Identifies and tracks speakers across conversations
• Smart Response Scheduling: Delivers quotes at optimal times (real-time, 6-hour rotation, daily summaries)
• Privacy-First Design: GDPR compliant with user consent management

Advanced Capabilities

• Multi-Provider AI Support: OpenAI, Anthropic, Groq, OpenRouter, Ollama, LMStudio
• Laughter Detection: Enhances quote scoring based on audience reactions
• Memory Management: Long-term conversation context and speaker profiles
• Plugin System: Extensible architecture with AI voice chat, personality engine, and research agents
• Performance Monitoring: Comprehensive metrics and health monitoring

Architecture

 core/                   # Core system managers
    ai_manager.py      # AI provider orchestration
    memory_manager.py  # Long-term context storage
    consent_manager.py # Privacy and consent handling
    database.py        # Database management
 services/              # Processing services
    audio/            # Audio processing pipeline
    quotes/           # Quote analysis and scoring
    automation/       # Response scheduling
    interaction/      # User feedback systems
    monitoring/       # Health and metrics
 plugins/              # Extensible plugins
    ai_voice_chat/    # Voice interaction plugin
    personality_engine/ # Dynamic personality system
    research_agent/   # Information research plugin
 config/               # Configuration and templates

Installation

Prerequisites

• Python 3.12+
• PostgreSQL database
• Redis (for caching)
• Qdrant (for vector storage)
• Discord Bot Token

Quick Start

1. Clone the repository

   git clone <repository-url>
   cd disbord
   

2. Set up virtual environment

   make venv
   source .venv/bin/activate
   

3. Install dependencies

   make install
   

4. Configure environment

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

5. Set up database

   make migrate
   

6. Run the bot

   make run
   

Docker Deployment

# Build and run with Docker
make docker-build
make docker-run

# Or use docker-compose
docker-compose up -d

Configuration

Required Environment Variables

# Discord
DISCORD_TOKEN=your_discord_bot_token
GUILD_ID=your_test_server_id  # Optional for development

# Database
DATABASE_URL=postgresql://user:password@localhost:5432/quotes_db
REDIS_URL=redis://localhost:6379
QDRANT_URL=http://localhost:6333

# AI Providers (at least one required)
OPENAI_API_KEY=your_openai_key
ANTHROPIC_API_KEY=your_anthropic_key
GROQ_API_KEY=your_groq_key

# Optional Services
ELEVENLABS_API_KEY=your_elevenlabs_key  # For TTS
AZURE_SPEECH_KEY=your_azure_key         # For speaker recognition

Quote Scoring Configuration

The bot uses a sophisticated scoring system with configurable thresholds:

# Score thresholds (0-10 scale)
QUOTE_THRESHOLD_REALTIME=8.5    # Immediate responses
QUOTE_THRESHOLD_ROTATION=6.0    # 6-hour summaries
QUOTE_THRESHOLD_DAILY=3.0       # Daily compilations

# Scoring weights (0-1 scale)
SCORING_WEIGHT_FUNNY=0.3        # Humor detection
SCORING_WEIGHT_DARK=0.15        # Dark humor
SCORING_WEIGHT_SILLY=0.2        # Silly content
SCORING_WEIGHT_SUSPICIOUS=0.1   # Context awareness
SCORING_WEIGHT_ASININE=0.25     # Absurd content

Usage

Basic Commands

• /start_recording - Begin recording in current voice channel
• /stop_recording - Stop recording
• /consent manage - Manage privacy settings
• /quote search <query> - Search historical quotes
• /stats - View bot statistics

Voice Channel Behavior

1. Bot joins voice channels when invited
2. Records 120-second rolling clips continuously
3. Processes audio for transcription and speaker identification
4. Analyzes quotes using AI providers
5. Responds based on scoring thresholds:
   • Real-time: High-quality quotes (8.5+) trigger immediate responses
   • Rotation: Good quotes (6.0+) included in 6-hour summaries
   • Daily: All notable quotes (3.0+) in daily compilations

Development

Development Setup

# Install development dependencies
make install

# Run in development mode with auto-reload
make run-dev

# Run tests
make test

# Code quality checks
make pre-commit

Testing

# Run all tests
make test

# Specific test types
make test-unit        # Fast unit tests
make test-integration # Integration tests
make test-performance # Performance benchmarks
make test-coverage    # Coverage report

Code Quality

# Format code
make format

# Lint checks
make lint

# Type checking
make type-check

# Security scan
make security

Deployment

Production Deployment

1. Environment Setup

   # Production configuration
   cp docker-compose.production.yml docker-compose.yml
   

2. Database Migration

   make migrate
   

3. Container Deployment

   docker-compose up -d
   

4. Health Monitoring

   make health    # Check system status
   make metrics   # View performance metrics
   

Kubernetes Deployment

# Apply Kubernetes manifests
kubectl apply -f k8s/deployment.yaml

Monitoring & Maintenance

Health Checks

The bot exposes health endpoints at:

• http://localhost:8080/health - System health status
• http://localhost:8080/metrics - Prometheus metrics

Logs

make logs        # Follow all logs
make logs-error  # Error logs only

Database Management

make migrate-create  # Create new migration
make migrate         # Apply migrations
make migrate-rollback # Rollback last migration
make db-reset        # Reset database (CAUTION)

Privacy & Compliance

• GDPR Compliant: Built-in consent management and data retention policies
• User Control: Users can opt-out, delete data, and manage privacy settings
• Secure Storage: Encrypted data storage and automatic audio file cleanup
• Audit Logging: Comprehensive logging for compliance requirements

Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Run tests: make test
4. Run pre-commit checks: make pre-commit
5. Commit changes: git commit -m 'Add amazing feature'
6. Push to branch: git push origin feature/amazing-feature
7. Open a Pull Request

License

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

Support

For support, please:

1. Check the documentation
2. Search existing issues
3. Create a new issue with detailed information

Acknowledgments

• Discord.py community for the excellent library
• AI providers for powerful language models
• Contributors and beta testers

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Note: This bot processes voice conversations and uses AI services. Ensure compliance with your organization's privacy policies and local regulations before deployment.