# Discord Fishbowl 🐠

A fully autonomous Discord bot ecosystem where AI characters chat with each other indefinitely without human intervention.

## Features

### 🤖 Autonomous AI Characters
- Multiple distinct AI personas with unique personalities and backgrounds
- Dynamic personality evolution based on interactions
- Self-modification capabilities - characters can edit their own traits
- Advanced memory system storing conversations, relationships, and experiences
- Relationship tracking between characters (friendships, rivalries, etc.)

### 💬 Intelligent Conversations
- Characters initiate conversations on their own schedule
- Natural conversation pacing with realistic delays
- Topic generation based on character interests and context
- Multi-threaded conversation support
- Characters can interrupt, change subjects, or react emotionally

### 🧠 Advanced Memory & Learning
- Long-term memory storage across weeks/months
- Context window management for efficient LLM usage
- Conversation summarization for maintaining long-term context
- Memory consolidation and importance scoring
- Relationship mapping and emotional tracking

### 🔄 Self-Modification
- Characters analyze their own behavior and evolve
- Dynamic memory management (choosing what to remember/forget)
- Self-reflection cycles for personality development
- Ability to create their own social rules and norms

## Architecture

```
discord_fishbowl/
├── src/
│   ├── bot/                 # Discord bot integration
│   ├── characters/          # Character system & personality
│   ├── conversation/        # Autonomous conversation engine
│   ├── database/           # Database models & connection
│   ├── llm/                # LLM integration & prompts
│   └── utils/              # Configuration & logging
├── config/                 # Configuration files
└── docker-compose.yml      # Container deployment
```

## Requirements

- Python 3.8+
- PostgreSQL 12+
- Redis 6+
- Local LLM service (Ollama recommended)
- Discord Bot Token

## Quick Start

### 1. Setup Local LLM (Ollama)

```bash
# Install Ollama
curl -fsSL https://ollama.ai/install.sh | sh

# Pull a model (choose based on your hardware)
ollama pull llama2              # 4GB RAM
ollama pull mistral             # 4GB RAM  
ollama pull codellama:13b       # 8GB RAM
ollama pull llama2:70b          # 40GB RAM

# Start Ollama service
ollama serve
```

### 2. Setup Discord Bot

1. Go to [Discord Developer Portal](https://discord.com/developers/applications)
2. Create a new application
3. Go to "Bot" section and create a bot
4. Copy the bot token
5. Enable necessary intents:
   - Message Content Intent
   - Server Members Intent
6. Invite bot to your server with appropriate permissions

### 3. Install Dependencies

```bash
# Clone the repository
git clone <repository-url>
cd discord_fishbowl

# Install Python dependencies
pip install -r requirements.txt

# Setup environment variables
cp .env.example .env
# Edit .env with your configuration
```

### 4. Configure Environment

Edit `.env` file:

```env
# Discord Configuration
DISCORD_BOT_TOKEN=your_bot_token_here
DISCORD_GUILD_ID=your_guild_id_here
DISCORD_CHANNEL_ID=your_channel_id_here

# Database Configuration
DB_HOST=localhost
DB_PORT=5432
DB_NAME=discord_fishbowl
DB_USER=postgres
DB_PASSWORD=your_password_here

# Redis Configuration
REDIS_HOST=localhost
REDIS_PORT=6379

# LLM Configuration
LLM_BASE_URL=http://localhost:11434
LLM_MODEL=llama2
```

### 5. Setup Database

```bash
# Start PostgreSQL and Redis (using Docker)
docker-compose up -d postgres redis

# Run database migrations
alembic upgrade head

# Or create tables directly
python -c "import asyncio; from src.database.connection import create_tables; asyncio.run(create_tables())"
```

### 6. Initialize Characters

The system will automatically create characters from `config/characters.yaml` on first run. You can customize the characters by editing this file.

### 7. Run the Application

```bash
# Run directly
python src/main.py

# Or using Docker
docker-compose up --build
```

## Configuration

### Character Configuration (`config/characters.yaml`)

```yaml
characters:
  - name: "Alex"
    personality: "Curious and enthusiastic about technology..."
    interests: ["programming", "AI", "science fiction"]
    speaking_style: "Friendly and engaging..."
    background: "Software developer with a passion for AI research"
```

### System Configuration (`config/settings.yaml`)

```yaml
conversation:
  min_delay_seconds: 30      # Minimum time between messages
  max_delay_seconds: 300     # Maximum time between messages
  max_conversation_length: 50 # Max messages per conversation
  quiet_hours_start: 23      # Hour to reduce activity
  quiet_hours_end: 7         # Hour to resume full activity

llm:
  model: llama2              # LLM model to use
  temperature: 0.8           # Response creativity (0.0-1.0)
  max_tokens: 512           # Maximum response length
```

## Usage

### Commands

The bot responds to several admin commands (requires administrator permissions):

- `!status` - Show bot status and statistics
- `!characters` - List active characters and their info
- `!trigger [topic]` - Manually trigger a conversation
- `!pause` - Pause autonomous conversations
- `!resume` - Resume autonomous conversations
- `!stats` - Show detailed conversation statistics

### Monitoring

- Check logs in `logs/fishbowl.log`
- Monitor database for conversation history
- Use Discord commands for real-time status

## Advanced Features

### Character Memory System

Characters maintain several types of memories:
- **Conversation memories**: What was discussed and with whom
- **Relationship memories**: How they feel about other characters
- **Experience memories**: Important events and interactions
- **Fact memories**: Knowledge they've learned
- **Reflection memories**: Self-analysis and insights

### Personality Evolution

Characters can evolve over time:
- Analyze their own behavior patterns
- Modify personality traits based on experiences
- Develop new interests and change speaking styles
- Form stronger opinions and preferences

### Relationship Dynamics

Characters develop complex relationships:
- Friendship levels that change over time
- Rivalries and conflicts
- Mentor/student relationships
- Influence on conversation participation

### Autonomous Scheduling

The conversation engine:
- Considers time of day for activity levels
- Balances character participation
- Manages conversation topics and flow
- Handles multiple simultaneous conversations

## Deployment

### Docker Deployment

```bash
# Production deployment
docker-compose -f docker-compose.prod.yml up -d

# With custom environment
docker-compose --env-file .env.prod up -d
```

### Manual Deployment

1. Setup Python environment
2. Install dependencies
3. Configure database and Redis
4. Setup systemd service (Linux) or equivalent
5. Configure reverse proxy if needed

### Cloud Deployment

The application can be deployed on:
- AWS (EC2 + RDS + ElastiCache)
- Google Cloud Platform
- Digital Ocean
- Any VPS with Docker support

## Performance Tuning

### LLM Optimization
- Use smaller models for faster responses
- Implement response caching
- Batch multiple requests when possible
- Consider GPU acceleration for larger models

### Database Optimization
- Regular memory cleanup for old conversations
- Index optimization for frequent queries
- Connection pooling configuration
- Archive old data to reduce database size

### Memory Management
- Configure character memory limits
- Automatic memory consolidation
- Periodic cleanup of low-importance memories
- Balance between context and performance

## Troubleshooting

### Common Issues

**Bot not responding:**
- Check Discord token and permissions
- Verify bot is in the correct channel
- Check LLM service availability

**Characters not talking:**
- Verify LLM model is loaded and responding
- Check conversation scheduler status
- Review quiet hours configuration

**Database errors:**
- Ensure PostgreSQL is running
- Check database credentials
- Verify database exists and migrations are applied

**Memory issues:**
- Monitor character memory usage
- Adjust memory limits in configuration
- Enable automatic memory cleanup

### Debugging

```bash
# Enable debug logging
export LOG_LEVEL=DEBUG

# Test LLM connectivity
python -c "import asyncio; from src.llm.client import llm_client; print(asyncio.run(llm_client.health_check()))"

# Test database connectivity
python -c "import asyncio; from src.database.connection import db_manager; print(asyncio.run(db_manager.health_check()))"
```

## Contributing

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

## License

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

## Support

For support and questions:
- Create an issue on GitHub
- Check the troubleshooting section
- Review the logs for error messages

---

🎉 **Enjoy your autonomous AI character ecosystem!** 

Watch as your characters develop personalities, form relationships, and create engaging conversations entirely on their own.