Discord Character Chat Game

A Discord bot that allows users to chat with virtual characters. This project implements a character selection system with memory, affinity tracking, and customization.

Features

• Character selection using !select command
• Automatic user registration
• Conversation memory tracking
• Character-user relationship (affinity) tracking
• Customizable character details
• Optimized database connection pooling
• Robust error handling and retry mechanisms
• Performance improvements for AI chat

Setup Instructions

Installation

This project uses NoneBot framework and it is recommended to use pipx for installation.

For more details, check the documentation.

1. Install pipx

2. Install NoneBot scaffolding

   pipx install nb-cli

3. Create a .env file from the template and fill in the required environment variables.

4. Run the main.py script

   python main.py

Environment Variables

The following environment variables are required:

• DISCORD_BOT_TOKEN: Your Discord bot token
• OPENAI_API_KEY: Your OpenAI API key
• DATABASE_USER: Database username
• DATABASE_PASSWORD: Database password
• DATABASE_HOST: Database host
• DATABASE_PORT: Database port
• DATABASE_NAME: Database name

For Team Development

Option 1: Individual Test Bots

1. Create your own Discord bot in the Discord Developer Portal
2. Enable Message Content Intent under the Bot settings
3. Use your bot's token in your local .env file
4. Run the bot locally for testing

Commands

• !select <character_name> - Select a character to chat with

Technical Improvements

The following optimizations have been implemented:

1. Database Connection Pooling:

   • Improved connection validation and reconnection
   • Better error handling for database operations
   • Connection pool with proper resource management

2. Error Handling and Retry Mechanisms:

   • Added retry with exponential backoff for OpenAI API calls
   • Better error logging and categorization
   • Type-safe validation for user inputs

3. Performance Optimizations:

   • LRU caching for frequently used data
   • Message history management to prevent memory issues
   • Specific error handling for different API error types

4. Memory Management:

   • Improved affinity value validation
   • Automatic context pruning to maintain performance
   • Better input validation