Vibe Discord Bot with RAG Chat History

A Discord bot that stores long-term chat history using SQLite with RAG (Retrieval-Augmented Generation) capabilities. It supports custom bots with personalities, text-to-speech via Kokoro, image generation, and image editing.

• Vibe Discord Bot with RAG Chat History
  • Available Commands
    • Custom Bot Management
    • Using Custom Bots
    • Text-to-Speech
    • Image Commands
    • Bot Conversations
    • Chat History
  • Features
  • Setup
    • Prerequisites
    • Environment Variables
    • Installation
    • Running the Bot
  • How It Works
    • Database Structure
    • RAG Process
  • File Structure
  • Building
    • Local
    • Container
  • Testing
  • Configuration

Available Commands

Custom Bot Management

Command	Description	Example Usage
!custom-bot <name> <personality>	Create a custom bot with a personality	!custom-bot alfred you are a proper british butler
!list-custom-bots	List all available custom bots	!list-custom-bots
!delete-custom-bot <name>	Delete your custom bot (owner only)	!delete-custom-bot alfred

Using Custom Bots

Once you create a custom bot, interact with it by prefixing your message with the bot name:

!<bot_name> <your message>

Example:

1. Create a bot: !custom-bot alfred you are a proper british butler
2. Use the bot: alfred Could you fetch me some tea?
3. The bot will respond in character as a British butler

Text-to-Speech

Command	Description	Example Usage
!speak <text>	Convert text to speech (MP3 attachment)	!speak hello world
!speak <text> --voice <voice>	Convert text to speech with a specific voice	!speak hello world --voice af_bella
!speak <bot_name> <text>	Have a custom bot respond and speak	!speak alfred what time is it
!speak <bot_name> <text> --voice	Have a custom bot respond and speak with a voice	!speak alfred what time is it --voice am_puck
!voices	List all available TTS voices by category	!voices

Image Commands

Command	Description	Example Usage
!doodlebob	Generate an image from a text prompt	!doodlebob a cat sitting on the moon
!retcon	Edit an attached image with text	!retcon <image attachment> Make it sunny

Bot Conversations

Command	Description	Example Usage
!talkforme <bot1> <bot2> <n> <topic>	Have two bots discuss a topic for n replies	!talkforme alfred jarvis 4 the meaning of life

Chat History

Command	Description	Example Usage
!history <bot_name>	View the chat history of a custom bot	!history alfred

Features

• Long-term chat history storage: Persistent storage of all bot interactions in SQLite
• RAG-based context retrieval: Smart retrieval of relevant conversation history using vector embeddings
• Custom bots: Create unlimited bots with unique personalities
• Text-to-speech: Kokoro TTS engine converts bot responses to MP3 audio
• Image generation: Generate images from text prompts via OpenAI-compatible API
• Image editing: Edit uploaded images with text instructions
• Bot conversations: Two custom bots can discuss a topic autonomously
• Chat history: View the full conversation history of any custom bot with !history
• Automatic message cleanup: Configurable limits on stored messages

Setup

Prerequisites

• Python 3.13 or higher
• uv package manager
• Discord bot token
• OpenAI-compatible API endpoints (for chat, embeddings, and image generation)

Environment Variables

Create a .env file with the following variables:

# Discord Bot Token (required)
DISCORD_TOKEN=your_discord_bot_token

# Chat/Completion API (required)
CHAT_ENDPOINT=https://your-api.com/v1
COMPLETION_ENDPOINT=https://your-api.com/v1
CHAT_ENDPOINT_KEY=your_api_key
COMPLETION_ENDPOINT_KEY=your_api_key
CHAT_MODEL=your_model_name
COMPLETION_MODEL=your_model_name

# Image Generation (required)
IMAGE_GEN_ENDPOINT=https://your-api.com/v1
IMAGE_EDIT_ENDPOINT=https://your-api.com/v1
IMAGE_GEN_ENDPOINT_KEY=your_api_key
IMAGE_EDIT_ENDPOINT_KEY=your_api_key
IMAGE_GEN_MODEL=gen
IMAGE_EDIT_MODEL=edit

# Embedding API (required)
EMBEDDING_ENDPOINT=https://your-api.com/v1
EMBEDDING_ENDPOINT_KEY=your_api_key
EMBEDDING_MODEL=your_embed_model

# Optional: TTS Configuration
TTS_MODEL_PATH=kokoro-v1.0.onnx
TTS_VOICES_PATH=voices-v1.0.bin
TTS_VOICE=af_sarah
TTS_SPEED=1.0

# Optional: Database/Chat Settings
DB_PATH=chat_history.db
MAX_COMPLETION_TOKENS=1000
MAX_HISTORY_MESSAGES=1000
SIMILARITY_THRESHOLD=0.7
TOP_K_RESULTS=5

Installation

1. Clone the repository and sync dependencies:

   uv sync
   

2. Ensure the TTS model files are present in the project root:

   • kokoro-v1.0.onnx
   • voices-v1.0.bin

Running the Bot

uv run python -m vibe_bot.main

How It Works

Database Structure

The system uses SQLite with three tables:

1. chat_messages: Stores message metadata

   • message_id, user_id, username, content, bot_name, timestamp, channel_id, guild_id

2. message_embeddings: Stores vector embeddings for RAG

   • message_id (PK), embedding (binary blob of float32 values)

3. custom_bots: Stores custom bot configurations

   • bot_name (PK), system_prompt, created_by, created_at, is_active

RAG Process

1. When a message is sent to a custom bot, it's stored in chat_messages
2. An embedding is generated via the configured embedding API and stored in message_embeddings
3. When a new message is sent:
   • The system retrieves recent messages from the same user
   • It searches for semantically similar messages using cosine similarity on embeddings
   • Relevant context (user + bot message pairs) is prepended to the prompt
   • The LLM generates a response with awareness of past conversations

File Structure

vibe_discord_bots/
├── vibe_bot/
│   ├── __init__.py            # Package marker
│   ├── main.py                # Main bot application (commands, event handlers)
│   ├── config.py              # Environment variable loading and validation
│   ├── database.py            # SQLite database with RAG + CustomBotManager
│   ├── llama_wrapper.py       # OpenAI-compatible API wrappers (chat, images, embeddings)
│   ├── tts.py                 # Kokoro TTS engine
│   └── tests/
│       ├── conftest.py        # Shared test fixtures
│       ├── test_main.py       # Bot command tests
│       ├── test_config.py     # Config loading tests
│       ├── test_database.py   # Database + CustomBotManager tests
│       ├── test_llama_wrapper.py  # API wrapper tests
│       └── test_tts.py        # TTS engine tests
├── pyproject.toml             # Project dependencies (uv)
├── uv.lock                    # Locked dependency versions
├── .env                       # Environment variables
├── kokoro-v1.0.onnx           # Kokoro TTS model
├── voices-v1.0.bin            # Kokoro voice definitions
├── Containerfile              # Podman/Docker build file
└── README.md                  # This file

Building

Local

# Sync dependencies
uv sync

# Run the bot
uv run python -m vibe_bot.main

Container

# Build the container image
podman build -t vibe-bot:latest .

# Run with environment file
podman run --env-file .env localhost/vibe-bot:latest

Testing

Run the full test suite:

uv run pytest vibe_bot/tests/ -v

Run linters:

# Ruff (linter + formatter)
uv run ruff check vibe_bot/

# Mypy (type checking)
uv run mypy vibe_bot/

# Pyright (type checking)
uv run pyright vibe_bot/

# Black (formatter check)
uv run black --check vibe_bot/

Configuration

Variable	Default	Description
DISCORD_TOKEN	(required)	Discord bot authentication token
CHAT_ENDPOINT	(required)	OpenAI-compatible chat API URL
CHAT_MODEL	(required)	Model name for chat completions
IMAGE_GEN_ENDPOINT	(required)	Image generation API URL
IMAGE_EDIT_ENDPOINT	(required)	Image editing API URL
EMBEDDING_ENDPOINT	(required)	Embedding API URL
EMBEDDING_MODEL	(required)	Model name for text embeddings
MAX_COMPLETION_TOKENS	1000	Max tokens in LLM responses
MAX_HISTORY_MESSAGES	1000	Max messages kept in the database
SIMILARITY_THRESHOLD	0.7	Min cosine similarity for RAG context
TOP_K_RESULTS	5	Number of similar messages retrieved
TTS_MODEL_PATH	kokoro-v1.0.onnx	Path to Kokoro ONNX model file
TTS_VOICES_PATH	voices-v1.0.bin	Path to Kokoro voices binary file
TTS_VOICE	af_sarah	Default voice for TTS
TTS_SPEED	1.0	Speech speed multiplier
DB_PATH	chat_history.db	SQLite database file path