# LiteLLM Discord Bot

A Discord bot that interfaces with LiteLLM proxy to provide AI-powered responses in your Discord server. Supports multiple LLM providers through LiteLLM, conversation history management, image analysis, and configurable system prompts.

## Features

- 🤖 **LiteLLM Integration**: Use any LLM provider supported by LiteLLM (OpenAI, Anthropic, Google, local models, etc.)
- 💬 **Conversation History**: Intelligent message history with token-aware truncation
- 🖼️ **Image Support**: Analyze images attached to messages (for vision-capable models)
- ⚙️ **Configurable System Prompts**: Customize bot behavior via file-based prompts
- 🔄 **Async Architecture**: Efficient async/await design for responsive interactions
- 🐳 **Docker Support**: Easy deployment with Docker

## Prerequisites

- **Python 3.11+** (for local development) or **Docker** (for containerized deployment)
- **Discord Bot Token** ([How to create one](https://www.writebots.com/discord-bot-token/))
- **LiteLLM Proxy** instance running ([LiteLLM setup guide](https://docs.litellm.ai/docs/proxy/quick_start))

## Quick Start

### Option 1: Running with Docker (Recommended)

1. Clone the repository:
```bash
git clone <repository-url>
cd OpenWebUI-Discordbot
```

2. Configure environment variables:
```bash
cd scripts
cp .env.sample .env
# Edit .env with your actual values
```

3. Build and run with Docker:
```bash
docker build -t discord-bot .
docker run --env-file scripts/.env discord-bot
```

### Option 2: Running Locally

1. Clone the repository and navigate to scripts directory:
```bash
git clone <repository-url>
cd OpenWebUI-Discordbot/scripts
```

2. Install dependencies:
```bash
pip install -r requirements.txt
```

3. Copy and configure environment variables:
```bash
cp .env.sample .env
# Edit .env with your configuration
```

4. Run the bot:
```bash
python discordbot.py
```

## Configuration

### Environment Variables

Create a `.env` file in the `scripts/` directory with the following variables:

```env
# Discord Bot Token - Get from https://discord.com/developers/applications
DISCORD_TOKEN=your_discord_bot_token

# LiteLLM API Configuration
LITELLM_API_KEY=sk-1234
LITELLM_API_BASE=http://localhost:4000

# Model name (any model supported by your LiteLLM proxy)
MODEL_NAME=gpt-4-turbo-preview

# System Prompt Configuration (optional)
SYSTEM_PROMPT_FILE=./system_prompt.txt

# Maximum tokens to use for conversation history (optional, default: 3000)
MAX_HISTORY_TOKENS=3000
```

### System Prompt Customization

The bot's behavior is controlled by a system prompt file. Edit `scripts/system_prompt.txt` to customize how the bot responds:

```txt
You are a helpful AI assistant integrated into Discord. Users will interact with you by mentioning you or sending direct messages.

Key behaviors:
- Be concise and friendly in your responses
- Use Discord markdown formatting when helpful (code blocks, bold, italics, etc.)
- When users attach images, analyze them and provide relevant insights
...
```

## Setting Up LiteLLM Proxy

### Quick Setup (Local)

1. Install LiteLLM:
```bash
pip install litellm
```

2. Run the proxy:
```bash
litellm --model gpt-4-turbo-preview --api_key YOUR_OPENAI_KEY
# Or for local models:
litellm --model ollama/llama3.2-vision
```

### Production Setup (Docker)

```bash
docker run -p 4000:4000 \
  -e OPENAI_API_KEY=your_key \
  ghcr.io/berriai/litellm:main-latest
```

For advanced configuration, create a `litellm_config.yaml`:
```yaml
model_list:
  - model_name: gpt-4-turbo
    litellm_params:
      model: gpt-4-turbo-preview
      api_key: os.environ/OPENAI_API_KEY
  - model_name: claude
    litellm_params:
      model: claude-3-sonnet-20240229
      api_key: os.environ/ANTHROPIC_API_KEY
```

Then run:
```bash
litellm --config litellm_config.yaml
```

See [LiteLLM documentation](https://docs.litellm.ai/) for more details.

## Usage

### Triggering the Bot

The bot responds to:
- **@mentions** in any channel where it has read access
- **Direct messages (DMs)**

Example:
```
User: @BotName what's the weather like?
Bot: I don't have access to real-time weather data, but I can help you with other questions!
```

### Image Analysis

Attach images to your message (requires vision-capable model):
```
User: @BotName what's in this image? [image.png]
Bot: The image shows a beautiful sunset over the ocean with...
```

### Message History

The bot automatically maintains conversation context:
- Retrieves recent relevant messages from the channel
- Limits history based on token count (configurable via `MAX_HISTORY_TOKENS`)
- Only includes messages where the bot was mentioned or bot's own responses

## Architecture Overview

### Key Improvements from OpenWebUI Version

1. **LiteLLM Integration**: Switched from OpenWebUI to LiteLLM for broader model support
2. **Proper Conversation Format**: Messages use correct role attribution (system/user/assistant)
3. **Token-Aware History**: Intelligent truncation to stay within model context limits
4. **Async Image Downloads**: Uses `aiohttp` instead of synchronous `requests`
5. **File-Based System Prompts**: Easy customization without code changes
6. **Better Error Handling**: Improved error messages and validation

### Project Structure

```
OpenWebUI-Discordbot/
├── scripts/
│   ├── discordbot.py          # Main bot code (production)
│   ├── system_prompt.txt      # System prompt configuration
│   ├── requirements.txt       # Python dependencies
│   └── .env.sample           # Environment variable template
├── v2/
│   └── bot.py                # Development/experimental version
├── Dockerfile                # Docker containerization
├── README.md                 # This file
└── claude.md                 # Development roadmap & upgrade notes
```

## Upgrading from OpenWebUI

If you're upgrading from the previous OpenWebUI version:

1. **Update environment variables**: Rename `OPENWEBUI_API_BASE` → `LITELLM_API_BASE`, `OPENAI_API_KEY` → `LITELLM_API_KEY`
2. **Set up LiteLLM proxy**: Follow setup instructions above
3. **Install new dependencies**: Run `pip install -r requirements.txt`
4. **Optional**: Customize `system_prompt.txt` for your use case

See `claude.md` for detailed upgrade documentation and future roadmap (MCP tools support, etc.).