Dockerize the bashar bot

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# Docker Deployment Guide
## Quick Start
1. **Copy environment file:**
```bash
cp .env.example .env
```
2. **Edit .env with your Discord token:**
```bash
# Edit .env and add your DISCORD_TOKEN
```
3. **Build and run with Docker Compose:**
```bash
docker-compose up -d
```
4. **View logs:**
```bash
docker-compose logs -f basharbot
```
## Portainer Deployment
### Method 1: Using Portainer Stacks
1. Log into Portainer
2. Go to **Stacks** → **Add stack**
3. Name it `basharbot`
4. Choose **Upload** and upload `docker-compose.yml`
5. Add environment variables in the **Environment variables** section:
- `DISCORD_TOKEN`: Your Discord bot token
- `WHISPER_MODEL_SIZE`: small (or tiny/base/medium/large)
- `LOG_LEVEL`: INFO
6. Click **Deploy the stack**
### Method 2: Using Git Repository
1. In Portainer, go to **Stacks** → **Add stack**
2. Choose **Repository**
3. Enter your Git repository URL
4. Set compose path: `docker-compose.yml`
5. Add environment variables
6. Click **Deploy the stack**
## Configuration
All configuration is done via environment variables in `.env`:
- `DISCORD_TOKEN`: Your Discord bot token (required)
- `WHISPER_MODEL_SIZE`: Model size for speech recognition (tiny/small/base/medium/large)
- `LOG_LEVEL`: Logging level (DEBUG/INFO/WARNING/ERROR)
- `TRANSCRIPT_LOG_ENABLED`: Enable transcript logging (true/false)
- `HOTWORD_ENABLED`: Enable hotword detection (true/false)
- `GOODBOY_USER_ID`: Special user ID for goodboy audio
## Volumes
- `./logs`: Bot and transcript logs
- `./data`: Persistent data
- `whisper-models`: Cached Whisper AI models
## Commands
```bash
# Start the bot
docker-compose up -d
# Stop the bot
docker-compose down
# View logs
docker-compose logs -f
# Restart the bot
docker-compose restart
# Rebuild after code changes
docker-compose up -d --build
# Remove everything including volumes
docker-compose down -v
```
## Troubleshooting
**Bot won't start:**
- Check logs: `docker-compose logs basharbot`
- Verify DISCORD_TOKEN is set correctly in .env
**Audio issues:**
- Ensure ffmpeg is installed in container (included in Dockerfile)
- Check opus library is available
**High memory usage:**
- Use smaller Whisper model: `WHISPER_MODEL_SIZE=tiny`
- Reduce model compute type in stt.py
## Updates
To update the bot:
```bash
git pull
docker-compose up -d --build
```