ds_zagres_ai/README.md

# OpenWebUI Backend Service

A backend service for OpenWebUI that provides OpenWebUI-compatible API endpoints for chat functionality and model switching.

## Features

- OpenWebUI-compatible API endpoints
- Ollama API proxy
- Chat functionality with model switching
- Support for multiple LLM models (gemma3, llama3.3, llama3.1, mistral, deepseek)
- Team chat functionality

## Technology Stack

- **Backend**: FastAPI
- **Chat Models**: Ollama models via OpenWebUI

## Project Structure

```
ai_service/
├── models/           # Model and chat services
│   ├── model_service.py
│   ├── chat_service.py
│   └── model_parameters.py
├── embeddings/       # Document processing for RAG
│   └── document_service.py
├── openwebui_api.py  # OpenWebUI-compatible API endpoints
├── config.py         # Configuration settings
├── api.py            # FastAPI application
└── deploy.sh         # Deployment script
openwebui-bot/        # OpenWebUI bot integration
run_ai_service.py     # Script to run the service
run_openwebui_bot.py  # Script to run the OpenWebUI bot
run_custom_bot.py     # Script to run a custom OpenWebUI bot
deploy_ai_service.sh  # Local deployment script
remote_deploy.sh      # Remote deployment script
```

## Setup Instructions

1. Create a virtual environment:
   ```
   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   ```

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

3. Copy `.env.example` to `.env` and update the values:
   ```
   cp ai_service/.env.example ai_service/.env
   # Edit the .env file with appropriate values
   ```

4. Run the service:
   ```
   python run_ai_service.py
   ```

## Deployment

To deploy the service:

1. Local deployment:
   ```
   ./deploy_ai_service.sh
   ```

2. Remote deployment:
   ```
   ./remote_deploy.sh [server_ip] [user] [port] [remote_dir]
   ```

## API Documentation

Once the service is running, you can access the API documentation at:
- Swagger UI: http://localhost:5252/docs
- ReDoc: http://localhost:5252/redoc

## OpenWebUI Configuration

To configure OpenWebUI to use this service as its backend:

1. Set the following environment variables in OpenWebUI:
   ```
   OLLAMA_API_BASE_URL=http://your-server-ip:5252/ollama
   OPENAI_API_BASE_URL=http://your-server-ip:5252/api
   ```

2. Restart OpenWebUI to apply the changes.

## OpenWebUI Bot Integration

This project includes integration with the [Open WebUI bot](https://github.com/open-webui/bot) to provide AI responses in OpenWebUI channels. See [BOT_README.md](BOT_README.md) for detailed instructions on how to use the bot.

### Bot Integration

The bot is integrated with the AI service and starts automatically when the service starts (if `BOT_ENABLED=true` in the `.env` file). The bot connects to OpenWebUI via WebSocket and listens for messages in channels. When a message mentions the AI (using trigger words like `@ai`), the bot processes the message and sends a response back to the channel.

### Bot API Endpoints

The AI service provides the following endpoints to manage the bot:

- `GET /bot/status`: Get the status of the bot (enabled and running)
- `POST /bot/start`: Start the bot if it's not already running
- `POST /bot/stop`: Stop the bot if it's running

You can also check the bot status in the configuration endpoint:

- `GET /config`: Get the current configuration, including bot status

### Running the Bot Separately

If you want to run the bot separately from the AI service, you can use the provided scripts:

```bash
# Run the original AI example
./run_openwebui_bot.py

# Or run our custom AI bot implementation
./run_custom_bot.py
```