# Aptos Hackathon

Project for Aptos Hackathon (backend)

## Features

- Execute AI pipelines using OpenAI models
- Integration with Model Context Protocol (MCP)
- Convenient Telegram bot interface
- Support for dynamic prompts and variables

## Running with Docker Compose (Recommended)

### Prerequisites

- Docker and Docker Compose installed
- `.env` file with required environment variables

### Setup

1. Copy `.env.example` to `.env` and configure the settings:

```bash
cp .env.example .env
```

2. Edit the `.env` file and set:
   - `OPENAI_API_KEY` - Your OpenAI API key
   - `TELEGRAM_BOT_TOKEN` - Your Telegram bot token (get it from @BotFather)
   - `MCP_SERVER_URL` - (Optional) MCP server URL

### Running the Application

Build and start the container:

```bash
docker-compose up --build -d
```

### Viewing Logs

```bash
docker-compose logs -f
```

### Stopping the Application

```bash
docker-compose down
```

## Local Development

### Prerequisites

- Bun installed
- Node.js

### Installing Dependencies

```bash
bun install
```

### Running the Application

In development mode with auto-reload:

```bash
bun --watch src/main.ts
```

Or in production mode:

```bash
bun run build
bun start
```

## Using the Bot

1. Find your bot on Telegram using the username you set with @BotFather
2. Start a chat with the bot
3. Send any message to the bot, and it will process it through the AI pipeline
4. The bot will respond with the AI's analysis or action

## Project Structure

- `src/bot/` - Telegram bot implementation
- `src/models/` - Data models and interfaces
- `src/pipelines/` - Pipeline execution logic
- `src/services/` - External service integrations
- `src/main.ts` - Application entry point

## Development

- Run linter: `bun run lint`
- Type checking: `bun run ts:check`
- Run all checks: `bun run check`
- Code formatting: `bun run lint:fix`

## License

MIT