QUICKSTART.md

# Quick Start Guide

## Installation

1. **Install dependencies with uv**
```bash
uv sync
```

2. **Install Playwright browsers**
```bash
uv run playwright install chromium
```

3. **Set up environment variables**
```bash
cp .env.example .env
```

Edit `.env` and configure at minimum:
- `STUDENT_SECRET` - Your secret key
- `STUDENT_EMAIL` - Your email
- `GITHUB_TOKEN` - GitHub personal access token
- `GITHUB_USERNAME` - Your GitHub username
- `ANTHROPIC_API_KEY` or `OPENAI_API_KEY` - LLM API key

## Running the System

### Option 1: Using main.py CLI

**Start Student API:**
```bash
uv run python main.py student-api
```

**Start Instructor API:**
```bash
uv run python main.py instructor-api
```

**Initialize Database:**
```bash
uv run python main.py init-db
```

**Run Round 1:**
```bash
uv run python main.py round1
```

**Run Evaluation:**
```bash
uv run python main.py evaluate
```

**Run Round 2:**
```bash
uv run python main.py round2
```

### Option 2: Direct module execution

**Start Student API:**
```bash
uv run python -m student.api
```

**Start Instructor API:**
```bash
uv run python -m instructor.api
```

## Testing the System

### 1. Test Student API

Start the student API:
```bash
uv run python main.py student-api
```

In another terminal, send a test request:
```bash
curl -X POST http://localhost:8000/api/build \
  -H "Content-Type: application/json" \
  -d '{
    "email": "your-email@example.com",
    "secret": "your-secret",
    "task": "test-task-abc",
    "round": 1,
    "nonce": "unique-nonce-123",
    "brief": "Create a simple Hello World page with Bootstrap",
    "checks": ["Page displays Hello World", "Bootstrap is loaded"],
    "evaluation_url": "http://localhost:8001/api/evaluate",
    "attachments": []
  }'
```

Check status:
```bash
curl http://localhost:8000/api/status/test-task-abc
```

### 2. Test Instructor Workflow

**Start Instructor API:**
```bash
uv run python main.py instructor-api
```

**Initialize Database:**
```bash
uv run python main.py init-db
```

**Create submissions.csv:**
```csv
timestamp,email,endpoint,secret
2025-01-15T10:00:00,student@example.com,http://localhost:8000/api/build,your-secret
```

**Run Round 1:**
```bash
uv run python main.py round1
```

**Run Evaluation:**
```bash
uv run python main.py evaluate
```

**Check Results:**
```bash
curl http://localhost:8001/api/results/student@example.com
```

## Project Structure Overview

```
student/              # Student side (receives tasks, generates code)
├── api.py           # API endpoint
├── code_generator.py # LLM code generation
├── github_manager.py # GitHub operations
└── notification_client.py # Notify evaluation

instructor/          # Instructor side (generates tasks, evaluates)
├── api.py          # Evaluation endpoint
├── database.py     # Database operations
├── task_templates.py # Template management
├── round1.py       # Generate round 1 tasks
├── round2.py       # Generate round 2 tasks
├── evaluate.py     # Run evaluations
└── checks/         # Evaluation checks
    ├── static_checks.py
    ├── dynamic_checks.py
    └── llm_checks.py

shared/             # Shared utilities
├── config.py       # Configuration
├── models.py       # Data models
├── logger.py       # Logging
└── utils.py        # Utilities

templates/          # Task templates (YAML)
```

## Next Steps

1. Configure your `.env` file with actual credentials
2. Set up a PostgreSQL database (if using instructor features)
3. Review the task templates in `templates/`
4. Test the student API with a simple request
5. Set up the instructor system for evaluation

## Common Issues

**Import errors**: Make sure you run commands with `uv run` prefix

**GitHub auth errors**: Verify GITHUB_TOKEN in .env has proper permissions

**Database errors**: Make sure PostgreSQL is running and DATABASE_URL is correct

**LLM errors**: Check your API key and quota

For more details, see README.md