Metadata-Version: 2.4
Name: airflow-tutor-agent
Version: 1.0.0
Summary: A beginner-focused AI Tutor Agent to help freshers set up Apache Airflow locally.
Home-page: https://github.com/yourusername/airflow-tutor-agent
Author: Your Name
Author-email: your.email@example.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: typer>=0.9.0
Requires-Dist: rich>=13.0.0
Requires-Dist: pydantic>=2.0.0
Requires-Dist: python-dotenv>=1.0.0
Requires-Dist: openai>=1.0.0
Requires-Dist: jinja2>=3.0.0
Requires-Dist: colorama>=0.4.6
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# Airflow Tutor Agent 🤖✈️

A complete beginner-focused AI Tutor designed to help freshers step-by-step through setting up Apache Airflow 3.x locally on Windows, macOS, or Linux. 

## Project Goal
This agent doesn't just run a bash script to install Airflow. It stops, explains what each command does, asks the student to verify the output, and provides an immediate rule-based troubleshooting engine if they hit a wall. Finally, it teaches them core Airflow concepts and walks them through running their first beginner DAG.

## Features
- **Deterministic Preflight Checks**: Verifies Python, Docker, Port 8080.
- **Auto-Recommendation Engine**: Recommends *Docker Compose* for Windows and *pip + venv* for macOS/Linux.
- **Guided Setup Mode**: Gives short 1-line commands and waits for confirmation.
- **Troubleshooting Engine**: Catches `Exit Code 137`, `Port 8080 in use`, `Python version mismatch`.
- **Teaching Mode**: Explains `DAGs`, `Tasks`, `Schedulers`, and runs a sample payload.

## How to Run it Locally

1. Clone this repository (or copy the generated folder).
2. Install Python 3.8+ if you haven't already.
3. Open a terminal and navigate to this folder.
4. Run:
```bash
python -m venv venv
# Windows: .\venv\Scripts\activate
# Mac/Linux: source venv/bin/activate
pip install -r requirements.txt
```
5. Start the Tutor!
```bash
python -m app.main start
```

### Preflight Only
If you just want to run the system checks without launching the interactive tutor:
```bash
python -m app.main check
```
Or execute the raw shell scripts in `/scripts`.

## Architecture
See `docs/architecture.md` for a full breakdown. It uses `Typer` and `Rich` for a beautiful CLI interface.

## Support OS & Methods
- **Windows**: Target method -> Docker Compose
- **macOS / Linux**: Target method -> pip + venv (standalone)
- **Advanced Optional**: Kubernetes with Helm

## Security Notes
This is meant strictly for local learning on `localhost:8080`.
- Do not expose port 8080 to the public internet.
- Never commit `airflow.cfg` or `.env` files with generated secret keys to GitHub.
- Airflow's standalone password defaults are NOT safe for production!
