👋 Hello AI World – Setting Up AI Environments with uv

A hands-on AI Summer School session showing you how to quickly set up Python environments for AI development using uv. We'll explore two modes: fun instant tools with uvx and serious project environments for training deep learning models.

🌟 What You'll Learn

• 🛡️ Why Virtual Environments Matter – Keep projects isolated and conflict-free
• ⚡ uv Basics – Fast installs, clean env management
• 🐄 Fun with Tools – Try out terminal toys instantly with uvx
• 🧠 Real ML Workflows – Train a Variational Autoencoder (VAE) in an isolated environment

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1️⃣ Why Virtual Environments?

Virtual environments let you:

• Avoid dependency conflicts between projects
• Share code with reproducible installs
• Experiment without breaking your system Python

tl;dr: They keep your projects clean, reproducible, and conflict‑free.

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2️⃣ Installing uv & Playing with Tools

Install uv

curl -LsSf https://astral.sh/uv/install.sh | sh

Tool Mode Fun 🐄

With uvx, you can run CLI tools instantly without installing them permanently:

uvx cowsay "Hello AI Scholars!"

• fortune prints a random quote
• cowsay makes a cow say it 🐮

Chain them for instant smiles.

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3️⃣ Create an Environment & Train a VAE

Step 1 – Add Project Files

git clone git@github.com:GauravR1206/Hello-AI-World.git
cd Hello-AI-World

Step 2 – Install Dependencies

uv sync

This creates & populates your virtual environment from pyproject.toml.

Step 3 – Train the Model

python train_VAE.py --epochs 20 --latent_dim 2```
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**🎉 That's it!** You’ve learned how to:

* Use `uv` for quick, fun CLI tools
* Create a clean, reproducible environment for ML
* Train a real deep learning model in minutes