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Workshop Day 1 - Development Environment Setup

This guide will walk you through setting up your development environment for development, including WSL (for Windows users), VS Code, Git, UV package manager, and running your first AI text generation example using the Groq API.

Prerequisites

  • Windows 10/11 (for WSL setup) or macOS
  • Administrator/sudo access on your machine
  • Stable internet connection

Step 1: Install WSL (Windows Subsystem for Linux)

For Windows Users:

  1. Open Command Prompt (CMD) as Administrator

  2. Run the following command:

    wsl --install

  3. Restart your computer (this is required for WSL installation to complete)

  4. After restart, WSL will launch automatically. You'll be prompted to:

    • Create a username (use lowercase, no spaces)
    • Create a password (you won't see characters as you type - this is normal)
    • Confirm your password

  5. Verify WSL installation:

    wsl --version

    or

    wsl -l -v

For macOS Users:

  • Skip this step (you'll use the native Terminal)

Step 2: Install Visual Studio Code

  1. Download VS Code from https://code.visualstudio.com/ or from the Microsoft Store
  2. Install and open VS Code

Step 3: Install Required VS Code Extensions

Click on the Extensions icon in the left sidebar (or press Ctrl+Shift+X) and search for the following extensions:

1. WSL (Windows Subsystem for Linux)

  • Why: Allows VS Code to connect directly to your WSL environment, enabling seamless development within the Linux subsystem
  • For: Windows users only

2. vscode-pdf

  • Why: Enables you to view PDF documentation and reference materials directly within VS Code without switching applications

3. Rainbow CSV

  • Why: Provides color-coded columns when viewing CSV files, making data easier to read and analyze

Step 4: Connect VS Code to WSL

For Windows Users:

  1. Press Ctrl+Shift+P to open the Command Palette
  2. Type and select: "WSL: Connect to WSL"
  3. A new VS Code window will open connected to WSL

Note: You'll need to do this every time you want to develop in the WSL environment

For macOS Users:

  • Simply open VS Code and use the integrated terminal (`Ctrl+``)

Step 5: Create Project Directory

Open the terminal in VS Code (Ctrl+`) and run:

mkdir intel-training
cd intel-training

Step 6: Install Git

For WSL/Linux Users:

sudo apt-get update
sudo apt-get install git

For macOS Users:

  1. Install Homebrew (if not already installed):

    • Visit https://brew.sh and copy the installation command
    • Paste and run it in your terminal

  2. Install Git:

    brew install git

Why Git is Required: Git is a version control system that allows you to track changes in your code, collaborate with others, and access open-source projects. It's essential for modern software development.

Verify Git Installation:

git --version

Step 7: Configure Git

Set up your identity for Git commits:

git config --global user.name "Your Name"
git config --global user.email "your.email@example.com"

Step 8: Install UV Package Manager

Why UV is Required: UV is a modern, blazingly fast Python package and project manager. It's significantly faster than pip and conda, provides better dependency resolution, and simplifies virtual environment management. It's written in Rust, making it highly performant for installing packages and managing Python projects.

Why Choose UV Over Alternatives:

  • Speed: 10-100x faster than pip
  • Reliability: Better dependency resolution than pip
  • Simplicity: Combines the functionality of pip, pip-tools, pipx, poetry, and pyenv
  • Modern: Built with modern Python best practices in mind

  1. Visit the UV installation page: Google "install uv" or go to https://docs.astral.sh/uv/

  2. Copy and run the installation command in your terminal:

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

  3. Restart your terminal or run:

    source ~/.bashrc  # or source ~/.zshrc for macOS

  4. Verify UV Installation:

    uv --version

Step 9: Create a GitHub Account

Why GitHub is Required: GitHub is the world's largest platform for hosting and collaborating on code. It allows you to access open-source projects, contribute to repositories, showcase your work, and collaborate with developers worldwide. You'll use it to clone the workshop curriculum repository.

  1. Visit https://github.com
  2. Click "Sign up" and create an account
  3. Verify your email address

Step 10: Clone the Curriculum Repository

  1. Visit the curriculum repository: https://github.com/navchetna/curriculum

  2. Click the green "Code" button

  3. Copy the URL (should be: https://github.com/navchetna/curriculum.git)

  4. In VS Code terminal, run:

    git clone https://github.com/navchetna/curriculum.git
cd curriculum/

  5. Verify your location:

    pwd

    Expected output: /home/<your_username>/intel-training/curriculum (or as per your dev environment)

Step 11: Working with Groq API (Text Generation)

Navigate to the Groq Example

cd text-generation/api/groq

Create and Activate Virtual Environment

uv venv
source .venv/bin/activate

Install Dependencies

uv pip install -r requirements.txt

Set Up Groq API Key

  1. Obtain API Key:

    • Read the README.md file in the current directory for detailed instructions
    • Visit https://console.groq.com
    • Create an account and generate an API key

  2. Configure API Key:

    Option 1 - Create .env file (Recommended):

    # Create a .env file in the current directory
echo "GROQ_API_KEY=your_actual_api_key_here" > .env

    Option 2 - Export in terminal:

    export GROQ_API_KEY=your_actual_api_key_here

Understanding the Script

The inference.py script accepts command-line flags:

  • --prompt (required): The text prompt for the AI model
  • Additional optional flags are available (check the script for details)

Run Your First Inference

python inference.py --prompt="Describe Generative AI with examples"

Troubleshooting

WSL Issues

  • If WSL doesn't start after installation, run wsl --update in CMD
  • Check WSL status: wsl --status

Git Clone Fails

  • Ensure you have internet connection
  • Try using SSH instead of HTTPS (requires SSH key setup)

UV Installation Issues

  • Make sure curl is installed: sudo apt-get install curl
  • Check if UV is in PATH: echo $PATH

API Key Not Working

  • Ensure no extra spaces in the .env file
  • Check that the .env file is in the same directory as inference.py
  • Verify API key is valid on Groq console

Exploring Other API Providers

Now that you've successfully worked with the Groq API, you can explore other popular AI providers that follow similar steps:

Available Providers in the Curriculum

Navigate back to the API directory to see all available providers:

cd ..  # Go back to text-generation/api/
ls

Try These Providers:

  1. Google Gemini

    cd gemini
    • Similar setup process (create venv, install requirements, configure API key)
    • Obtain API key from Google AI Studio

  2. Hugging Face

    cd huggingface

Exercise: Try running the same prompt with different providers and compare the responses!

Next Steps

You've completed Day 1 setup. You now have:

  • A fully functional development environment
  • Git configured for version control
  • UV package manager installed
  • Successfully run an AI text generation example
  • Knowledge of how to work with multiple API providers

Challenge: Experiment with Gemini and Hugging Face APIs using the same workflow you learned with Groq!

Day 2 content will be provided separately.

Additional Resources

Last Updated: October 2025