Generative-IA

A collection of practical examples demonstrating how to build applications with Generative AI using Large Language Models (LLMs), prompt engineering, and AI APIs.

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🚀 Overview

This repository contains hands-on examples for learning and experimenting with Generative AI technologies, including:

• Prompt Engineering
• Chat Completion APIs
• AI-powered Python applications
• LLM integrations
• API authentication
• Best practices for working with AI models

The project is intended for developers who want to understand how to build applications powered by modern Generative AI models.

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📂 Project Structure

Generative-IA/
│
├── examples/            # Example applications
├── prompts/             # Prompt templates
├── data/                # Sample datasets (if applicable)
├── requirements.txt
├── README.md
└── *.py                 # Python source files

The exact structure may vary depending on the project.

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⚙️ Requirements

• Python 3.10+
• pip
• API key for the AI provider used in the examples

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📦 Installation

Clone the repository:

git clone https://github.com/rubencruz/Generative-IA.git
cd Generative-IA

Create a virtual environment:

python -m venv .venv

Activate it:

Windows

.venv\Scripts\activate

Linux / macOS

source .venv/bin/activate

Install dependencies:

pip install -r requirements.txt

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🔑 Environment Variables

Create a .env file and configure your API credentials:

API_KEY=your_api_key_here

Depending on the provider used, you may need variables such as:

OPENAI_API_KEY=
GEMINI_API_KEY=
IBM_API_KEY=

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▶️ Running the Examples

Run a Python example:

python example.py

or

python app.py

Replace the filename with the example you want to execute.

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📚 Topics Covered

• Generative AI fundamentals
• Prompt Engineering
• Chat models
• AI APIs
• Python integration
• Error handling
• Environment variables
• Best practices

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🛠 Technologies

• Python
• Generative AI APIs
• Large Language Models (LLMs)
• REST APIs
• dotenv

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📖 Learning Objectives

After completing these examples, you'll understand how to:

• Connect to AI APIs
• Send prompts to LLMs
• Process model responses
• Build conversational applications
• Manage API keys securely
• Structure AI-powered Python projects

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🤝 Contributing

Contributions are welcome!

Feel free to:

• Open an Issue
• Submit a Pull Request
• Improve documentation
• Add new AI examples

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📄 License

This project is licensed under the MIT License.

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👤 Author

Ruben Cruz

GitHub: https://github.com/rubencruz

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