Generative AI

Welcome to the Generative AI repository, where we explore various aspects of cloud-applied generative AI engineering. This project is part of the PIAIC (Presidential Initiative for Artificial Intelligence & Computing) learning program.

Table of Contents

• About
• Project Structure
• Installation
• Usage
• Contributing
• License
• Contact

About

This repository contains a collection of projects and exercises focused on generative AI, cloud computing, and related technologies. The goal is to learn and apply advanced AI concepts in practical scenarios.

Technologies Used

• Python
• Docker
• Kafka
• Docker-Compose
• PostgreSQL
• Poetry
• FastAPI
• SQLModel
• PIAIC
• Panaverse
• Codehunts

Project Structure

Generative-AI/
├── CrewAI/
├── Docker-Compose/
├── Docker/fastapi_database/
├── FastAPI/
├── Kafka/
├── Kong/
├── Practice/day01/
├── Python with Poetry/
├── TODO/Fullstack-Todo-App-with-FastAPI-SQLModel/
├── Tasks/Class1/fastapi-neon/
├── groqCloud/
├── oAuth/
└── README.md

Folders and Contents

• CrewAI: Adding crewAI (Latest update)
• Docker-Compose: Initial setup for Docker-Compose
• Docker/fastapi_database: FastAPI with Docker and database configuration
• FastAPI: Examples and projects using FastAPI
• Kafka: Kafka messaging with Kafka UI
• Kong: API Gateway with Kong
• Practice/day01: Day 01 practice exercises
• Python with Poetry: Python projects managed with Poetry
• TODO/Fullstack-Todo-App-with-FastAPI-SQLModel: A full-stack TODO application using FastAPI and SQLModel
• Tasks/Class1/fastapi-neon: Class tasks related to FastAPI and Neon
• groqCloud: Cloud-related projects
• oAuth: OAuth integration examples

Installation

To get started with this repository, follow these steps:

1. Clone the repository:

   git clone https://github.com/hmzi67/Generative-AI.git

2. Navigate to the project directory:

    cd Generative-AI

3. Set up your environment (example using Poetry):

   poetry install