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Learning Cloud Applied Generative AI Engineering from PIAIC

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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

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