project-platter 1.0.0

A CLI tool to serve up ready-to-go AI/automation project templates with Git and GitHub setup.

# 🧠 Project Platter

[![PyPI version](https://img.shields.io/pypi/v/project-platter.svg)](https://pypi.org/project/project-platter/)
[![Python](https://img.shields.io/badge/python-3.9%2B-blue.svg)](https://www.python.org/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)
[![Documentation Status](https://img.shields.io/badge/docs-online-brightgreen.svg)](https://Hamza-Ghaffar.github.io/Test_Platter/)
[![Build](https://img.shields.io/github/actions/workflow/status/Hamza-Ghaffar/project-platter/ci.yml?branch=main)](https://github.com/Hamza-Ghaffar/project-platter/actions)

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## 🚀 Overview

**Project Platter** is an open-source Python automation framework by **Hamza-Ghaffar**, built to streamline the setup and management of automation, agentic, and AI-based projects.

It’s a **plug-and-play project scaffolding system** designed for engineers, researchers, and developers who want to:

- ⚙️ Quickly bootstrap new Python or AI agent projects  
- 🧱 Maintain clean, consistent project structures  
- 🔗 Integrate GitHub repositories, CI/CD, and RAG workflows  
- 🤖 Extend automation using LangChain, OpenAI, or custom pipelines  
- 📈 Scale with reusable templates and automation commands  

Project Platter follows the same documentation and distribution standards as top-tier open-source libraries like **React**, **FastAPI**, and **LangChain**.

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## ⚙️ Installation

Install directly from **PyPI**:

```bash
pip install project-platter

Or install from source:

git clone https://github.com/Hamza-Ghaffar/project-platter.git
cd project-platter
pip install -e .

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🚀 Quick Usage

Create a new project scaffold instantly:

project-platter init my_project

Typical workflow:

# Initialize a structured project
project-platter init my_project

# List available CLI options
project-platter --help

# View or modify configuration
project-platter config --view

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🧩 CLI Commands

Command	Description
init <project_name>	Create a new project folder with default layout
config	Show or edit configuration settings
list	List available templates or modules
run <workflow>	Execute a defined automation pipeline
version	Display current version
--help	Show all available CLI commands

For full CLI documentation → see docs/cli.md

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🧱 Folder Structure

my_project/
├── data/                # Data inputs & outputs
├── logs/                # Logging and metrics
├── src/
│   ├── agents/          # AI agent modules
│   ├── models/          # ML or GenAI models
│   ├── pipelines/       # Workflows & orchestrations
│   └── utils/           # Utilities and helpers
├── configs/             # Config YAML/JSON files
├── tests/               # Unit & integration tests
└── requirements.txt     # Project dependencies

Each generated project is ready for:

• 🧩 Modular AI agent development
• ⚙️ CI/CD integration
• 🔧 Reusable templates
• 📦 Rapid deployment

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🧰 GitHub & CI/CD Integration

Project Platter supports GitHub automation out-of-the-box. When you initialize a new project, you can auto-generate:

• .github/workflows/ci.yml → Continuous Integration pipeline
• .gitignore → Optimized for Python, venv, and data artifacts
• Optional pre-commit hooks

You can connect your GitHub repository by running:

project-platter github init

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📘 Documentation

Comprehensive documentation will be hosted soon at: 👉 https://Hamza-Ghaffar.github.io/Test_Platter

The documentation includes:

• 🧠 Overview
• ⚙️ Installation
• 🚀 Usage Guide
• 🧩 CLI Details
• 🧱 Folder Structure
• 🧰 GitHub Integration
• 📘 API Reference
• 🤝 Contribution Guidelines

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🧠 Example (Python Integration)

You can also use Project Platter programmatically:

from project_platter.core import Platter

platter = Platter()
platter.create_project("my_project")
platter.run_pipeline("data_preprocess")

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🤝 Contributing

Contributions are warmly welcomed! ❤️

If you’d like to add features, fix bugs, or improve docs:

1. Fork the repository
2. Create a feature branch
3. Submit a pull request

Refer to docs/contributing.md for contribution standards.

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🪪 License

This project is licensed under the MIT License — see the LICENSE file for details.

MIT License

Copyright (c) 2025 Hamza-Ghaffar

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

[Full MIT License included in LICENSE file]

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🧩 Credits & Acknowledgments

Author: Hamza-Ghaffar Role: Software Automation Engineer & Researcher

This project leverages insights, APIs, and design inspiration from:

• OpenAI, LangChain, and RAG frameworks for GenAI integration
• FastAPI, React, and MkDocs open-source ecosystems for structural inspiration
• Developed with assistance from OpenAI’s GPT-based tools to accelerate documentation and automation workflows

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🌟 Support & Feedback

If you find Project Platter helpful:

• ⭐ Star the repo on GitHub → Hamza-Ghaffar/project-platter
• 🪶 Report issues or suggest enhancements in the Issues tab

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