README.md

metadata

title: AI REST API Generator
emoji: 🤖
colorFrom: blue
colorTo: purple
sdk: docker
app_port: 7860
pinned: false
license: mit

🤖 AI REST API Generator

AI REST API Generator is a developer-focused tool that automatically generates Django REST Framework backends using AI or manual configuration. It converts high-level requirements into a fully structured, runnable Django project with CRUD APIs, serializers, views, URLs, and settings.

🚧 Status: Under active development 📧 Contact: harshadhole04@gmail.com

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✨ Features

• ⚡ AI-Powered Backend Generation

  • Generate Django REST APIs from natural language prompts
  • Automatically infers models, fields, and relationships

• 🧱 Manual Model Builder

  • Define models, fields, relationships (One-to-One, One-to-Many)
  • Full control without AI if preferred

• 🧩 Schema-Driven Architecture

  • JSON Schema validation before code generation
  • Auto-fixes common schema issues safely

• 📦 Complete Django Project Output

  • Models, serializers, views, URLs
  • JWT authentication support
  • Database configuration (SQLite / PostgreSQL)
  • Static & media configuration

• 📥 One-Click Download

  • Generated backend is zipped and ready to run

• 🧠 Pluggable LLM Support

  • OpenAI
  • Groq
  • Easy to extend for other providers

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🏗️ Architecture Overview

Streamlit UI
   ↓
Pipeline Orchestrator
   ↓
LLM (Model Prompt / Spec Generation)
   ↓
Schema Validation (JSON Schema)
   ↓
Django Code Generator
   ↓
Ready-to-run Django REST Project

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🚀 How It Works

1. Input

   • Project name & description
   • Choose AI-generated models or manual models
   • Select database and authentication
   • Provide LLM provider and API key

2. Validation

   • Generated spec is validated against a strict JSON schema
   • Automatic normalization and safe fixes applied

3. Generation

   • Django project is created in an isolated run directory
   • Apps, models, serializers, views, URLs, settings generated

4. Output

   • Project is zipped
   • Download instantly from the UI

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🖥️ Running Locally

1️⃣ Clone the Repository

git clone https://github.com/harshadSH/ai-rest-api-generator.git
cd ai-rest-api-generator

2️⃣ Create Virtual Environment

python -m venv venv
source venv/bin/activate   # Windows: venv\Scripts\activate

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Run the Streamlit App

streamlit run app.py

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📂 Generated Project Structure

project_name/
├── manage.py
├── project_name/
│   ├── settings.py
│   ├── urls.py
│   └── wsgi.py
├── core/
│   ├── models.py
│   ├── serializers.py
│   ├── views.py
│   ├── urls.py
│   └── admin.py
├── requirements.txt
└── README.md

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🛡️ Authentication

• Supports JWT Authentication
• All CRUD endpoints can be protected
• Easily extendable to session-based auth

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🧪 Validation & Reliability

• Strict JSON Schema enforcement

• Deterministic naming conventions

• Auto-correction of:

  • Database engine names
  • Model and field naming
  • Missing required fields

• Prevents invalid or unsafe Django code generation

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🌍 Deployment

This project is suitable for:

• Local development
• Docker-based deployment
• Cloud hosting (AWS, Azure, GCP, Railway, Render)

⚠️ Note: Production hardening (rate limiting, monitoring, secrets management) should be added as per deployment needs.

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📜 License

This project is licensed under the MIT License. You are free to use, modify, and distribute it with attribution.

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👨‍💻 Author

Harshad Hole Bachelor of Engineering – Artificial Intelligence & Data Science 📧 Email: harshadhole04@gmail.com

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⭐ Why This Project Matters

• Solves repetitive backend boilerplate
• Demonstrates real-world use of LLMs in software engineering
• Combines AI + validation + deterministic code generation
• Strong portfolio-grade project for AI / Backend / Full-Stack roles

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If you want, I can also:

• Write a “Project Motivation” section
• Optimize README for Hugging Face Spaces
• Add badges (Python, Django, MIT, AI)
• Review it from a recruiter’s perspective

Just tell me 👍