🚀 FastAPI React Chat: Full-Stack AI Assistant

A powerful, full-stack AI Chat application built to master modern web development technologies. This project seamlessly integrates a high-performance FastAPI backend with a dynamic React frontend, utilizing PostgreSQL for robust data persistence and OpenAI for intelligent responses.

Designed with N-Layer Architecture, this project serves as a comprehensive example of building scalable, maintainable, and production-ready software systems.

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✨ Features

• 🤖 Intelligent Chat: Powered by OpenAI's GPT models for natural, context-aware conversations.
• 🧠 Conversation Memory: Remembers past messages within a session for coherent dialogue.
• 💾 Persistent History: All chats are saved in a PostgreSQL database using SQLAlchemy ORM.
• 🎨 Modern UI: A responsive, dark-mode enabled interface built with React, Vite, and custom CSS (Glassmorphism).
• 📱 Mobile Responsive: Fully optimized for mobile devices with a collapsible sidebar and touch-friendly controls.
• ⚡ High Performance: Async capabilities of FastAPI ensure lightning-fast responses.
• 🔒 Secure: JWT-based structure (ready for expansion) and environment variable management.
• 🏗️ N-Layer Architecture:
  • API Layer: Handles HTTP requests and routing.
  • Service Layer: Contains business logic.
  • Data Layer: Manages database interactions (DAO pattern).
  • Domain Layer: Defines core entities and models.

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🛠️ Technology Stack

Component	Technology
Backend	Python, FastAPI, Uvicorn, SQLAlchemy
Frontend	React, Vite, JavaScript, CSS3
Database	PostgreSQL
AI Engine	OpenAI API
Tools	Git, Docker (Optional), ngrok

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🚀 Quick Start

Prerequisites

• Python 3.10+
• Node.js & npm (for frontend development)
• PostgreSQL installed and running

One-Click Launch (Recommended)

This project includes a smart startup script baslat.bat that handles everything for you:

1. Sets up the environment.
2. Starts the generic Uvicorn server.
3. Launches the application in your browser (http://localhost:8000).
4. (Optional) Starts ngrok tunneling if available.

Just double-click baslat.bat in the root directory!

Manual Setup

1. Clone the repository:

   git clone https://github.com/azizdeniz890/fastapi-react-chat.git
   cd fastapi-react-chat

2. Create Virtual Environment:

   python -m venv venv
   .\venv\Scripts\activate

3. Install Base Dependencies:

   pip install -r requirements.txt

4. Configure Environment: Create a .env file (or set variables in baslat.bat) with:

   DATABASE_URL=postgresql://user:password@localhost/dbname
   OPENAI_API_KEY=sk-...

5. Run Application:

   uvicorn app.main:app --reload

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📂 Project Structure

fastapi-react-chat/
├── app/                  # Backend Application (N-Layer Architecture)
│   ├── api/              # API Layer (Endpoints & Schemas)
│   ├── auth/             # Authentication (JWT & Rate Limiting)
│   ├── config/           # Configuration Settings
│   ├── data/             # Data Access Layer (DAO & Database Connection)
│   ├── domain/           # Domain Entities & Models
│   ├── infra/            # Infrastructure (OpenAI Client)
│   ├── service/          # Business Logic Layer
│   └── main.py           # Application Entry Point
├── frontend/             # React Frontend
│   ├── src/              # Components, Hooks, & Styles
│   └── index.html        # Entry HTML
├── static/               # Compiled Frontend Assets
├── docs/                 # Documentation Images
├── requirements.txt      # Python Dependencies
├── baslat.bat            # One-Click Startup Script
└── README.md             # Project Documentation

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🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

This project is open-source and available under the MIT License.

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Note: This project was built for educational purposes to demonstrate full-stack development skills.