ai-chat-platform

Full stack AI Chat SaaS with React + Flask + Ollama (Local LLM)

AI Chat Platform (Full Stack SaaS)

Full Stack AI Chat SaaS built with:

• React + TypeScript (Frontend)
• Flask (Backend API)
• Ollama Local LLM
• JWT Authentication
• Chat History System
• Admin & User Management

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Project Structure

ai-chat-platform/ │ ├── ai-chat-backend/ │ ├── models/ │ ├── routes/ │ ├── services/ │ ├── utils/ │ ├── schemas/ │ ├── db/ │ ├── app.py │ ├── config.py │ └── requirements.txt │ ├── ai-chat-frontend/ │ ├── src/ │ ├── package.json │ └── vite.config.ts │ ├── generate_token.py ├── response.json └── README.md

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🔧 Backend Setup cd ai-chat-backend python -m venv venv

▶ Activate Virtual Environment

Windows:

venv\Scripts\activate

Mac/Linux:

source venv/bin/activate

▶ Install Dependencies pip install -r requirements.txt

▶ Run Server python app.py

Backend runs on:

http://127.0.0.1:5000

💻 Frontend Setup cd ai-chat-frontend npm install npm run dev

Frontend runs on:

http://localhost:3000

🔐 Authentication Features

JWT-based authentication

Token expiration handling

Middleware-protected routes

Role-based access control (Admin / User)

🧠 AI Integration

Supports:

Ollama local models

Easily extendable to OpenAI API

📊 Features

✅ Create new chats

✅ Persistent chat history per user

✅ Dark mode UI

✅ Admin routes & management

✅ Message limits

✅ Secure backend architecture

✅ Tests & CI

Backend Tests

cd ai-chat-backend
pip install -r requirements.txt
pip install -r requirements-dev.txt
pytest

Runs the backend test suite (request validation, auth/registration flow, token counting, rate limiting, and config defaults) against an isolated throwaway SQLite database — no network, external services, or a live Ollama server needed.

CI

GitHub Actions (.github/workflows/ci.yml) runs on every push/PR to main:

• backend-tests — installs the backend dependencies and runs pytest
• frontend-build — installs frontend deps with npm ci and runs npm run build

📌 Version

Current Version: v3.0

🚀 Future Improvements

Docker deployment

CI/CD pipeline

Streaming AI responses

API rate limiting

Production database (PostgreSQL)

Cloud deployment support

👨‍💻 Author

DSK — AI Developer