CINEIQ 🎬

Project Status

This project is cuurently Active and under development. We are open to new contributions!

Next-Generation AI-Powered Movie Recommendation Platform

Overview

CINEIQ is a production-grade movie recommendation platform featuring advanced AI-driven personalized movie suggestions, real-time analytics, and a cinematic user interface.

1. FastAPI Backend — Advanced ML inference, personalized recommendations, robust data processing pipelines
2. Next.js 15 Frontend — Immersive, cinematic design system with Server-Side Rendering (SSR) for optimal performance

Architecture

┌─────────────────┐     ┌──────────────────┐
│  Next.js 15     │────▶│   FastAPI API    │
│  Frontend       │◀────│   (Backend)      │
└─────────────────┘     └──────────────────┘
                               │
                    ┌──────────┼──────────┐
                    ▼          ▼          ▼
              ┌──────────┐ ┌──────┐ ┌────────┐
              │PostgreSQL│ │Redis │ │Qdrant  │
              │   16     │ │  7   │ │ VecDB  │
              └──────────┘ └──────┘ └────────┘
                               │
                          ┌────────┐
                          │ MinIO  │
                          │Storage │
                          └────────┘

Quick Start

Prerequisites

• Docker & Docker Compose
• Node.js 20+ (for local frontend dev)
• Python 3.11+ (for local backend dev)

Run with Docker (Recommended)

The entire stack can be launched via Docker Compose:

cp .env.example .env
# Fill in API keys in .env
make dev
# or alternatively
docker-compose up --build

Run Locally (without Docker)

Backend:

cd backend
pip install -r requirements.txt
# Set up necessary env variables
uvicorn app.main:app --reload   # Start API server

Frontend:

cd frontend
npm install
npm run dev

Roadmap

-[ ] Implement user authentication (OAuth) -[ ] Add mobile responsiveness -[ ] Integrate real-time analytics dashboard -[ ] Expand AI recommendation models

Contributing

We welcome contributions!

1. Fork the repository.
2. Create a new branch: git checkout -b feature/your-feature-name
3. Make your changes and commit: git commit -m 'Add some feature'
4. Push to your branch: git push origin feature/your-feature-name
5. Open a Pull Request.

Technology Stack

• Backend: FastAPI, SQLAlchemy (async), AI/ML Pipelines
• Frontend: Next.js 15, React, Tailwind CSS / Vanilla CSS (Cinematic Design)
• Database: PostgreSQL 16
• Caching & Brokers: Redis 7
• Vector Search: Qdrant
• Object Storage: MinIO
• Containerization: Docker & Docker Compose

License

This project is licensed under the MIT License.