Zebra668/movie-recommender
0
๐ฌ CineRec โ Movie Recommendation System
S-Class cinematic movie recommender with 3 AI strategies + sentiment analysis.
Tech Stack
3 Recommendation Strategies
- Content-Based โ Genre, keywords, cast se similar movies
- Collaborative Filtering โ User ratings ke pattern se
- Hybrid โ Dono ka combination (best results)
๐ Deploy Steps
Step 1: Backend โ Hugging Face Spaces
- HuggingFace pe new Space banao
- SDK: Docker
- Name:
movie-recommender - Visibility: Public
backend/folder ki sab files upload karo
- Space Settings โ Secrets mein add karo:
TMDB_API_KEY = f2c65dbd4b13d7dda8b7bb8ae95448b4- Space automatically build ho jaayega
- URL milegi:
https://YOUR-USERNAME-movie-recommender.hf.space
Step 2: Frontend โ GitHub Pages
- GitHub pe new repo banao:
movie-recommender-frontend
frontend/folder ki sab files upload karo
app.jsmein line 4 update karo:
const API_BASE = "https://YOUR-HF-USERNAME-movie-recommender.hf.space";- GitHub repo Settings โ Pages โ Branch:
mainโ Save
- URL milegi:
https://YOUR-GITHUB-USERNAME.github.io/movie-recommender-frontend
Project Structure
backend/
โโโ main.py โ FastAPI routes
โโโ recommender.py โ 3 ML strategies
โโโ sentiment.py โ Review sentiment
โโโ database.py โ SQLite
โโโ tmdb.py โ TMDB API helper
โโโ requirements.txt
โโโ Dockerfile
frontend/
โโโ index.html โ Home page
โโโ movie.html โ Movie detail + reviews + recommendations
โโโ style.css โ Cinematic dark gold design
โโโ app.js โ All frontend logicFeatures
- โ Live movie data + posters from TMDB
- โ 3 recommendation strategies with tab switcher
- โ Post-watch recommendations banner
- โ Star rating + text review system
- โ Automatic sentiment analysis (positive/negative/neutral)
- โ Sentiment visualization bars
- โ Movie search with live dropdown
- โ Genre filter chips
- โ Hero banner with auto-rotation
- โ Skeleton loading states
- โ Responsive design (mobile friendly)
- โ Watch history tracking
- โ Personalized recommendations per user
