metadata

title: Personalized Movie Recommender Assistant
emoji: 🎬
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.33.1
app_file: app.py
pinned: false
license: apache-2.0
short_description: Your Al Movie Buddy tailored to your watching habits
tags:
  - agent-demo-track

🎬 Personalized Movie Recommender

A chatbot-style movie recommendation system built for the 🤖 Gradio Agents & MCP Hackathon 2025 🚀.

This project leverages the powerful Google gemma-2b-it model (quantized to 4-bit for speed and efficiency), FastAPI for serving, and Gradio for an engaging interactive UI.

🚀 Features

✅ Personalized Movie Recommendations

Understands user’s mood and genre preferences to deliver tailored suggestions.
Fully customizable: choose the agent’s personality, expertise level, and response language.

✅ Gemma-2B-It Integration

Efficient 4-bit quantized loading using bitsandbytes.
Runs on H100 GPUs for blazing-fast inference.

✅ Multilingual Support

Supports English, Korean, and Japanese.

🏗️ Architecture

Backend: FastAPI app deployed on Modal with GPU acceleration.
Model: Google’s gemma-2b-it with 4-bit quantization.
Frontend: Gradio chatbot UI for a natural conversation experience.
Infrastructure: Modal’s NetworkFileSystem for model caching and deployment.

🔧 How to Use

Modal Deployment

Set up secrets: Store your modal-key secret.
Deploy:
```
modal deploy
```

Local Development 1. Install dependencies:

pip install torch transformers accelerate einops huggingface_hub bitsandbytes fastapi gradio requests

2.	Run locally:

python app.py

⸻

🪄 Live Demo

A video overview of the app in action: 👉 Watch here! (replace with your video recording link)

⸻

🏷️ Hackathon Track

This project participates in the Agentic Demo Showcase.

⸻

🧑‍💻 Team • Jadob ⸻

📜 License

This project is licensed under the MIT License.

⸻

🌟 Acknowledgments • Thanks to the 🤖 Gradio Agents & MCP Hackathon 2025 🚀 team and sponsors for organizing this event. • Huge shoutout to Hugging Face, Modal, and all the contributors to open-source tools powering this project.

⸻

💡 This project was built from scratch during the Hackathon week, following all official rules and submission guidelines.