title: Shoppy AI emoji: 🛒 colorFrom: blue colorTo: purple sdk: gradio sdk_version: "5.34.2" app_file: app.py

pinned: false

Shoppy AI 🛒

An AI-powered e-commerce assistant built with Gradio and modern NLP techniques.

🔗 Live Demo

👉 https://huggingface.co/spaces/santhosh11042007/shoppyai

Overview

Shoppy AI helps users discover, compare, and understand products using natural language queries. It is designed as a lightweight AI assistant that can later scale into a full RAG-based recommendation system.

Core Capabilities

• Natural language product search
  
• Intelligent product suggestions
  
• Context-aware responses
  
• Extensible backend for RAG pipelines
  
• Ready for vector database integration
  

System Architecture

• UI Layer: Gradio interface (app.py)
• Logic Layer: Python backend processing
• AI Layer: LLM API or local transformer models
• Data Layer (optional): SQLite / FAISS / ChromaDB

Execution Flow

1. User submits query in UI
   
2. Request is handled by app.py
   
3. Prompt optionally enriched (RAG-ready design)
   
4. LLM generates response
   
5. Output rendered in Gradio UI
   

Future Upgrades

• Add vector database (FAISS / ChromaDB)
• Implement full RAG pipeline
• Add async inference layer
• Introduce caching for repeated queries
• Deploy with Docker-based HF Space

Tech Stack

• Python
  
• Gradio
  
• Transformers / LLM APIs
  
• Hugging Face Spaces
  

Engineering Insight

This project is intentionally structured to evolve from:

simple LLM wrapper → production-grade AI retrieval system

Key learning areas:

• prompt orchestration
• API-based inference design
• scalable AI system architecture
• modular backend design for AI apps

Built With

• dockerfile
• python