| title | Shoppy AI |
|---|---|
| emoji | 🛒 |
| colorFrom | blue |
| colorTo | purple |
| sdk | gradio |
| sdk_version | 5.34.2 |
| app_file | app.py |
| pinned | false |
An AI-powered e-commerce assistant built with Gradio and modern NLP techniques.
👉 https://huggingface.co/spaces/santhosh11042007/shoppyai
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.
- Natural language product search
- Intelligent product suggestions
- Context-aware responses
- Extensible backend for RAG pipelines
- Ready for vector database integration
- 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
- User submits query in UI
- Request is handled by
app.py - Prompt optionally enriched (RAG-ready design)
- LLM generates response
- Output rendered in Gradio UI
- Add vector database (FAISS / ChromaDB)
- Implement full RAG pipeline
- Add async inference layer
- Introduce caching for repeated queries
- Deploy with Docker-based HF Space
- Python
- Gradio
- Transformers / LLM APIs
- Hugging Face Spaces
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