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title: E Commerce | |
emoji: 💬 | |
colorFrom: yellow | |
colorTo: purple | |
sdk: gradio | |
sdk_version: 5.0.1 | |
app_file: app.py | |
pinned: false | |
license: apache-2.0 | |
short_description: Testing for e-commerce | |
An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.25.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index). | |
# README.md | |
# Product Recommender | |
A machine learning-powered product recommendation system that uses semantic search to find similar products based on user queries. | |
## Features | |
- Semantic search using sentence transformers | |
- FastAPI backend for quick recommendations | |
- BigQuery integration for training data | |
- HuggingFace model hosting | |
- Docker support for easy deployment | |
## Setup | |
1. Install dependencies: | |
```bash | |
pip install -e . | |
``` | |
2. Copy and configure environment variables: | |
```bash | |
cp backend/.env.example backend/.env | |
# Edit .env with your credentials | |
``` | |
3. Train the model: | |
```bash | |
python -m backend.train | |
``` | |
4. Start the API: | |
```bash | |
python -m backend.server | |
``` | |
## API Documentation | |
Once running, visit http://localhost:8000/docs for the OpenAPI documentation. | |
## Docker Usage | |
```bash | |
cd backend | |
docker-compose up --build | |
``` | |
## License | |
MIT License - See LICENSE file for details | |