README.md

metadata

title: SuperKart Backend API
emoji: ⚙️
colorFrom: blue
colorTo: purple
sdk: docker
app_file: api.py
pinned: false

SuperKart Backend

This is the Flask backend that serves trained models for sales forecasting.

SuperKart Backend (Flask API)

Endpoints:

• GET /health -> health check
• POST /predict -> JSON with store_id and features or features_list
• POST /predict_batch -> multipart CSV with store_id column

Run locally

pip install -r requirements.txt
export PORT=7860
python api.py
# or gunicorn
gunicorn -b 0.0.0.0:$PORT api:app --workers 2 --threads 8 --timeout 180

Deploy to Hugging Face Spaces (Docker)

1. Create a new Space → Docker → name: superkart-backend.
2. Upload files in this folder (including Dockerfile).
3. Add your trained models/ directory:

   models/
     store_101/
       RandomForest.joblib
       metadata.json
     store_102/
       XGBoost.joblib
       metadata.json
   

4. The Space will build and expose the API at: https://Sales-prediction-sudhirpgcmma02.hf.space