Upload README.md with huggingface_hub

README.md

@@ -1,64 +1,65 @@
 ---
-title: SuperKart Sales Forecasting API
-emoji: 🛋️
+title: SuperKart Sales Forecasting UI
+emoji: 🛒
 colorFrom: blue
 colorTo: green
-sdk: docker
-app_port: 8080
+sdk: streamlit
+sdk_version: 1.28.1
+app_file: app.py
 pinned: false
+license: mit
 ---
 
-# SuperKart Sales Forecasting API
-
-## Overview
-Production-ready Flask API for predicting SuperKart sales using machine learning.
-
-## Features
-- Single prediction endpoint
-- Batch prediction support
-- Input validation and error handling
-- Health monitoring
-- Model information endpoint
-- CORS support
-- Production-ready configuration
-
-## Endpoints
-- `GET /` - API information
-- `GET /health` - Health check
-- `GET /model_info` - Model details
-- `POST /predict` - Single prediction
-- `POST /batch_predict` - Batch predictions
-
-## Local Development
-```bash
-pip install -r requirements.txt
-python app.py
-```
-
-## Docker Deployment
-```bash
-docker build -t superkart-api .
-docker run -p 8080:8080 superkart-api
-```
-
-## Sample Request
-```json
-{
-    "Product_Weight": 10.5,
-    "Product_Sugar_Content": "Low Sugar",
-    "Product_Allocated_Area": 0.15,
-    "Product_Type": "Fruits and Vegetables",
-    "Product_MRP": 150.0,
-    "Store_Size": "Medium",
-    "Store_Location_City_Type": "Tier 2",
-    "Store_Type": "Supermarket Type2",
-    "Store_Age": 15
-}
-```
-
-## Model Information
-- Model: Random Forest (Tuned)
-- Accuracy: High precision sales forecasting
-- Input Features: 9 core features + engineered features
-- Output: Predicted sales value
+# 🛒 SuperKart Sales Forecasting System
 
+An intelligent sales forecasting system powered by machine learning that helps SuperKart optimize inventory management and make data-driven business decisions.
+
+## 🚀 Features
+
+- **📊 Interactive Predictions**: Single and batch sales forecasting
+- **📈 Real-time Analytics**: Live dashboard with business insights
+- **🔄 API Integration**: Seamless connection to ML backend
+- **📱 User-friendly Interface**: Intuitive design for business users
+- **📋 Batch Processing**: Upload CSV files for bulk predictions
+
+## 🎯 Quick Start
+
+1. **Configure API URL**: Set your backend API endpoint in the app
+2. **Single Prediction**: Enter product and store details for instant forecasting
+3. **Batch Processing**: Upload CSV file for multiple predictions
+4. **View Analytics**: Explore interactive charts and insights
+
+## 🔧 Configuration
+
+### Backend API Connection
+- Navigate to "API Status" in the sidebar
+- Enter your backend API URL (e.g., `https://your-backend-api.hf.space`)
+- Test the connection to ensure it's working
+
+### Input Format
+Required fields for predictions:
+- Product Weight, Sugar Content, Allocated Area, Type, MRP
+- Store Size, Location City Type, Store Type, Age
+
+## 📊 Business Intelligence
+
+The system provides actionable insights including:
+- Sales performance analysis by product categories
+- Store performance comparisons
+- Regional sales patterns
+- Inventory optimization recommendations
+
+## 🛠️ Technical Details
+
+- **Framework**: Streamlit
+- **ML Backend**: Flask API with scikit-learn
+- **Deployment**: Hugging Face Spaces
+- **Container**: Docker-based deployment
+
+## 📞 Support
+
+For technical support or business consultation, contact the SuperKart ML Analytics Team.
+
+---
+
+**Transform your retail operations with AI-powered sales forecasting!** 🌟