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Dockerfile

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+# Use official lightweight Python image
+FROM python:3.9-slim
+
+# Set workdir
+WORKDIR /app
+
+# Copy project files
+COPY app.py .
+COPY superkart_sales_predictor.joblib .
+COPY requirements.txt .
+
+# Install dependencies
+RUN pip install -r requirements.txt
+
+# Expose Hugging Face default port
+EXPOSE 7860
+
+# Start Flask API
+CMD ["python", "app.py"]

app.py

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+from flask import Flask, request, jsonify
+import joblib
+import pandas as pd
+
+# Initialize Flask app
+app = Flask(__name__)
+
+# Load trained model (pipeline with preprocessing)
+model = joblib.load("superkart_sales_predictor.joblib")
+
+@app.route("/")
+def home():
+    return jsonify({"message": "SuperKart Sales Predictor API is running 🚀"})
+
+@app.route("/predict", methods=["POST"])
+def predict():
+    try:
+        # Input JSON
+        data = request.get_json()
+
+        # Convert to DataFrame
+        new_data = pd.DataFrame([data])
+
+        # Prediction
+        prediction = model.predict(new_data)[0]
+
+        return jsonify({"prediction": float(prediction)})
+
+    except Exception as e:
+        return jsonify({"error": str(e)})
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=7860)

requirements.txt

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+flask
+scikit-learn
+pandas
+joblib

superkart_sales_predictor.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d5cbe0c5430759b2c8d197c3a43b861296223a1a6d0c36386d2f7d1e834e66f8
+size 52440938