Add deployment files

Dockerfile

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+# Use a lightweight Python base image
+FROM python:3.11-slim
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY app.py .
+COPY best_sales_forecast_model.pkl .
+
+EXPOSE 5000
+CMD ["python", "app.py"]

app.py

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+from flask import Flask, request, jsonify
+import pandas as pd
+import joblib
+
+app = Flask(__name__)
+
+MODEL_PATH = "best_sales_forecast_model.pkl"
+model = joblib.load(MODEL_PATH)
+
+FEATURE_COLUMNS = [
+    "Product_Weight","Product_Allocated_Area","Product_MRP",
+    "Store_Establishment_Year","Store_Size","Store_Location_City_Type",
+    "Store_Type","Product_Prefix","Product_Num","Store_Age"
+]
+
+@app.route("/")
+def home():
+    return "SuperKart Sales Forecast API is up."
+
+@app.route("/predict", methods=["POST"])
+def predict():
+    payload = request.get_json(force=True)
+    df = pd.DataFrame(payload["data"])
+    X = df[FEATURE_COLUMNS]
+    preds = model.predict(X)
+    return jsonify({"predictions": preds.tolist()})
+
+if __name__ == "__main__":
+    import os
+    port = int(os.environ.get("PORT", 5000))
+    app.run(host="0.0.0.0", port=port)

best_sales_forecast_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6f13226779001590e025ef62b31e40021305709d38a5ab555e18bc1611208c97
+size 49997859

requirements.txt

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+flask==2.2.5
+pandas==2.1.1
+scikit-learn==1.4.0
+joblib==1.3.2