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Dockerfile

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+FROM python:3.9-slim
+
+# Set the working directory inside the container
+WORKDIR /app
+
+# Copy all files from the current directory to the container's working directory
+COPY . .
+
+# Install dependencies from the requirements file without using cache to reduce image size
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+# Define the command to start the application using Gunicorn with 4 worker processes
+# - `-w 4`: Uses 4 worker processes for handling requests
+# - `-b 0.0.0.0:7860`: Binds the server to port 7860 on all network interfaces
+# - `app:superkart_api`: Runs the Flask app (Flask app instance is named `superkart_api` inside app.py)
+CMD ["gunicorn", "-w", "4", "-b", "0.0.0.0:7860", "app:app"]

app.py

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+
+import os
+import numpy as np
+import pandas as pd
+import joblib
+from flask import Flask, request, jsonify
+from flask_cors import CORS
+
+# ------------------------------------------------------------
+# Flask Application Setup
+# ------------------------------------------------------------
+def create_app(model_path: str):
+    """
+    Factory function to create and configure the Flask app.
+    """
+    app = Flask("superkart_api")
+    CORS(app)
+
+    # Load model once during startup
+    if not os.path.exists(model_path):
+        raise FileNotFoundError(f"Trained model not found at {model_path}")
+
+    model = joblib.load(model_path)
+
+    # --------------------------------------------------------
+    # Health check route
+    # --------------------------------------------------------
+    @app.route("/", methods=["GET"])
+    def health_check():
+        """
+        Returns a simple message to verify the API is running.
+        """
+        return jsonify({"status": "ok", "message": "SuperKart Sales Prediction API is active"})
+
+    # --------------------------------------------------------
+    # Prediction endpoint
+    # --------------------------------------------------------
+    @app.route("/api/v1/predict", methods=["POST"])
+    def predict():
+        """
+        Accepts JSON input, validates fields, runs the model, and returns predictions.
+        """
+        data = request.get_json()
+
+        if not data:
+            return jsonify({"error": "No input received"}), 400
+
+        expected_fields = [
+            "Product_Weight",
+            "Product_Sugar_Content",
+            "Product_Allocated_Area",
+            "Product_MRP",
+            "Store_Size",
+            "Store_Location_City_Type",
+            "Store_Type",
+            "Store_Age_Years",
+            "Product_Type_Category"
+        ]
+
+        missing = [f for f in expected_fields if f not in data]
+        if missing:
+            return jsonify({"error": f"Missing required fields: {missing}"}), 400
+
+        try:
+            # Preprocess input data into model format
+            processed = pd.DataFrame([{
+                "Product_Weight": float(data["Product_Weight"]),
+                "Product_Sugar_Content": data["Product_Sugar_Content"],
+                "Product_Allocated_Area_Log": np.log1p(float(data["Product_Allocated_Area"])),
+                "Product_MRP": float(data["Product_MRP"]),
+                "Store_Size": data["Store_Size"],
+                "Store_Location_City_Type": data["Store_Location_City_Type"],
+                "Store_Type": data["Store_Type"],
+                "Store_Age_Years": int(data["Store_Age_Years"]),
+                "Product_Type_Category": data["Product_Type_Category"]
+            }])
+
+            prediction = model.predict(processed)[0]
+
+            return jsonify({
+                "Predicted_Sales": round(float(prediction), 2),
+                "status": "success"
+            })
+
+        except Exception as exc:
+            return jsonify({"error": f"Prediction failed: {str(exc)}"}), 500
+
+    return app
+
+MODEL_PATH = "/content/drive/My Drive/Colab Notebooks/superKart/superkart_product_sales_forecasting_model_v1_0.joblib"
+app = create_app(saved_model_path)

requirements.txt

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+pandas==2.2.2
+numpy==2.0.2
+scikit-learn==1.6.1
+flask-cors==3.0.10
+joblib==1.4.2
+Werkzeug==2.2.2
+flask==2.2.2
+gunicorn==20.1.0
+requests==2.28.1
+uvicorn[standard]
+streamlit==1.43.2