Upload 4 files

Dockerfile

@@ -0,0 +1,15 @@
+FROM python:3.9-slim
+
+WORKDIR /app
+COPY . .
+
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    curl \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+RUN pip install --no-cache-dir -r requirements.txt
+
+EXPOSE 7860
+CMD ["gunicorn", "-w", "2", "-b", "0.0.0.0:7860", "app:superkart_api"]

app.py

@@ -0,0 +1,52 @@
+import pandas as pd
+import joblib
+from flask import Flask, request, jsonify
+import os # Import os for debugging
+
+superkart_api = Flask(__name__)
+
+print("--- APP STARTUP: Flask app instance created ---")
+
+# Load the trained model
+try:
+    print(f"--- APP STARTUP: Attempting to load model from {os.path.join(os.getcwd(), MODEL_FILENAME)} ---")
+    model = joblib.load("tuned_gradient_boosting_regressor_model.joblib")
+    print("--- APP STARTUP: Model loaded successfully ---")
+except Exception as e:
+    print(f"--- APP STARTUP: ERROR loading model: {e} ---")
+    raise # Re-raise to crash early if model loading fails
+
+print("--- APP STARTUP: Model variable assigned ---")
+
+@superkart_api.get('/')
+def home():
+    print("--- REQUEST: Home endpoint accessed ---")
+    return "Welcome to the Superkart Sales Prediction API!"
+
+@superkart_api.post('/v1/predict')
+def predict_sales():
+    print("--- REQUEST: Predict endpoint accessed ---")
+    data = request.get_json()
+    # ... (rest of your predict_sales logic) ...
+    sample = {
+        'Product_Weight': data['Product_Weight'],
+        'Product_Sugar_Content': data['Product_Sugar_Content'],
+        'Product_Allocated_Area': data['Product_Allocated_Area'],
+        'Product_MRP': data['Product_MRP'],
+        'Store_Size': data['Store_Size'],
+        'Store_Location_City_Type': data['Store_Location_City_Type'],
+        'Store_Type': data['Store_Type'],
+        'Product_Id_char': data['Product_Id_char'],
+        'Store_Age_Years': data['Store_Age_Years'],
+        'Product_Type_Category': data['Product_Type_Category']
+    }
+    input_df = pd.DataFrame([sample])
+    prediction = model.predict(input_df).tolist()[0]
+    print(f"--- REQUEST: Prediction made: {prediction} ---")
+    return jsonify({'Sales': prediction})
+
+if __name__ == '__main__':
+    print("--- APP STARTUP: Running in __main__ block ---")
+    # import os # Redundant import removed
+    port = int(os.environ.get("PORT", 7860))
+    superkart_api.run(host="0.0.0.0", port=port)

requirements.txt

@@ -0,0 +1,7 @@
+pandas==2.2.2
+numpy==2.0.2
+scikit-learn==1.6.1
+xgboost==2.1.4
+joblib==1.4.2
+flask==3.0.3  # <-- CHANGED TO 3.0.3
+gunicorn==20.1.0

tuned_gradient_boosting_regressor_model.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:42fa408c73255e88dad17d07e822e9d9896c8dae68ba8786af1d9eced3abcce7
+size 196171