Upload 5 files

Dockerfile.dockerfile

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+FROM python:3.10-slim
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+EXPOSE 7860
+
+CMD ["streamlit", "run", "app.py", "--server.port=7860", "--server.address=0.0.0.0"]

app.py

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+%%writefile backend_files/app.py
+# app.py
+import numpy as np
+from flask import Flask, request, jsonify
+import joblib
+import pandas as pd
+
+# Inititialize Flask app with name
+sales_prediction_api = Flask("Sales Predictor")
+
+# Load the trained model predictor model
+dt_model = joblib.load("decision_tree_model.pkl")
+
+# Define a route for the home page
+@sales_prediction_api.route('/')
+def home():
+    return "Sales Prediction API"
+
+# Define an endpoint to predict sales
+@sales_prediction_api.post('/predict')
+def predict():
+    # Get the data from the request
+    data = request.get_json()
+
+    # Extract relevant features from the input data
+    sample = {
+        'product_weight' = data['product_weight']
+        'product_sugar_content' = data['product_sugar_content']
+        'Product_Allocated_Area	' = data['Product_Allocated_Area']
+        'Product_Type' = data['Product_Type]
+        'Product_MRP' = data['Product_MRP']
+        'Store_Size' = data['Store_Size]
+        'Store_Location_City_Type' = data['Store_Location_City_Type']
+        'Store_Type' = data['Store_Type']
+        'Store_Age' = data['Store_Age']
+    }
+
+    #convert the extracted data into a dataframe
+    sample_df = pd.DataFrame(sample, index=[0])
+
+    #make a sales prediction using the model
+    prediction = dt_model.predict(sample_df).tolist()[0]
+
+    #return the prediction as a JSON response
+    return jsonify({'prediction': prediction})
+
+if __name__ == '__main__':
+    app.run(debug=True)

decision_tree_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ea3b7c00e81dc02cf0ab4af6c4714fe8f799da15d9be8158e77c612d096c6663
+size 41201

requirements.txt

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+streamlit
+flask
+pandas
+numpy
+scikit-learn
+xgboost
+joblib

xgboost_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:eb60b8f8584a03d8f18c14d36e93b36a5c4d75d993630ebcab0b875dd2b9ae15
+size 1938822