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app.py

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+import streamlit as st
+import pandas as pd
+from fastai.tabular.all import load_learner
+import random
+import torch
+import joblib
+from sklearn.preprocessing import LabelEncoder
+import numpy as np
+
+# Set random seed for reproducibility
+random.seed(42)
+torch.manual_seed(42)
+
+# Load the saved model and LabelEncoder
+learn = load_learner('/home/venerable/Downloads/rohit/tabular_model1.pkl')  # Replace with your model path
+label_encoder = joblib.load('/home/venerable/Downloads/rohit/label_encoder.pkl')  # Replace with your encoder path
+
+# Function to make predictions
+def predict_location(input_data):
+    input_df = pd.DataFrame([input_data])
+    pred_class, pred_idx, outputs = learn.predict(input_df.iloc[0])
+    
+    # Apply softmax to get probabilities
+    probabilities = torch.nn.functional.softmax(torch.tensor(outputs), dim=0)
+    
+    # Get the index of the maximum probability
+    pred_idx = np.argmax(probabilities.numpy())
+    
+    # Convert the index to the corresponding location
+    location = label_encoder.inverse_transform([pred_idx])[0]
+    return location
+
+# Streamlit app
+def main():
+    st.title('Location Prediction App')
+
+    # Example input fields (replace with your actual input fields)
+    product_name = st.text_input('Product Name')
+    day_of_purchase = st.selectbox('Day of Purchase', ['Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday'])
+    product_price = st.number_input('Product Price (INR)')
+    avg_purchase_value = st.number_input('Average Purchase Value (INR)')
+
+    # Prepare input data for prediction
+    input_data = {
+        'Product Name': product_name,
+        'Day of Purchase': day_of_purchase,
+        'Product Price (INR)': product_price,
+        'Average Purchase Value (INR)': avg_purchase_value
+    }
+
+    # Predict button
+    if st.button('Predict Location'):
+        prediction = predict_location(input_data)
+        st.success(f'Predicted Location: {prediction}')
+
+if __name__ == '__main__':
+    main()

label_encoder.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3dd272a0c24c5806dedf8518cad756fe45edb00475086f874f47e1fc4c32969d
+size 2589

tabular_model1.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:90a3211bd59b025c182e4bd894027cbd3cbdf3672a856fc6889be7d9bfdbc9a2
+size 635546