Create app.py

app.py

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+import pandas as pd
+from gradio import Interface, Textbox, Dropdown
+
+# Load the prediction data for each algorithm and season
+als_spring_data = pd.read_csv('als_pred_spring.csv')
+als_fall_data = pd.read_csv('als_pred_fall.csv')
+als_winter_data = pd.read_csv('als_pred_winter.csv')
+als_summer_data = pd.read_csv('als_pred_summer.csv')
+
+nmf_spring_data = pd.read_csv('nmf_pred_spring.csv')
+nmf_fall_data = pd.read_csv('nmf_pred_fall.csv')
+nmf_winter_data = pd.read_csv('nmf_pred_winter.csv')
+nmf_summer_data = pd.read_csv('nmf_pred_summer.csv')
+
+# Function to get recommendations based on customer ID, season, and algorithm
+def get_recommendations(customer_id, season, algorithm):
+    if algorithm == 'ALS':
+        if season == 'Spring':
+            data = als_spring_data
+        elif season == 'Fall':
+            data = als_fall_data
+        elif season == 'Winter':
+            data = als_winter_data
+        elif season == 'Summer':
+            data = als_summer_data
+        else:
+            return 'Invalid season'
+    elif algorithm == 'NMF':
+        if season == 'Spring':
+            data = nmf_spring_data
+        elif season == 'Fall':
+            data = nmf_fall_data
+        elif season == 'Winter':
+            data = nmf_winter_data
+        elif season == 'Summer':
+            data = nmf_summer_data
+        else:
+            return 'Invalid season'
+    else:
+        return 'Invalid algorithm'
+    
+    if customer_id not in data['customer_id'].values:
+        return 'Recommendation not found'
+    
+    recommendations = data[data['customer_id'] == customer_id]['article_id'].iloc[0]
+    recommendations = recommendations.strip("[]").split(", ")
+    recommendations = [f"Item {i}: {item}" for i, item in enumerate(recommendations, 1)]
+    
+    return '\n'.join(recommendations)
+
+# Create the input and output interfaces
+customer_id_input = Textbox(label="Customer ID")
+season_input = Dropdown(choices=['Spring', 'Fall', 'Winter', 'Summer'], label="Season")
+algorithm_input = Dropdown(choices=['ALS', 'NMF'], label="Algorithm")
+output = Textbox(label="Recommendations")
+
+# Create the interface with the title
+title = "Collaborative Filtering for Recommendation System on Fashion Products"
+interface = Interface(fn=get_recommendations, inputs=[customer_id_input, season_input, algorithm_input], outputs=output, title=title)
+
+# Run the interface
+interface.launch()