Upload 2 files

app.py

@@ -35,5 +35,7 @@ def recommend(user_id):
     ground_truth_items, recommendations = utils.predict(lightGCNModel, device, data, num_users, num_items, user_id, train_edge_label_index, k=5)
     return ground_truth_items, recommendations
 
+
+
 iface = gr.Interface(fn=recommend, inputs="number", outputs=["text", "text"])
 iface.launch()

utils.py

@@ -48,6 +48,7 @@ def predict(model, device, data, num_users, num_items, user_id, train_edge_label
         
         ground_truth_items = meta_dataframe[meta_dataframe['asin'].isin(ground_truth_asins)].head(5)
         
+        # print(f"Ground truth items: {ground_truth_items['title'].values.tolist()}")
         
         _, top_ratings = torch.topk(user_rates, k)
         
@@ -57,4 +58,4 @@ def predict(model, device, data, num_users, num_items, user_id, train_edge_label
             recommended_item = meta_dataframe[meta_dataframe['asin'] == asin_of_item]['title'].values
             recommended_items.append(recommended_item)
 
-        return ground_truth_items.values.tolist(), recommended_items
+        return ground_truth_items, recommended_items