Update app.py

app.py

@@ -166,16 +166,15 @@ def predict_icd(text_input, model_name, label_count):
     label_dict = label_dict_df.set_index('icd9_code')['long_title'].to_dict()
     predicted_labels_float = [float(label) for label in predicted_labels]
     predicted_labels_with_titles = [(label, label_dict.get(str(label), "Not Found")) for label in predicted_labels_float]
-    print("Types of keys in label_probabilities:")
-    for key in label_probabilities.keys():
-        print(type(key))
-    # print("Keys in label_probabilities:", label_probabilities.keys())
-
 
     html_output ="<h2>ICD Codes</h2>"
+    # for label, title in predicted_labels_with_titles:
+    #     color = hash_to_color(str(label))
+    #     html_output += f"<div style='background-color: {color}; padding: 5px; margin-bottom: 5px;'>{label} - {title} <span style='float:right;'>{label_probabilities[label]:.2f}%</span></div>"
     for label, title in predicted_labels_with_titles:
-        color = hash_to_color(str(label))
-        html_output += f"<div style='background-color: {color}; padding: 5px; margin-bottom: 5px;'>{label} - {title} <span style='float:right;'>{label_probabilities[label]:.2f}%</span></div>"
+        label = str(label)
+        color = hash_to_color(label)
+        html_output += f"<div style='background-color: {color}; padding: 5px; margin-bottom: 5px;'>{label} - {title} <span style='float:right;'>{label_probabilities.get(label, 0):.2f}%</span></div>"