Update gradio_interface.py

gradio_interface.py

@@ -29,17 +29,22 @@ def evaluate_text(input_text):
     doc = nlp(input_text)
     predicted_labels = doc.cats
     
-    # Construct output dictionary
+    # Construct output dictionary with likelihood for each label
     output_dict = {
         "PredictedLabels": {label: score for label, score in predicted_labels.items() if score > threshold}
     }
+    
+    # Add likelihood for each ground truth label
+    for label in ground_truth_labels:
+        if label not in output_dict["PredictedLabels"]:
+            output_dict["PredictedLabels"][label] = 0  # Set likelihood to 0 if label not present
+    
     return output_dict
 
 # Gradio Interface
 iface = gr.Interface(fn=evaluate_text, inputs="text", outputs="json", title="Text Evaluation-Manjinder", description="Enter your text")
 iface.launch(share=True)
 
-
 # import gradio as gr
 # import spacy
 # from sklearn.metrics import classification_report, accuracy_score, f1_score, precision_score, recall_score