Update gradio_interface.py

gradio_interface.py

@@ -58,33 +58,5 @@ def evaluate_text(input_text):
     
     return output_dict
 
-    # Convert predicted and ground truth labels to lists
-    predicted_labels_list = [1 if predicted_labels[label] else 0 for label in predicted_labels]
-    ground_truth_labels_list = [ground_truth_labels[label] for label in predicted_labels]
-
-    # Calculate evaluation metrics
-    accuracy = accuracy_score(ground_truth_labels_list, predicted_labels_list)
-    precision = precision_score(ground_truth_labels_list, predicted_labels_list, average='weighted')
-    recall = recall_score(ground_truth_labels_list, predicted_labels_list, average='weighted')
-    f1 = f1_score(ground_truth_labels_list, predicted_labels_list, average='weighted')
-
-    # Additional classification report
-    report = classification_report(ground_truth_labels_list, predicted_labels_list)
-
-    # Construct output dictionary
-    output_dict = {
-        "PredictedLabels": predicted_labels,
-        "EvaluationMetrics": {
-            "Accuracy": accuracy,
-            "Precision": precision,
-            "Recall": recall,
-            "F1-Score": f1,
-            "ClassificationReport": report
-        }
-    }
-    
-    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)
+iface = gr.Interface(fn=evaluate_text, inputs="text", outputs