chore: add raw predictions.

app.py

@@ -138,38 +138,6 @@ def clean_prediction(row, feature_name, threshols_dict, clean_functions_dict):
         return prediction_clean
     else:
         return None
-    
-def calculate_metrics(X, feature_name, data_type):
-    true_positives = 0
-    true_negatives = 0
-    false_positives = 0
-    false_negatives = 0
-    for pred, true in zip(X[f"clean_pred_{feature_name}"], X[f"clean_{feature_name}"]):
-        if isinstance(pred, data_type):
-            if isinstance(true, data_type):
-                if pred == true:
-                    true_positives += 1
-                else:
-                    false_positives += 1
-            else:
-                false_positives += 1
-        else:
-            if isinstance(true, data_type):
-                false_negatives += 1
-            else:
-                true_negatives += 1
-                
-    # Calculate Metrics   
-    precision = true_positives / (true_positives + false_positives) if (true_positives + false_positives) != 0 else np.nan
-    recall = true_positives / (true_positives + false_negatives) if (true_positives + false_negatives) != 0 else np.nan
-    f1_score = 2 * (precision * recall) / (precision + recall) if (precision + recall) != 0 else np.nan
-    metrics = {
-        "precision": precision,
-        "recall": recall,
-        "f1_score": f1_score,
-    }
-    
-    return metrics
 
 def extract_remodeling_year_from_string(string):
     if isinstance(string, str):
@@ -251,7 +219,7 @@ def generate_answer(text):
             
     result_json = json.dumps(entities_cleaned, indent = 4, ensure_ascii = False)
 
-    return result_json
+    return result_json + "\n \n" + entities_formatted
 
 # Cambiar a entrada de texto
 #text_input = gr.inputs.Textbox(lines=15, label="Input Text")