Update utils/target_classifier.py

utils/target_classifier.py

@@ -37,7 +37,7 @@ def get_target_labels(preds):
         index_of_one = ele.index(1)
       except ValueError:
         index_of_one = "NA"
-      st.write(index_of_one)
+      
       # Retrieve the name of the label (if no prediction made = NA)
       if index_of_one != "NA":
         name  = label_dict[index_of_one]
@@ -107,42 +107,19 @@ def target_classification(haystack_doc:pd.DataFrame,
     logging.info("Working on target/action identification")
                             
     haystack_doc['Target Label'] = 'NA'
-    st.write("haystack_doc")
-    st.write(haystack_doc)
-                            
+                                
     if not classifier_model:
 
-        st.write("No classifier_model")
-
         classifier_model = st.session_state['target_classifier']
-        st.write("classifier model defined")
         
         # Get predictions
         predictions = classifier_model(list(haystack_doc.text))
-        st.write("predictions made")
-        st.write(predictions)
+      
         # Get labels for predictions
         pred_labels = get_target_labels(predictions)
-        st.write("pred_labels")
-        st.write(pred_labels)
+     
         # Save labels
         haystack_doc['Target Label'] = pred_labels
 
         return haystack_doc            
-    # logging.info("Working on action/target extraction")
-    # if not classifier_model:
-#     #     classifier_model = st.session_state['target_classifier']
-    
-#     # results = classifier_model(list(haystack_doc.text))
-#     # labels_= [(l[0]['label'],
-#     #            l[0]['score']) for l in results]
-           
-
-#     # df1 = DataFrame(labels_, columns=["Target Label","Target Score"])
-#     # df = pd.concat([haystack_doc,df1],axis=1)
-    
-#     # df = df.sort_values(by="Target Score", ascending=False).reset_index(drop=True)
-#     # df['Target Score'] = df['Target Score'].round(2)
-#     # df.index += 1
-#     # # df['Label_def'] = df['Target Label'].apply(lambda i: _lab_dict[i])