Update app.py

app.py

@@ -207,6 +207,8 @@ form_explainer.header("Explainer Settings")
 position_dep = form_explainer.checkbox("Check this if you want to take into account the position of a word in the interpretation", value = False)
 number_samples = form_explainer.number_input("Enter the number of explainer peterbuted samples, higher creates a better explanation but takes longer - you should most likely increase this", value = 200)
 char_based = form_explainer.checkbox("Check this if you want to use a character based explanier", value = False)
+top_features = form_explainer.number_input("Enter the top number of features we want to show", value = 200)
+top_targets = form_explainer.number_input("Enter the top number of targets we want to show explanations of", value = 5)
 form_explainer.form_submit_button("Submit")
 
 
@@ -254,9 +256,9 @@ if task == "Classification":
     target_feature_names = text_clf['clf'].classes_
     #target_feature_names = pd.unique(df[labels_column_name])
     target_feature_names_list = list(target_feature_names)
-    t_pred = te.explain_prediction(target_names = target_feature_names_list)
+    t_pred = te.explain_prediction(target_names = target_feature_names_list, top = top_features, top_targets = top_targets)
 else:
-    t_pred = te.explain_prediction()
+    t_pred = te.explain_prediction(top = top_features, top_targets = top_targets)
 html = format_as_html(t_pred)
 
 form_html = st.sidebar.form("html_size_form")