Update app.py

app.py

@@ -212,7 +212,7 @@ form_explainer.form_submit_button("Submit")
 
 te = TextExplainer(random_state=42, char_based=char_based, n_samples = number_samples, position_dependent=position_dep)
 
-@st.cache(allow_output_mutation=True)
+@st.cache(allow_output_mutation=True) ##Seems to break shit :( 
 def fit_text_explainer(X, predict_proba):
     te.fit(X, predict_proba)
     return te
@@ -220,8 +220,8 @@ def fit_text_explainer(X, predict_proba):
 input_choice = st.checkbox("Check this if you want to enter your own example to explain", value = False)
 if input_choice == False:
     record_to_explain = st.number_input("Enter the index of the document from the original dataset to interpret", value = 30)
-    #te.fit(df[column_name][record_to_explain], text_clf.predict_proba)
-    te = fit_text_explainer(df[column_name][record_to_explain], text_clf.predict_proba)
+    te.fit(df[column_name][record_to_explain], text_clf.predict_proba)
+    #te = fit_text_explainer(df[column_name][record_to_explain], text_clf.predict_proba)
     if task == "Classification":
         st.write("Ground truth label")
         st.write(df[labels_column_name][record_to_explain])
@@ -236,8 +236,8 @@ if input_choice == False:
         st.write(model_prediction)
 else:
     record_to_explain = st.text_area("Enter the example document to explain", value = text_example)
-    #te.fit(record_to_explain, text_clf.predict_proba)
-    te = fit_text_explainer(record_to_explain, text_clf.predict_proba)
+    te.fit(record_to_explain, text_clf.predict_proba)
+    #te = fit_text_explainer(record_to_explain, text_clf.predict_proba)
     if task == "Classification":
         st.write("Model prediction")
         model_prediction = text_clf.predict([record_to_explain])