...

tabs/sentence_similarity_tab.py

@@ -371,6 +371,8 @@ def run():
         st.write("")
         proximite()
     '''
+    st.write("")
+    st.title(tr(title))
     sentences = ["This is an example sentence", "Each sentence is converted"]
     sentences[0] = st.text_area(label=tr("Saisir le texte le texte de reference"), value="This is an example sentence")
     sentences[1] = st.text_area(label=tr("Saisir le texte à comparer"), value="Each sentence is converted")

tabs/text2speech_tab.py

@@ -321,7 +321,7 @@ def display_preprocess_results(lang, data, data_split, data_lem, data_wosw, txt_
             st.write("\n**"+tr("Mots uniques sans stop words")+":**")
             st.markdown(mots_wo_sw[:500])
 
-
+'''
 def run():
     global max_lines, first_line, last_line, lemmatize_to_do, stopwords_to_do
     global full_txt_en, full_txt_split_en, full_txt_lem_en, full_txt_wo_stopword_en, full_df_count_word_en
@@ -329,7 +329,7 @@ def run():
     
     st.write("")
     st.title(tr(title))
-    
+    '''
     st.write("## **"+tr("Explications")+" :**\n")
     st.markdown(tr(
         """
@@ -411,7 +411,7 @@ def run():
             if st.session_state.reCalcule:
                 txt_fr, corpus_fr, txt_split_fr, txt_lem_fr, txt_wo_stopword_fr, df_count_word_fr,sent_len_fr, sent_wo_sw_len_fr, sent_lem_len_fr  = preprocess_txt (txt_fr,'fr')
             display_preprocess_results('fr', txt_fr, txt_split_fr, txt_lem_fr, txt_wo_stopword_fr, df_count_word_fr)
-'''
+    '''