Fix bugs

utilities_language_bert/rus_sentence_bert.py

@@ -236,6 +236,6 @@ class TASK:
             distractors = sample(self.inflected_distractors, len_variants) + [self.original_text, ]
         except ValueError:
             distractors = self.inflected_distractors + [self.original_text, ]
-        tmp_vars = [f'{item[0]} {item[1].replace("_", " ")}'.lower()
+        tmp_vars = [f'{item[0]} {item[1].replace("_", " ").lower()}'.lower()
                     for item in zip(letters, sorted(distractors, key=lambda _: random()))]
         self.variants.append((self.original_text.lower(), tmp_vars))

utilities_language_general/rus_constants.py

@@ -5,21 +5,25 @@ import pymorphy2
 import streamlit as st
 from transformers import pipeline
 
+
 @st.cache_resource
 def load_morph():
     _morph = pymorphy2.MorphAnalyzer(lang='ru')
     return _morph
 
+
 @st.cache_resource
 def load_w2v(model_path):
     _w2v_model = gensim.models.KeyedVectors.load_word2vec_format(model_path, binary=True)
     return _w2v_model
 
-@st.cache_resource    
+
+@st.cache_resource
 def load_spacy():
     _nlp = spacy.load('ru_core_news_lg')
     return _nlp
 
+
 @st.cache_resource
 def load_bert():
     return pipeline("fill-mask", model="a-v-white/ruBert-base-finetuned-russian-moshkov-child-corpus-pro")

utilities_language_general/rus_utils.py

@@ -318,8 +318,8 @@ def prepare_tasks(input_variants):
     for num, item in enumerate(input_variants):
         item = item[0]
         answer = item[0].lower()
-        variants = '\t'.join(item[1])
-        current_answer_letter = answer_letter(answer=answer, variants=item[1])
+        variants = '\t'.join([i.lower() for i in item[1]])
+        current_answer_letter = answer_letter(answer=answer, variants=[i.lower() for i in item[1]])
         RAW_TASKS.append((num + 1, variants))
         RAW_KEYS_ONLY.append((num + 1, current_answer_letter.split(' ')[0]))
         RESULT_TASKS_STUDENT.append(f"{num + 1}.\t{variants}")