Короче, ничего не получилось что хотел :(

Завтра сделаю фильтрованый датасет по городам, чтобы отдавать также инфу из городов

model.py

@@ -12,7 +12,7 @@ with open('neural_network/models/tokenization/tokenizer_lstm_lstm_negative.pickl
     tokenizer = pickle.load(handle)
 
 # Загрузка названий классов
-with open('neural_network/models/class/class_names_lstm_negative.txt', 'r', encoding='utf-8') as file:
+with open('neural_network/models/classification/class_names_lstm_negative.txt', 'r', encoding='utf-8') as file:
     class_names = [line.strip() for line in file.readlines()]
 
 def preprocess_text(text: str):

neural_network/classification/class_save.py

@@ -38,7 +38,7 @@ def process_dataset(dataset_path, label_column, output_path):
     dataset = label_processor.encode_labels()
     class_names = label_processor.get_class_names()
 
-    # Save class names
+    # Save classification names
     label_processor.save_class_names(class_names, output_path)
 
     return dataset

neural_network/dataset/conversion.py

@@ -1,3 +1,5 @@
+import sys
+
 import kaggle
 import zipfile
 import os
@@ -116,8 +118,8 @@ def main():
     # Сохранение результатов
     FileSaver.save_rubrics_to_file(unique_rubrics_positive, 'class/class_positive.txt')
     FileSaver.save_rubrics_to_file(unique_rubrics_negative, 'class/class_negative.txt')
-    FileSaver.save_dataset_to_csv(filtered_positive, '../dataset/filtered/filtered_dataset_positive.csv')
-    FileSaver.save_dataset_to_csv(filtered_negative, '../dataset/filtered/filtered_dataset_negative.csv')
+    FileSaver.save_dataset_to_csv(filtered_positive, 'filtered/filtered_dataset_positive.csv')
+    FileSaver.save_dataset_to_csv(filtered_negative, 'filtered/filtered_dataset_negative.csv')
 
 
 if __name__ == "__main__":

neural_network/models/create_model.py

@@ -206,7 +206,7 @@ class Plotter:
 def main():
 
     tokenizer_path_positive = '../tokenization/tokenizer_positive.pickle'
-    class_names_path_positive = '../class/class_names_positive.txt'
+    class_names_path_positive = '../classification/class_names_positive.txt'
     dataset_path_positive = '../dataset/filtered/filtered_dataset_positive.csv'
 
     model_save_path_lstm_positive = './model/best_model_lstm_positive.keras'
@@ -219,7 +219,7 @@ def main():
     plot_save_path_gru_positive = './graphics/history_gru_positive.png'
 
     tokenizer_path_negative = '../tokenization/tokenizer_negative.pickle'
-    class_names_path_negative = '../class/class_names_negative.txt'
+    class_names_path_negative = '../classification/class_names_negative.txt'
     dataset_path_negative = '../dataset/filtered/filtered_dataset_negative.csv'
 
     model_save_path_lstm_negative = './model/best_model_lstm_negative.keras'