Update func_ai.py

func_ai.py

@@ -1,17 +1,18 @@
 import requests
 import torch
+# from googletrans import Translator
 from transformers import pipeline
 from deep_translator import GoogleTranslator
 import time
 import os 
-
 VECTOR_API_URL = os.getenv('API_URL')
 
-# Initialize the sentiment analysis model with distilbert
+# translator = Translator()
+
 sentiment_model = pipeline(
     'sentiment-analysis',
-    model='distilbert/distilbert-base-uncased-finetuned-sst-2-english',
-    tokenizer='distilbert/distilbert-base-uncased-finetuned-sst-2-english',
+    model='cardiffnlp/twitter-xlm-roberta-base-sentiment',
+    tokenizer='cardiffnlp/twitter-xlm-roberta-base-sentiment',
     device=0 if torch.cuda.is_available() else -1
 )
 
@@ -64,23 +65,9 @@ def analyze_sentiment(comments):
     for i in range(0, len(comments), 50):
         batch = comments[i:i + 50]
         print(f"Анализируем батч с {i} по {i + len(batch)} комментарий: {batch}")
-
-        # Translate each comment in the batch
-        try:
-            translated_batch = [GoogleTranslator(source='auto', target='en').translate(comment) for comment in batch]
-            print(f"Translated batch: {translated_batch}")
-        except Exception as e:
-            print(f"Translation failed: {e}")
-            continue
-
-        # Analyze sentiment on the translated batch
-        try:
-            batch_results = sentiment_model(translated_batch)
-            print(f"Результаты батча: {batch_results}")
-            results.extend(batch_results)
-        except Exception as e:
-            print(f"Sentiment analysis failed: {e}")
-
+        batch_results = sentiment_model(batch)
+        print(f"Результаты батча: {batch_results}")
+        results.extend(batch_results)
         time.sleep(1)  # Задержка для предотвращения перегрузки
-    print(f"Анализ настроений завершен. Общие результаты: {results}")
-    return results
+    print("Анализ настроений завершен. Общие результаты: {results}")
+    return results