Update app.py

app.py

@@ -8,6 +8,7 @@ from transformers import (
     AutoModelForSequenceClassification,
     pipeline
 )
+from transformers import MarianMTModel, MarianTokenizer
 
 # ────────────────────── konfiguracja ──────────────────────
 device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -22,8 +23,14 @@ sentiment_model = AutoModelForSequenceClassification.from_pretrained("absa-rober
 sentiment_model.eval()
 
 # Tłumaczenia
-pl_to_en = pipeline("translation", model="Helsinki-NLP/opus-mt-pl-en", device=0 if torch.cuda.is_available() else -1)
-en_to_pl = pipeline("translation", model="gsarti/opus-mt-tc-en-pl", device=0 if torch.cuda.is_available() else -1)
+
+pl_to_en_tokenizer = MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-pl-en")
+pl_to_en_model = MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-pl-en").to(device)
+pl_to_en = pipeline("translation", model=pl_to_en_model, tokenizer=pl_to_en_tokenizer, device=0 if torch.cuda.is_available() else -1)
+
+en_to_pl_tokenizer = MarianTokenizer.from_pretrained("gsarti/opus-mt-tc-en-pl")
+en_to_pl_model = MarianMTModel.from_pretrained("gsarti/opus-mt-tc-en-pl").to(device)
+en_to_pl = pipeline("translation", model=en_to_pl_model, tokenizer=en_to_pl_tokenizer, device=0 if torch.cuda.is_available() else -1)
 
 # Alias słownik
 aspect_aliases = {