Update app.py

app.py

@@ -1,7 +1,6 @@
 import gradio as gr
 from transformers import MarianMTModel, MarianTokenizer
 import torch
-import re
 
 # Load the model and tokenizer from the Hub
 model_name = "Dddixyy/latin-italian-translatorV2"
@@ -10,24 +9,14 @@ model = MarianMTModel.from_pretrained(model_name)
 
 # Translation function
 def translate_latin_to_italian(latin_text):
-    # Split input text into sentences while preserving line breaks
-    sentences = re.split(r'(?<=[.!?]) +', latin_text.strip())
-    
-    translated_sentences = []
-    
-    for sentence in sentences:
-        # Make the first letter lowercase if the sentence is not empty
-        if sentence:
-            sentence = sentence[0].lower() + sentence[1:]
-        inputs = tokenizer(sentence, return_tensors="pt", padding=True, truncation=True)
-        with torch.no_grad():
-            generated_ids = model.generate(inputs["input_ids"])
-        translation = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
-        translated_sentences.append(translation[0])
-    
-    # Reassemble the translated sentences and keep original line breaks
-    translated_text = ' '.join(translated_sentences)
-    return translated_text
+    # Make the first letter lowercase if the input is not empty
+    if latin_text:
+        latin_text = latin_text[0].lower() + latin_text[1:]
+    inputs = tokenizer(latin_text, return_tensors="pt", padding=True, truncation=True)
+    with torch.no_grad():
+        generated_ids = model.generate(inputs["input_ids"])
+    translation = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
+    return translation[0]
 
 # Define the Gradio interface
 interface = gr.Interface(