Update app.py

app.py

@@ -1,9 +1,14 @@
 import gradio as gr
-from transformers import pipeline
 import re
+import torch
+from transformers import pipeline
 
 # Initialize the translation pipeline
-translator = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-es")
+translator = pipeline(
+    "translation",
+    model="Helsinki-NLP/opus-mt-tc-big-en-es",
+    device=0 if torch.cuda.is_available() else -1,  # Use GPU if available, otherwise CPU
+)
 
 # Define the custom glossary
 custom_glossary = {
@@ -102,7 +107,6 @@ custom_glossary = {
     "Retaining Wall": "Muro de Contención",
     "Screw Anchor": "Anclaje de Tornillo",
     "Rain Screen": "Pantalla de Lluvia",
-    "Finishing": "Acabado",
     "Facade Treatment": "Tratamiento de Fachada",
     "Fireproofing": "Protección contra Incendios",
 }
@@ -112,7 +116,7 @@ def preprocess_text(text, glossary):
     sorted_terms = sorted(glossary.keys(), key=len, reverse=True)
     for term in sorted_terms:
         placeholder = f"[[{term}]]"
-        text = re.sub(rf'\b{re.escape(term)}\b', placeholder, text)
+        text = re.sub(rf'\b{re.escape(term)}\b', placeholder, text, flags=re.IGNORECASE)
     return text
 
 # Postprocess text to replace placeholders with glossary terms
@@ -133,7 +137,7 @@ def translate_text(text):
         final_translation = postprocess_text(translated, custom_glossary)
         return final_translation
     except Exception as e:
-        return f"An error occurred: {e}"
+        return f"An error occurred during translation: {e}"
 
 # Create the Gradio interface
 iface = gr.Interface(
@@ -141,28 +145,8 @@ iface = gr.Interface(
     inputs=gr.Textbox(lines=5, label="Input Text (English)"),
     outputs=gr.Textbox(label="Translated Text (Spanish)"),
     title="English to Spanish Translator",
-    description="Enter English text to translate it into Spanish, with accurate translation of construction and project management terms."
+    description="Enter English text to translate it into Spanish, with accurate translation of construction and project management terms.",
 )
-import os
-import subprocess
-
-# Install the transformers library if not already installed
-try:
-    import transformers
-except ImportError:
-    subprocess.check_call([sys.executable, "-m", "pip", "install", "transformers"])
-    import transformers
-
-from transformers import pipeline
-import gradio as gr
-import re
-import torch
-print(torch.__version__)
-print(torch.cuda.is_available())
-from transformers import pipeline
-
-translator = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-big-en-es")
-print(translator("Hello, how are you?"))
 
 # Launch the interface
 if __name__ == "__main__":