Update app.py

app.py

@@ -39,35 +39,34 @@ def preprocess_text(text: str, is_spell_corrected: bool = False):
             "original": text,
             "corrected": capitalized_text
         })
-        text = capitalized_text  # Update text for further processing
+    text = capitalized_text  # Update text after preprocessing
 
-    # Transformer spell check (other suggestions)
+    # Translate right after preprocessing
+    client = Client("Frenchizer/space_17")
+    try:
+        translation = client.predict(text)
+    except Exception as e:
+        translation = f"Error: {str(e)}"
+
+    # Transformer spell check (other suggestions), after translation
     spell_checked = spell_checker(text, max_length=512)[0]['generated_text']
     if spell_checked != text:
         result["other_suggestions"].append({
             "original": text,
             "corrected": spell_checked
         })
-        text = spell_checked  # Update text after spell correction
 
     # Add entities and tags
     doc = nlp(text)
     result["entities"] = [{"text": ent.text, "label": ent.label_} for ent in doc.ents]
     result["tags"] = [token.text for token in doc if token.text.startswith(('#', '@'))]
 
-    return text, result
+    return translation, result
 
 def preprocess_and_forward(text: str, is_spell_corrected: bool = False):
     """Process text and forward to translation service."""
-    original_text, preprocessing_result = preprocess_text(text, is_spell_corrected)
-    
-    # Forward original text to translation service
-    client = Client("Frenchizer/space_21")
-    try:
-        translation = client.predict(original_text)
-        return translation, preprocessing_result
-    except Exception as e:
-        return f"Error: {str(e)}", preprocessing_result
+    translation, preprocessing_result = preprocess_text(text, is_spell_corrected)
+    return translation, preprocessing_result
 
 # Gradio interface
 with gr.Blocks() as demo: