Update app.py

app.py

@@ -23,39 +23,41 @@ def preprocess_capitalization(text: str) -> str:
     
     return " ".join(processed_words)
 
-def preprocess_text(text: str, is_spell_corrected: bool = False):
+def preprocess_text(text: str, is_suggestion_applied: bool = False):
     """Process text and return corrections with position information."""
     result = {
         "spell_suggestions": [],
-        "other_suggestions": [],  # For spell_checker suggestions
+        "other_suggestions": [],
         "entities": [],
         "tags": []
     }
 
-    # Apply capitalization preprocessing (spell suggestions)
-    capitalized_text = preprocess_capitalization(text)
-    if capitalized_text != text and not is_spell_corrected:
-        result["spell_suggestions"].append({
-            "original": text,
-            "corrected": capitalized_text
-        })
-    text = capitalized_text  # Update text after preprocessing
+    # Only generate suggestions if no suggestion has been applied
+    if not is_suggestion_applied:
+        # Apply capitalization preprocessing (spell suggestions)
+        capitalized_text = preprocess_capitalization(text)
+        if capitalized_text != text:
+            result["spell_suggestions"].append({
+                "original": text,
+                "corrected": capitalized_text
+            })
+            text = capitalized_text  # Update text for further processing
 
-    # Translate right after preprocessing
+        # Transformer spell check (other suggestions)
+        spell_checked = spell_checker(text, max_length=512)[0]['generated_text']
+        if spell_checked != text:
+            result["other_suggestions"].append({
+                "original": text,
+                "corrected": spell_checked
+            })
+
+    # Translate the text (after preprocessing if first pass, or as-is if suggestion applied)
     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
-        })
-
     # Add entities and tags
     doc = nlp(text)
     result["entities"] = [{"text": ent.text, "label": ent.label_} for ent in doc.ents]
@@ -63,18 +65,18 @@ def preprocess_text(text: str, is_spell_corrected: bool = False):
 
     return translation, result
 
-def preprocess_and_forward(text: str, is_spell_corrected: bool = False):
+def preprocess_and_forward(text: str, is_suggestion_applied: bool = False):
     """Process text and forward to translation service."""
-    translation, preprocessing_result = preprocess_text(text, is_spell_corrected)
+    translation, preprocessing_result = preprocess_text(text, is_suggestion_applied)
     return translation, preprocessing_result
 
 # Gradio interface
 with gr.Blocks() as demo:
     input_text = gr.Textbox(label="Input Text")
-    is_spell_corrected = gr.Checkbox(label="Spell Corrected", value=False, visible=False)  # Hidden flag
+    is_suggestion_applied = gr.Checkbox(label="Suggestion Applied", value=False, visible=False)  # Hidden flag
     output_text = gr.Textbox(label="Output Text")
     preprocess_button = gr.Button("Process")
-    preprocess_button.click(fn=preprocess_and_forward, inputs=[input_text, is_spell_corrected], outputs=[output_text])
+    preprocess_button.click(fn=preprocess_and_forward, inputs=[input_text, is_suggestion_applied], outputs=[output_text])
 
 if __name__ == "__main__":
     demo.launch()