Update app.py

app.py

@@ -44,24 +44,38 @@ def preprocess_text(text: str):
         })
         text = capitalized_text  # Update text for further processing
 
-    # Transformer spell check
+    # Transformer spell check - only for words that look misspelled
     spell_checked = spell_checker(text, max_length=512)[0]['generated_text']
     if spell_checked != text:
-        result["spell_suggestions"].append({
-            "original": text,
-            "corrected": spell_checked,
-            "type": "spell"
-        })
+        spell_words = spell_checked.split()
+        text_words = text.split()
+        
+        # Only suggest spell corrections for words that are actually different
+        for orig, corrected in zip(text_words, spell_words):
+            if orig.lower() != corrected.lower():  # Compare case-insensitive
+                result["spell_suggestions"].append({
+                    "original": orig,
+                    "corrected": corrected,
+                    "type": "spell"
+                })
 
-    # Add example other suggestions (you would replace this with your actual logic)
-    for word in text.split():
-        if word.endswith('.') or word.endswith('?') or word.endswith('!'):
+    # Add fluency/style suggestions (other suggestions)
+    # Only add if the word isn't already in spell suggestions
+    spell_originals = {s["original"] for s in result["spell_suggestions"]}
+    words = text.split()
+    
+    for word in words:
+        # Skip words that have spell suggestions or already have punctuation
+        if word in spell_originals or word.endswith(('.', '?', '!')):
             continue
-        result["other_suggestions"].append({
-            "original": word,
-            "corrected": word + "!",
-            "type": "other"
-        })
+            
+        # Add style suggestions (like adding punctuation)
+        if not word.endswith('!'):  # Only suggest adding exclamation if it doesn't already have one
+            result["other_suggestions"].append({
+                "original": word,
+                "corrected": word + "!",
+                "type": "other"
+            })
 
     # Add entities and tags
     doc = nlp(text)