Update app.py

app.py

@@ -9,11 +9,6 @@ from nltk.corpus import wordnet
 # Initialize the English text classification pipeline for AI detection
 pipeline_en = pipeline(task="text-classification", model="Hello-SimpleAI/chatgpt-detector-roberta")
 
-# Function to predict the label and score for English text (AI Detection)
-def predict_en(text):
-    res = pipeline_en(text)[0]
-    return res['label'], res['score']
-
 # Ensure necessary NLTK data is downloaded for Humanifier
 nltk.download('wordnet')
 nltk.download('omw-1.4')
@@ -109,8 +104,21 @@ def correct_article_errors(text):
 
 # Function to paraphrase and correct grammar
 def paraphrase_and_correct(text):
-    paraphrased_text = capitalize_sentences_and_nouns(text)  # Capitalize first to ensure proper noun capitalization
-    
+    # Enhance rephrasing by using more advanced SpaCy functionalities
+    paraphrased_text = capitalize_sentences_and_nouns(text)  # Start by capitalizing sentences properly
+
+    # Use SpaCy to rephrase by substituting synonyms, restructuring sentences, etc.
+    doc = nlp(paraphrased_text)
+    rephrased = []
+    for token in doc:
+        synonyms = get_synonyms_nltk(token.text, pos=wordnet.VERB if token.pos_ == "VERB" else wordnet.NOUN)
+        if synonyms:
+            rephrased.append(synonyms[0])
+        else:
+            rephrased.append(token.text)
+
+    paraphrased_text = ' '.join(rephrased)
+
     # Apply grammatical corrections
     paraphrased_text = correct_article_errors(paraphrased_text)
     paraphrased_text = correct_singular_plural_errors(paraphrased_text)