Update app.py

app.py

@@ -21,22 +21,40 @@ except OSError:
 pipeline_en = pipeline(task="text-classification", model="Hello-SimpleAI/chatgpt-detector-roberta")
 
 def predict_en(text):
-    """ Function to predict the label and score for English text (AI Detection) """
+    """Function to predict the label and score for English text (AI Detection)"""
     res = pipeline_en(text)[0]
     return res['label'], res['score']
 
 def get_synonyms_nltk(word, pos):
-    """ Function to get synonyms using NLTK WordNet """
+    """Function to get synonyms using NLTK WordNet"""
     synsets = wordnet.synsets(word, pos=pos)
     if synsets:
         lemmas = synsets[0].lemmas()
         return [lemma.name() for lemma in lemmas]
     return []
 
+def rephrase_text(text):
+    """Function to rephrase text by replacing words with synonyms"""
+    doc = nlp(text)
+    rephrased_text = []
+
+    for token in doc:
+        if token.pos_ in ["NOUN", "VERB", "ADJ"]:
+            synonyms = get_synonyms_nltk(token.text, pos=token.pos_.lower())
+            if synonyms:
+                rephrased_text.append(synonyms[0])  # Replace with first synonym found
+            else:
+                rephrased_text.append(token.text)
+        else:
+            rephrased_text.append(token.text)
+    
+    return ' '.join(rephrased_text)
+
 def capitalize_sentences_and_nouns(text):
-    """ Function to capitalize the first letter of sentences and proper nouns """
+    """Function to capitalize the first letter of sentences and proper nouns"""
     doc = nlp(text)
     corrected_text = []
+
     for sent in doc.sents:
         sentence = []
         for token in sent:
@@ -47,10 +65,11 @@ def capitalize_sentences_and_nouns(text):
             else:
                 sentence.append(token.text)
         corrected_text.append(' '.join(sentence))
+
     return ' '.join(corrected_text)
 
 def correct_tense_errors(text):
-    """ Function to correct tense errors in a sentence """
+    """Function to correct tense errors in a sentence"""
     doc = nlp(text)
     corrected_text = []
     for token in doc:
@@ -62,7 +81,7 @@ def correct_tense_errors(text):
     return ' '.join(corrected_text)
 
 def correct_singular_plural_errors(text):
-    """ Function to correct singular/plural errors """
+    """Function to correct singular/plural errors"""
     doc = nlp(text)
     corrected_text = []
     for token in doc:
@@ -82,7 +101,7 @@ def correct_singular_plural_errors(text):
     return ' '.join(corrected_text)
 
 def correct_article_errors(text):
-    """ Function to check and correct article errors """
+    """Function to check and correct article errors"""
     doc = nlp(text)
     corrected_text = []
     for token in doc:
@@ -99,32 +118,28 @@ def correct_article_errors(text):
     return ' '.join(corrected_text)
 
 def paraphrase_and_correct(text):
-    """ Function to paraphrase and correct grammar """
-    paraphrased_text = capitalize_sentences_and_nouns(text)  # Capitalize first to ensure proper noun capitalization
-    
-    # Apply grammatical corrections
-    paraphrased_text = correct_article_errors(paraphrased_text)
-    paraphrased_text = correct_singular_plural_errors(paraphrased_text)
-    paraphrased_text = correct_tense_errors(paraphrased_text)
-
-    return paraphrased_text
-
-# Setup Gradio interface
+    """Function to rephrase and correct grammar"""
+    rephrased_text = rephrase_text(text)
+    rephrased_text = capitalize_sentences_and_nouns(rephrased_text)  # Capitalize first to ensure proper noun capitalization
+    rephrased_text = correct_article_errors(rephrased_text)
+    rephrased_text = correct_tense_errors(rephrased_text)
+    rephrased_text = correct_singular_plural_errors(rephrased_text)
+    return rephrased_text
+
+# Define Gradio interface
 with gr.Blocks() as demo:
-    with gr.Tab("AI Detection"):
-        t1 = gr.Textbox(lines=5, label='Text')
-        button1 = gr.Button("🤖 Predict!")
-        label1 = gr.Textbox(lines=1, label='Predicted Label')
-        score1 = gr.Textbox(lines=1, label='Score')
-
-        button1.click(predict_en, inputs=[t1], outputs=[label1, score1])
-
-    with gr.Tab("Humanifier"):
-        text_input = gr.Textbox(lines=5, label="Input Text")
-        paraphrase_button = gr.Button("Paraphrase & Correct")
-        output_text = gr.Textbox(label="Paraphrased Text")
-
-        paraphrase_button.click(paraphrase_and_correct, inputs=[text_input], outputs=[output_text])
+    with gr.Row():
+        t1 = gr.Textbox(label="Input Text", lines=5)
+        button1 = gr.Button("Process")
+    with gr.Row():
+        output_text = gr.Textbox(label="Processed Text", lines=5)
+        label1 = gr.Label(label="AI Detection Label")
+        score1 = gr.Label(label="AI Detection Score")
+    
+    button1.click(
+        fn=lambda text: (paraphrase_and_correct(text), *predict_en(text)),
+        inputs=[t1],
+        outputs=[output_text, label1, score1]
+    )
 
-# Launch the app
 demo.launch()