Update app.py

app.py

@@ -11,11 +11,19 @@ import random
 import string
 
 # Ensure necessary NLTK data is downloaded
-nltk.download('punkt')        
-nltk.download('stopwords')    
-nltk.download('averaged_perceptron_tagger')  
-nltk.download('wordnet')      
-nltk.download('omw-1.4')
+def download_nltk_resources():
+    try:
+        nltk.download('punkt')
+        nltk.download('stopwords')
+        nltk.download('averaged_perceptron_tagger')
+        nltk.download('wordnet')
+        nltk.download('omw-1.4')
+        nltk.download('punkt_tab')  # Added punkt_tab download
+    except Exception as e:
+        print(f"Error downloading NLTK resources: {e}")
+
+# Call the download function
+download_nltk_resources()
 
 top_words = set(stopwords.words("english"))  # More efficient as a set
 
@@ -207,27 +215,25 @@ def correct_spelling(text):
 # Main function for paraphrasing and grammar correction
 def paraphrase_and_correct(text):
     cleaned_text = remove_redundant_words(text)
+    cleaned_text = fix_punctuation_spacing(cleaned_text)
+    cleaned_text = fix_possessives(cleaned_text)
+    cleaned_text = capitalize_sentences_and_nouns(cleaned_text)
+    cleaned_text = force_first_letter_capital(cleaned_text)
+    cleaned_text = correct_tense_errors(cleaned_text)
+    cleaned_text = correct_article_errors(cleaned_text)
+    cleaned_text = ensure_subject_verb_agreement(cleaned_text)
+    cleaned_text = correct_spelling(cleaned_text)
     plag_removed = plagiarism_removal(cleaned_text)
-    paraphrased_text = capitalize_sentences_and_nouns(plag_removed)
-    paraphrased_text = force_first_letter_capital(paraphrased_text)
-    paraphrased_text = correct_article_errors(paraphrased_text)
-    paraphrased_text = correct_tense_errors(paraphrased_text)
-    paraphrased_text = ensure_subject_verb_agreement(paraphrased_text)
-    paraphrased_text = fix_possessives(paraphrased_text)
-    paraphrased_text = correct_spelling(paraphrased_text)
-    paraphrased_text = fix_punctuation_spacing(paraphrased_text)
-
-    return paraphrased_text
-
-# Gradio app setup
+    return plag_removed
+
+# Create the Gradio interface
 with gr.Blocks() as demo:
+    gr.Markdown("# AI Text Processor")
     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='Prob')
-
-        button1.click(fn=predict_en, inputs=t1, outputs=[label1, score1])
+        t1 = gr.Textbox(lines=5, label='Input Text')
+        output1 = gr.Label()
+        button1 = gr.Button("🚀 Process!")
+        button1.click(fn=predict_en, inputs=t1, outputs=output1)
 
     with gr.Tab("Paraphrasing and Grammar Correction"):
         t2 = gr.Textbox(lines=5, label='Input Text')