Update app.py

app.py

@@ -5,7 +5,7 @@ import spacy
 import subprocess
 import json
 import nltk
-from nltk.corpus import wordnet, stopwords  # Import stopwords here
+from nltk.corpus import wordnet, stopwords
 from spellchecker import SpellChecker
 import re
 import random
@@ -13,24 +13,22 @@ import string
 
 # Ensure necessary NLTK data is downloaded
 def download_nltk_resources():
-    try:nltk.download('punkt')
+    try:
+        nltk.download('punkt')
         nltk.download('stopwords')
         nltk.download('averaged_perceptron_tagger')
-        nltk.download('averaged_perceptron_tagger_eng')
         nltk.download('wordnet')
         nltk.download('omw-1.4')
-        nltk.download('punkt_tab')
-
     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
+top_words = set(stopwords.words("english"))
 
 # Path to the thesaurus file
-thesaurus_file_path = 'en_thesaurus.jsonl (1).old'  # Ensure the file path is correct
+thesaurus_file_path = 'en_thesaurus.jsonl'  # Ensure the file path is correct
 
 # Function to load the thesaurus into a dictionary
 def load_thesaurus(file_path):
@@ -38,7 +36,6 @@ def load_thesaurus(file_path):
     try:
         with open(file_path, 'r', encoding='utf-8') as file:
             for line in file:
-                # Parse each line as a JSON object
                 entry = json.loads(line.strip())
                 word = entry.get("word")
                 synonyms = entry.get("synonyms", [])
@@ -77,7 +74,7 @@ def predict_en(text):
     except Exception as e:
         return f"Error during AI detection: {e}"
 
-# Modified plagiarism_remover function to use the loaded thesaurus
+# Function to remove plagiarism
 def plagiarism_remover(word):
     if word.lower() in top_words or word.lower() in exclude_words or word in string.punctuation:
         return word
@@ -234,6 +231,7 @@ def paraphrase_and_correct(text):
 # 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='Input Text')
         btn1 = gr.Button("Detect AI")