Update app.py

app.py

@@ -5,6 +5,7 @@ import spacy
 import subprocess
 import nltk
 from nltk.corpus import wordnet
+import language_tool_python
 
 from gensim import downloader as api
 
@@ -29,6 +30,9 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased-finetuned-sst-2-english")
 model = AutoModelForSequenceClassification.from_pretrained("distilbert-base-uncased-finetuned-sst-2-english").to(device)
 
+# Initialize LanguageTool for grammar correction
+tool = language_tool_python.LanguageTool('en-US')
+
 # AI detection function using DistilBERT
 def detect_ai_generated(text):
     inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512).to(device)
@@ -73,7 +77,11 @@ def paraphrase_with_spacy_nltk(text):
     
     # Join the words back into a sentence
     paraphrased_sentence = ' '.join(paraphrased_words)
-    return paraphrased_sentence
+    
+    # Correct the grammar of the paraphrased sentence
+    corrected_sentence = tool.correct(paraphrased_sentence)
+    
+    return corrected_sentence
 
 # Gradio interface definition
 with gr.Blocks() as interface:
@@ -81,7 +89,7 @@ with gr.Blocks() as interface:
         with gr.Column():
             text_input = gr.Textbox(lines=5, label="Input Text")
             detect_button = gr.Button("AI Detection")
-            paraphrase_button = gr.Button("Paraphrase with spaCy & NLTK")
+            paraphrase_button = gr.Button("Paraphrase with spaCy & NLTK (Grammar Corrected)")
         with gr.Column():
             output_text = gr.Textbox(label="Output")