Added gingerit for grammar correction and updated app.py

app.py

@@ -6,6 +6,7 @@ import subprocess
 import nltk
 from nltk.corpus import wordnet
 from gensim import downloader as api
+from gingerit.gingerit import GingerIt
 
 # Ensure necessary NLTK data is downloaded
 nltk.download('wordnet')
@@ -28,6 +29,9 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 tokenizer_ai = AutoTokenizer.from_pretrained("distilbert-base-uncased-finetuned-sst-2-english")
 model_ai = AutoModelForSequenceClassification.from_pretrained("distilbert-base-uncased-finetuned-sst-2-english").to(device)
 
+# Initialize GingerIt parser
+parser = GingerIt()
+
 # AI detection function using DistilBERT
 def detect_ai_generated(text):
     inputs = tokenizer_ai(text, return_tensors="pt", truncation=True, max_length=512).to(device)
@@ -96,13 +100,21 @@ def paraphrase_with_spacy_nltk(text):
     
     return corrected_text
 
-# Combined function: Paraphrase -> Capitalization
+# Function to correct grammar using GingerIt
+def correct_grammar(text):
+    result = parser.parse(text)
+    return result['result']
+
+# Combined function: Paraphrase -> Capitalization -> Grammar Correction
 def paraphrase_and_correct(text):
     # Step 1: Paraphrase the text
     paraphrased_text = paraphrase_with_spacy_nltk(text)
     
     # Step 2: Capitalize sentences and proper nouns
-    final_text = capitalize_sentences_and_nouns(paraphrased_text)
+    capitalized_text = capitalize_sentences_and_nouns(paraphrased_text)
+    
+    # Step 3: Correct grammar
+    final_text = correct_grammar(capitalized_text)
     
     return final_text