Update app.py

app.py

@@ -5,7 +5,7 @@ import spacy
 import subprocess
 import nltk
 from nltk.corpus import wordnet
-import language_tool_python
+from gingerit.gingerit import GingerIt
 
 from gensim import downloader as api
 
@@ -30,8 +30,11 @@ 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')
+# Initialize Gingerit for grammar correction
+def correct_grammar_with_gingerit(text):
+    parser = GingerIt()
+    result = parser.parse(text)
+    return result['result']
 
 # AI detection function using DistilBERT
 def detect_ai_generated(text):
@@ -50,7 +53,7 @@ def get_synonyms_nltk(word, pos):
         return [lemma.name() for lemma in lemmas]
     return []
 
-# Paraphrasing function using spaCy and NLTK
+# Paraphrasing function using spaCy and NLTK with Gingerit grammar correction
 def paraphrase_with_spacy_nltk(text):
     doc = nlp(text)
     paraphrased_words = []
@@ -78,8 +81,8 @@ def paraphrase_with_spacy_nltk(text):
     # Join the words back into a sentence
     paraphrased_sentence = ' '.join(paraphrased_words)
     
-    # Correct the grammar of the paraphrased sentence
-    corrected_sentence = tool.correct(paraphrased_sentence)
+    # Correct the grammar of the paraphrased sentence using Gingerit
+    corrected_sentence = correct_grammar_with_gingerit(paraphrased_sentence)
     
     return corrected_sentence