Update app.py

app.py

@@ -1,13 +1,11 @@
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
 import spacy
 import subprocess
 import nltk
 from nltk.corpus import wordnet
 from gensim import downloader as api
-from autocorrect import Speller  # Autocorrect library for spelling correction
-from gingerit.gingerit import GingerIt  # GingerIt for grammar correction
+from gramformer import Gramformer
 
 # Ensure necessary NLTK data is downloaded
 nltk.download('wordnet')
@@ -26,16 +24,14 @@ word_vectors = api.load("glove-wiki-gigaword-50")
 # Check for GPU and set the device accordingly
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
-# Load AI Detector model and tokenizer from Hugging Face (DistilBERT)
+# Load Gramformer for grammar correction (model 2 for correction)
+gf = Gramformer(models=2, use_gpu=torch.cuda.is_available())
+
+# AI detection model and tokenizer remain the same as before
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
 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 Autocorrect for spelling correction
-spell = Speller()
-
-# Initialize GingerIt for grammar correction
-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)
@@ -127,17 +123,12 @@ def paraphrase_with_spacy_nltk(text):
     
     return corrected_text
 
-# Function to correct spelling using autocorrect and grammar using GingerIt
-def correct_spelling_and_grammar(text):
-    # Step 1: Correct spelling using autocorrect
-    corrected_spelling = spell(text)
-    
-    # Step 2: Correct grammar using GingerIt
-    grammar_correction = parser.parse(corrected_spelling)
-    
-    return grammar_correction['result']
+# Function to correct grammar using Gramformer
+def correct_grammar(text):
+    corrected_sentences = gf.correct(text)
+    return corrected_sentences[0] if corrected_sentences else text
 
-# Combined function: Paraphrase -> Tense Check -> Capitalization -> Spelling and Grammar Correction
+# Combined function: Paraphrase -> Tense Check -> Capitalization -> Grammar Correction
 def paraphrase_and_correct(text):
     # Step 1: Paraphrase the text
     paraphrased_text = paraphrase_with_spacy_nltk(text)
@@ -148,8 +139,8 @@ def paraphrase_and_correct(text):
     # Step 3: Capitalize sentences and proper nouns
     capitalized_text = capitalize_sentences_and_nouns(tense_checked_text)
     
-    # Step 4: Correct spelling and grammar
-    final_text = correct_spelling_and_grammar(capitalized_text)
+    # Step 4: Correct grammar using Gramformer
+    final_text = correct_grammar(capitalized_text)
     
     return final_text