Update app.py

app.py

@@ -5,7 +5,6 @@ import spacy
 import subprocess
 import nltk
 from nltk.corpus import wordnet
-from grammarChecker.util import check_becauseError, check_butError, check_TenseError, check_articleError
 from pattern.en import conjugate, tenses
 
 # Initialize the English text classification pipeline for AI detection
@@ -53,6 +52,13 @@ def capitalize_sentences_and_nouns(text):
 
     return ' '.join(corrected_text)
 
+# Function to check and correct conjunction errors with 'because' and 'but'
+def check_conjunction_errors(text):
+    # Replace misplaced 'because' and 'but'
+    text = text.replace("because, ", "because ")
+    text = text.replace("but, ", "but ")
+    return text
+
 # Function to check and correct tense consistency in sentences using Pattern.en
 def check_tense_consistency(text):
     doc = nlp(text)
@@ -83,14 +89,23 @@ def check_tense_consistency(text):
 
     return ' '.join(corrected_sentences)
 
-# Function to perform grammar and structure corrections using external grammar functions
-def grammar_correction(text):
-    error_count_because, corrected_text_because = check_becauseError(text)
-    error_count_but, corrected_text_but = check_butError(corrected_text_because)
-    error_count_tense, corrected_text_tense = check_TenseError(corrected_text_but)
-    error_count_article, final_corrected_text = check_articleError(corrected_text_tense)
-    
-    return final_corrected_text
+# Function to check and correct article usage ('a', 'an', 'the')
+def check_article_usage(text):
+    doc = nlp(text)
+    corrected_text = []
+
+    for token in doc:
+        if token.text.lower() in ['a', 'an', 'the']:
+            if token.text.lower() == 'a' and token.head.pos_ in ['NOUN', 'ADJ'] and token.head.text[0] in 'aeiou':
+                corrected_text.append('an')
+            elif token.text.lower() == 'an' and token.head.pos_ in ['NOUN', 'ADJ'] and token.head.text[0] not in 'aeiou':
+                corrected_text.append('a')
+            else:
+                corrected_text.append(token.text)
+        else:
+            corrected_text.append(token.text)
+
+    return ' '.join(corrected_text)
 
 # Paraphrasing function using SpaCy and NLTK (Humanifier)
 def paraphrase_with_spacy_nltk(text):
@@ -130,13 +145,16 @@ def paraphrase_and_correct(text):
     # Step 1: Paraphrase the text
     paraphrased_text = paraphrase_with_spacy_nltk(text)
     
-    # Step 2: Grammar and structure corrections
-    grammatically_corrected_text = grammar_correction(paraphrased_text)
+    # Step 2: Check and correct conjunction errors
+    corrected_conjunctions = check_conjunction_errors(paraphrased_text)
+    
+    # Step 3: Check and correct article usage
+    corrected_articles = check_article_usage(corrected_conjunctions)
     
-    # Step 3: Capitalize sentences and proper nouns
-    capitalized_text = capitalize_sentences_and_nouns(grammatically_corrected_text)
+    # Step 4: Capitalize sentences and proper nouns
+    capitalized_text = capitalize_sentences_and_nouns(corrected_articles)
     
-    # Step 4: Check and correct tense consistency
+    # Step 5: Check and correct tense consistency
     final_text = check_tense_consistency(capitalized_text)
     
     return final_text