Update app.py

app.py

@@ -22,12 +22,8 @@ inflect_engine = inflect.engine()
 nltk.download('wordnet')
 nltk.download('omw-1.4')
 
-# Ensure the SpaCy model is installed
-try:
-    nlp = spacy.load("en_core_web_sm")
-except OSError:
-    subprocess.run(["python", "-m", "spacy", "download", "en_core_web_sm"])
-    nlp = spacy.load("en_core_web_sm")
+# Load the SpaCy model
+nlp = spacy.load("en_core_web_sm")
 
 # Function to predict the label and score for English text (AI Detection)
 def predict_en(text):
@@ -173,18 +169,18 @@ def correct_spelling(text):
     corrected_words = []
     for word in words:
         corrected_word = spell.correction(word)
-        corrected_words.append(corrected_word if corrected_word else word)  # Keep original if correction is None
+        corrected_words.append(corrected_word if corrected_word else word)
     return ' '.join(corrected_words)
 
 # Function to correct punctuation issues
 def correct_punctuation(text):
-    text = re.sub(r'\s+([?.!,";:])', r'\1', text)  # Remove space before punctuation
-    text = re.sub(r'([?.!,";:])\s+', r'\1 ', text)  # Ensure a single space after punctuation
+    text = re.sub(r'\s+([?.!,";:])', r'\1', text)
+    text = re.sub(r'([?.!,";:])\s+', r'\1 ', text)
     return text
 
 # Function to ensure correct handling of possessive forms
 def handle_possessives(text):
-    text = re.sub(r"\b(\w+)'s\b", r"\1's", text)  # Preserve possessive forms
+    text = re.sub(r"\b(\w+)'s\b", r"\1's", text)
     return text
 
 # Function to rephrase text and replace words with their synonyms while maintaining form
@@ -231,37 +227,37 @@ def paraphrase_and_correct(text):
     # Remove meaningless or redundant words first
     cleaned_text = remove_redundant_words(text)
     
-    # Capitalize sentences and nouns
-    paraphrased_text = capitalize_sentences_and_nouns(cleaned_text)
-    
+    # Capitalize sentences and proper nouns
+    cleaned_text = capitalize_sentences_and_nouns(cleaned_text)
+
     # Correct tense errors
-    paraphrased_text = correct_tense_errors(paraphrased_text)
-    
+    cleaned_text = correct_tense_errors(cleaned_text)
+
     # Correct singular/plural errors
-    paraphrased_text = correct_singular_plural_errors(paraphrased_text)
-    
+    cleaned_text = correct_singular_plural_errors(cleaned_text)
+
     # Correct article errors
-    paraphrased_text = correct_article_errors(paraphrased_text)
-    
+    cleaned_text = correct_article_errors(cleaned_text)
+
     # Correct spelling
-    paraphrased_text = correct_spelling(paraphrased_text)
-    
+    cleaned_text = correct_spelling(cleaned_text)
+
     # Correct punctuation issues
-    paraphrased_text = correct_punctuation(paraphrased_text)
-    
+    cleaned_text = correct_punctuation(cleaned_text)
+
     # Handle possessives
-    paraphrased_text = handle_possessives(paraphrased_text)
-    
+    cleaned_text = handle_possessives(cleaned_text)
+
     # Replace words with synonyms
-    paraphrased_text = rephrase_with_synonyms(paraphrased_text)
+    cleaned_text = rephrase_with_synonyms(cleaned_text)
 
     # Correct double negatives
-    paraphrased_text = correct_double_negatives(paraphrased_text)
+    cleaned_text = correct_double_negatives(cleaned_text)
 
     # Ensure subject-verb agreement
-    paraphrased_text = ensure_subject_verb_agreement(paraphrased_text)
+    cleaned_text = ensure_subject_verb_agreement(cleaned_text)
 
-    return paraphrased_text
+    return cleaned_text
 
 # Function to detect AI-generated content
 def detect_ai(text):
@@ -277,7 +273,7 @@ def gradio_interface(text):
 # Create Gradio interface
 iface = gr.Interface(fn=gradio_interface,
                      inputs=gr.Textbox(lines=5, placeholder="Enter text here..."),
-                     outputs=[gr.outputs.Label(num_top_classes=2), gr.outputs.Textbox()],
+                     outputs=[gr.Label(num_top_classes=2), gr.Textbox()],
                      title="AI Detection and Grammar Correction",
                      description="Detect AI-generated content and correct grammar issues.")