Update app.py

app.py

@@ -11,7 +11,6 @@ from spellchecker import SpellChecker
 import re
 import string
 import random
-from language_tool_python import LanguageTool
 
 # Download necessary NLTK data
 nltk.download('punkt')
@@ -35,9 +34,6 @@ pipeline_en = pipeline(task="text-classification", model="Hello-SimpleAI/chatgpt
 # Initialize the spell checker
 spell = SpellChecker()
 
-# Initialize LanguageTool
-tool = LanguageTool('en-US')
-
 # Ensure the SpaCy model is installed
 try:
     nlp = spacy.load("en_core_web_sm")
@@ -78,12 +74,43 @@ def plagiarism_removal(text):
     corrected_text = []
     for i in range(len(final_text)):
         if final_text[i] in string.punctuation and i > 0:
-            corrected_text[-1] += final_text[i]
+            corrected_text[-1] += final_text[i]  
         else:
             corrected_text.append(final_text[i])
 
     return " ".join(corrected_text)
 
+def change_voice(text):
+    doc = nlp(text)
+    sentences = list(doc.sents)
+    modified_sentences = []
+
+    for sent in sentences:
+        # Randomly choose to convert to active or passive voice
+        if random.choice([True, False]):  # Change voice
+            subject = None
+            verb = None
+            obj = None
+            
+            for token in sent:
+                if token.dep_ == 'nsubj':  # Subject
+                    subject = token
+                elif token.dep_ == 'ROOT':  # Main verb
+                    verb = token
+                elif token.dep_ == 'dobj':  # Object
+                    obj = token
+
+            if subject and verb and obj:
+                # Active to Passive
+                passive_sentence = f"{obj.text} was {verb.lemma_} by {subject.text}"
+                modified_sentences.append(passive_sentence)
+            else:
+                modified_sentences.append(sent.text)  # No change if structure doesn't match
+        else:
+            modified_sentences.append(sent.text)  # No change
+
+    return ' '.join(modified_sentences)
+
 def predict_en(text):
     res = pipeline_en(text)[0]
     return res['label'], res['score']
@@ -192,13 +219,12 @@ def correct_spelling(text):
             corrected_words.append(word)
     return ' '.join(corrected_words)
 
-def grammar_check(text):
-    matches = tool.check(text)
-    corrected_text = language_tool_python.utils.correct(text, matches)
-    return corrected_text
-
+# Main function for paraphrasing and grammar correction
 def paraphrase_and_correct(text):
-    cleaned_text = remove_redundant_words(text)
+    # Change narrative voice randomly
+    voice_changed_text = change_voice(text)
+    
+    cleaned_text = remove_redundant_words(voice_changed_text)
     plag_removed = plagiarism_removal(cleaned_text)
     paraphrased_text = capitalize_sentences_and_nouns(plag_removed)
     paraphrased_text = force_first_letter_capital(paraphrased_text)
@@ -206,33 +232,11 @@ def paraphrase_and_correct(text):
     paraphrased_text = correct_tense_errors(paraphrased_text)
     paraphrased_text = ensure_subject_verb_agreement(paraphrased_text)
     paraphrased_text = fix_possessives(paraphrased_text)
-    paraphrased_text = correct_spelling(paraphrased_text)
     paraphrased_text = fix_punctuation_spacing(paraphrased_text)
-    paraphrased_text = grammar_check(paraphrased_text)
-
+    paraphrased_text = correct_spelling(paraphrased_text)
+    
     return paraphrased_text
 
-with gr.Blocks() as demo:
-    with gr.Tab("AI Detection"):
-        t1 = gr.Textbox(lines=5, label='Text')
-        button1 = gr.Button("🤖 Predict!")
-        label1 = gr.Textbox(lines=1, label='Predicted Label 🎃')
-        score1 = gr.Textbox(lines=1, label='Prob')
-
-        button1.click(fn=predict_en, inputs=t1, outputs=[label1, score1])
-
-    with gr.Tab("Paraphrasing & Grammar Correction"):
-        t2 = gr.Textbox(lines=5, label='Enter text for paraphrasing and grammar correction')
-        button2 = gr.Button("🔄 Paraphrase and Correct")
-        result2 = gr.Textbox(lines=5, label='Corrected Text')
-
-        button2.click(fn=paraphrase_and_correct, inputs=t2, outputs=result2)
-
-if __name__ == "__main__":
-    try:
-        subprocess.run(["java", "-version"], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
-    except FileNotFoundError:
-        print("Java is not installed. Please install Java to use LanguageTool.")
-        exit(1)
-    
-    demo.launch(share=True)
+# Gradio interface setup
+iface = gr.Interface(fn=paraphrase_and_correct, inputs="text", outputs="text", title="Text Paraphraser and Corrector", description="A tool to paraphrase and correct grammar in your text.")
+iface.launch()