# Added more redundant/filler words
def remove_redundant_words(text):
    doc = nlp(text)
    meaningless_words = {"actually", "basically", "literally", "really", "very", "just", "quite", "rather", "simply", "that", "kind of", "sort of", "you know", "honestly", "seriously"}
    filtered_text = [token.text for token in doc if token.text.lower() not in meaningless_words]
    return ' '.join(filtered_text)

# Capitalize sentences and proper nouns
def capitalize_sentences_and_nouns(text):
    doc = nlp(text)
    corrected_text = []
    for sent in doc.sents:
        sentence = []
        for token in sent:
            if token.i == sent.start or token.pos_ == "PROPN":
                sentence.append(token.text.capitalize())
            else:
                sentence.append(token.text.lower())
        corrected_text.append(' '.join(sentence))
    return ' '.join(corrected_text)

# Function to dynamically correct tenses and verb forms
def correct_tense_errors(text):
    doc = nlp(text)
    corrected_text = []
    for token in doc:
        if token.pos_ == "VERB" and token.dep_ in {"aux", "auxpass"}:
            lemma = wordnet.morphy(token.text, wordnet.VERB) or token.text
            corrected_text.append(lemma)
        else:
            corrected_text.append(token.text)
    return ' '.join(corrected_text)

# Enhanced function to handle subject-verb agreement
def ensure_subject_verb_agreement(text):
    doc = nlp(text)
    corrected_text = []
    for token in doc:
        if token.dep_ == "nsubj" and token.head.pos_ == "VERB":
            if token.tag_ == "NN" and token.head.tag_ != "VBZ":
                corrected_text.append(token.head.lemma_ + "s")
            elif token.tag_ == "NNS" and token.head.tag_ == "VBZ":
                corrected_text.append(token.head.lemma_)
            else:
                corrected_text.append(token.head.text)
        else:
            corrected_text.append(token.text)
    return ' '.join(corrected_text)

# Ensure proper apostrophe usage and possessives
def correct_apostrophes(text):
    text = re.sub(r"\b(\w+)s\b(?<!\'s)", r"\1's", text)  # Simple apostrophe correction
    text = re.sub(r"\b(\w+)s'\b", r"\1s'", text)         # Handles plural possessives
    return text

# Enhanced punctuation
def enhance_punctuation(text):
    text = re.sub(r'\s+([?.!,";:])', r'\1', text)         # Remove extra space before punctuation
    text = re.sub(r'([?.!,";:])(\S)', r'\1 \2', text)     # Add space after punctuation if needed
    return text

# Paraphrasing using synonyms and correcting semantic errors
def rephrase_with_synonyms(text):
    doc = nlp(text)
    rephrased_text = []

    for token in doc:
        pos_tag = None
        if token.pos_ in ["NOUN", "VERB", "ADJ", "ADV"]:
            pos_tag = getattr(wordnet, token.pos_)

        if pos_tag:
            synonyms = get_synonyms_nltk(token.lemma_, pos_tag)
            if synonyms:
                synonym = synonyms[0]
                if token.pos_ == "VERB":
                    if token.tag_ == "VBG":
                        synonym = synonym + 'ing'
                    elif token.tag_ in ["VBD", "VBN"]:
                        synonym = synonym + 'ed'
                    elif token.tag_ == "VBZ":
                        synonym = synonym + 's'
                rephrased_text.append(synonym)
            else:
                rephrased_text.append(token.text)
        else:
            rephrased_text.append(token.text)

    return ' '.join(rephrased_text)

# Comprehensive text correction
def paraphrase_and_correct(text):
    text = enhanced_spell_check(text)
    text = remove_redundant_words(text)
    text = capitalize_sentences_and_nouns(text)
    text = correct_tense_errors(text)
    text = correct_singular_plural_errors(text)
    text = correct_article_errors(text)
    text = enhance_punctuation(text)
    text = correct_apostrophes(text)
    text = rephrase_with_synonyms(text)
    text = correct_double_negatives(text)
    text = ensure_subject_verb_agreement(text)
    return text

# Integrate with Gradio UI
def gradio_interface(text):
    corrected_text = paraphrase_and_correct(text)
    return corrected_text

iface = gr.Interface(
    fn=gradio_interface,
    inputs=gr.Textbox(lines=5, placeholder="Enter text here..."),
    outputs=[gr.Textbox(label="Corrected Text")],
    title="Grammar & Semantic Error Correction",
)

if __name__ == "__main__":
    iface.launch()