app.py

import gradio as gr
import difflib
import re
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

def load_model(checkpoint_path):
    tokenizer = AutoTokenizer.from_pretrained(checkpoint_path)
    model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint_path)
    return model, tokenizer

checkpoint_path = "Diezu/Batpho_v2"
model, tokenizer = load_model(checkpoint_path)

def correct_spelling(text):
    inputs = tokenizer(text, return_tensors="pt", max_length=512, truncation=True)
    outputs = model.generate(**inputs, max_length=512, num_beams=5, early_stopping=True)
    corrected_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return corrected_text

def find_spelling_errors(s1, s2):
    a = s1.split()
    b = s2.split()
    matcher = difflib.SequenceMatcher(None, a, b)
    highlighted_text = []
    corrected_words = {}
    
    for tag, i1, i2, j1, j2 in matcher.get_opcodes():
        if tag == 'replace':
            incorrect_word = " ".join(a[i1:i2])
            correct_word = " ".join(b[j1:j2])
            highlighted_text.append(f'<button onclick="replaceWord(this, \"{correct_word}\")" style="color: red; text-decoration: underline; border: none; background: none;">{incorrect_word}</button>')
            corrected_words[incorrect_word] = correct_word
        elif tag == 'delete':
            highlighted_text.append(f'<span style="color: orange; text-decoration: line-through;">{" ".join(a[i1:i2])}</span>')
        elif tag == 'insert':
            highlighted_text.append(f'<span style="color: green; font-weight: bold;">{" ".join(b[j1:j2])}</span>')
        else:
            highlighted_text.append(" ".join(a[i1:i2]))
    
    return " ".join(highlighted_text), corrected_words

def process_text(text):
    sentences = re.split(r'(?<=[.!?])\s+', text)
    corrected_sentences = []
    highlighted_sentences = []
    all_corrected_words = {}
    
    for sentence in sentences:
        if sentence.strip():
            corrected_text = correct_spelling(sentence)
            highlighted_text, corrected_words = find_spelling_errors(sentence, corrected_text)
            corrected_sentences.append(corrected_text)
            highlighted_sentences.append(highlighted_text)
            all_corrected_words.update(corrected_words)
    
    return "<br>".join(highlighted_sentences), "\n".join(corrected_sentences), all_corrected_words

def apply_full_correction(text, corrected_words):
    for incorrect, correct in corrected_words.items():
        text = text.replace(incorrect, f'<span style="color: blue; font-weight: bold;">{correct}</span>')
    return text

demo = gr.Blocks()
with demo:
    input_text = gr.Textbox(placeholder="Nhập văn bản có lỗi chính tả...")
    output_html = gr.HTML()
    corrected_textbox = gr.Textbox()
    corrected_words_state = gr.State({})
    
    btn_check = gr.Button("Phát hiện lỗi")
    btn_correct_all = gr.Button("Sửa toàn bộ lỗi")
    
    def update_text(text):
        highlighted, corrected, corrected_words = process_text(text)
        return highlighted, corrected, corrected_words
    
    btn_check.click(update_text, inputs=input_text, outputs=[output_html, corrected_textbox, corrected_words_state])
    btn_correct_all.click(apply_full_correction, inputs=[input_text, corrected_words_state], outputs=output_html)

demo.launch()