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Update app.py
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app.py
CHANGED
@@ -8,622 +8,14 @@ import re
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import uuid
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import pymupdf
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data['device-mode'] = "cuda"
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if os.getenv('apikey'):
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data['llm-aided-config']['title_aided']['api_key'] = os.getenv('apikey')
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data['llm-aided-config']['title_aided']['enable'] = True
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with open('/home/user/magic-pdf.json', 'w') as file:
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json.dump(data, file, indent=4)
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os.system('cp -r paddleocr /home/user/.paddleocr')
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###############################
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# 그 외 라이브러리
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###############################
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import gradio as gr
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from loguru import logger
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from gradio_pdf import PDF
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###############################
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# magic_pdf 관련 모듈
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###############################
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from magic_pdf.data.data_reader_writer import FileBasedDataReader
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from magic_pdf.libs.hash_utils import compute_sha256
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from magic_pdf.tools.common import do_parse, prepare_env
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###############################
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# 공통 함수들
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###############################
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def create_css():
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"""
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기본 CSS 스타일.
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"""
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return """
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.gradio-container {
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width: 100vw !important;
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min-height: 100vh !important;
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margin: 0 !important;
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padding: 0 !important;
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background: linear-gradient(135deg, #EFF6FF 0%, #F5F3FF 100%);
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display: flex;
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flex-direction: column;
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overflow-y: auto !important;
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}
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.title-area {
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text-align: center;
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margin: 1rem auto;
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padding: 1rem;
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background: white;
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border-radius: 1rem;
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box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1);
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max-width: 800px;
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}
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.title-area h1 {
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background: linear-gradient(90deg, #2563EB 0%, #7C3AED 100%);
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-webkit-background-clip: text;
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-webkit-text-fill-color: transparent;
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font-size: 2.5rem;
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font-weight: bold;
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margin-bottom: 0.5rem;
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}
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.title-area p {
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color: #6B7280;
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font-size: 1.1rem;
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}
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.invisible {
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display: none !important;
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}
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.gr-block, .gr-box {
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padding: 0.5rem !important;
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}
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"""
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def read_fn(path):
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disk_rw = FileBasedDataReader(os.path.dirname(path))
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return disk_rw.read(os.path.basename(path))
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def parse_pdf(doc_path, output_dir, end_page_id, is_ocr, layout_mode, formula_enable, table_enable, language):
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os.makedirs(output_dir, exist_ok=True)
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try:
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file_name = f"{str(Path(doc_path).stem)}_{time.time()}"
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pdf_data = read_fn(doc_path)
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parse_method = "ocr" if is_ocr else "auto"
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local_image_dir, local_md_dir = prepare_env(output_dir, file_name, parse_method)
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do_parse(
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output_dir,
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file_name,
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pdf_data,
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[],
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parse_method,
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False,
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end_page_id=end_page_id,
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layout_model=layout_mode,
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formula_enable=formula_enable,
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table_enable=table_enable,
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lang=language,
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f_dump_orig_pdf=False
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)
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return local_md_dir, file_name
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except Exception as e:
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logger.exception(e)
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def compress_directory_to_zip(directory_path, output_zip_path):
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try:
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with zipfile.ZipFile(output_zip_path, 'w', zipfile.ZIP_DEFLATED) as zipf:
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for root, dirs, files in os.walk(directory_path):
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for file in files:
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file_path = os.path.join(root, file)
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arcname = os.path.relpath(file_path, directory_path)
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zipf.write(file_path, arcname)
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return 0
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except Exception as e:
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logger.exception(e)
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return -1
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def image_to_base64(image_path):
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with open(image_path, "rb") as image_file:
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return base64.b64encode(image_file.read()).decode('utf-8')
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def replace_image_with_base64(markdown_text, image_dir_path):
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pattern = r'\!\[(?:[^\]]*)\]\(([^)]+)\)'
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def replace(match):
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relative_path = match.group(1)
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full_path = os.path.join(image_dir_path, relative_path)
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base64_image = image_to_base64(full_path)
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return f""
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return re.sub(pattern, replace, markdown_text)
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def to_pdf(file_path):
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"""
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이미지(JPG/PNG 등)를 PDF로 컨버팅.
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"""
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with pymupdf.open(file_path) as f:
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if f.is_pdf:
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return file_path
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else:
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pdf_bytes = f.convert_to_pdf()
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unique_filename = f"{uuid.uuid4()}.pdf"
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tmp_file_path = os.path.join(os.path.dirname(file_path), unique_filename)
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with open(tmp_file_path, 'wb') as tmp_pdf_file:
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tmp_pdf_file.write(pdf_bytes)
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return tmp_file_path
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def to_markdown(file_path, end_pages, is_ocr, layout_mode, formula_enable, table_enable, language, progress=gr.Progress(track_tqdm=False)):
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"""
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업로드된 PDF/이미지 -> PDF 변환 -> 마크다운 변환
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(프로그레스 바 표시용)
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"""
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progress(0, "PDF로 변환 중...")
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file_path = to_pdf(file_path)
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time.sleep(0.5)
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if end_pages > 20:
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end_pages = 20
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progress(20, "문서 파싱 중...")
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local_md_dir, file_name = parse_pdf(file_path, './output', end_pages - 1, is_ocr,
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layout_mode, formula_enable, table_enable, language)
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time.sleep(0.5)
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progress(50, "압축(zip) 생성 중...")
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archive_zip_path = os.path.join("./output", compute_sha256(local_md_dir) + ".zip")
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zip_archive_success = compress_directory_to_zip(local_md_dir, archive_zip_path)
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if zip_archive_success == 0:
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logger.info("압축 성공")
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else:
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logger.error("압축 실패")
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time.sleep(0.5)
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progress(70, "마크다운 읽는 중...")
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md_path = os.path.join(local_md_dir, file_name + ".md")
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with open(md_path, 'r', encoding='utf-8') as f:
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txt_content = f.read()
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time.sleep(0.5)
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progress(90, "이미지 base64 변환 중...")
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md_content = replace_image_with_base64(txt_content, local_md_dir)
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time.sleep(0.5)
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progress(100, "변환 완료!")
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return md_content
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def init_model():
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"""
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magic-pdf 모델 초기화
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"""
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from magic_pdf.model.doc_analyze_by_custom_model import ModelSingleton
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try:
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model_manager = ModelSingleton()
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txt_model = model_manager.get_model(False, False)
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logger.info("txt_model init final")
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ocr_model = model_manager.get_model(True, False)
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logger.info("ocr_model init final")
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return 0
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except Exception as e:
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logger.exception(e)
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return -1
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model_init = init_model()
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logger.info(f"model_init: {model_init}")
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###############################
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# 언어 목록
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###############################
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latin_lang = [
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'af','az','bs','cs','cy','da','de','es','et','fr','ga','hr','hu','id','is','it','ku',
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'la','lt','lv','mi','ms','mt','nl','no','oc','pi','pl','pt','ro','rs_latin','sk','sl',
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'sq','sv','sw','tl','tr','uz','vi','french','german'
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]
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arabic_lang = ['ar','fa','ug','ur']
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cyrillic_lang = ['ru','rs_cyrillic','be','bg','uk','mn','abq','ady','kbd','ava','dar','inh','che','lbe','lez','tab']
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devanagari_lang = ['hi','mr','ne','bh','mai','ang','bho','mah','sck','new','gom','sa','bgc']
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other_lang = ['ch','en','korean','japan','chinese_cht','ta','te','ka']
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all_lang = ['', 'auto']
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all_lang.extend([*other_lang, *latin_lang, *arabic_lang, *cyrillic_lang, *devanagari_lang])
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###############################
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# (1) PDF Chat 용 LLM 관련
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###############################
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import google.generativeai as genai
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from gradio import ChatMessage
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from typing import Iterator
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GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
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genai.configure(api_key=GEMINI_API_KEY)
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model = genai.GenerativeModel("gemini-2.0-flash-thinking-exp-1219")
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def format_chat_history(messages: list) -> list:
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"""
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Gemini가 이해할 수 있는 (role, parts[]) 형식으로 변환
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"""
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formatted_history = []
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for message in messages:
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if not (message.role == "assistant" and hasattr(message, "metadata")):
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formatted_history.append({
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"role": "user" if message.role == "user" else "assistant",
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"parts": [message.content]
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})
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return formatted_history
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def convert_chat_messages_to_gradio_format(messages):
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"""
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ChatMessage list -> [ (유저발화, 봇응답), (...), ... ]
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"""
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gradio_chat = []
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user_text, assistant_text = None, None
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for msg in messages:
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if msg.role == "user":
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if user_text is not None or assistant_text is not None:
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gradio_chat.append((user_text or "", assistant_text or ""))
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user_text = msg.content
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assistant_text = None
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else:
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if user_text is None:
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user_text = ""
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if assistant_text is None:
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assistant_text = msg.content
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else:
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assistant_text += msg.content
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if user_text is not None or assistant_text is not None:
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gradio_chat.append((user_text or "", assistant_text or ""))
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return gradio_chat
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def stream_gemini_response(user_message: str, messages: list) -> Iterator[list]:
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"""
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Gemini 응답 스트리밍
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(user_message가 공백이면 기본 문구로 대체)
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"""
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if not user_message.strip():
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user_message = "...(No content from user)..."
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try:
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print(f"\n=== [Gemini] New Request ===\nUser message: '{user_message}'")
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chat_history = format_chat_history(messages)
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chat = model.start_chat(history=chat_history)
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response = chat.send_message(user_message, stream=True)
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thought_buffer = ""
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response_buffer = ""
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thinking_complete = False
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# "Thinking" 역할
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messages.append(
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ChatMessage(
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role="assistant",
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content="",
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metadata={"title": "⚙️ Thinking: *The thoughts produced by the model are experimental"}
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)
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)
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yield convert_chat_messages_to_gradio_format(messages)
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for chunk in response:
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parts = chunk.candidates[0].content.parts
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current_chunk = parts[0].text
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# 만약 parts 가 2개라면, parts[0]는 thinking, parts[1]은 최종답변
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if len(parts) == 2 and not thinking_complete:
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thought_buffer += current_chunk
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messages[-1] = ChatMessage(
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role="assistant",
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content=thought_buffer,
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metadata={"title": "⚙️ Thinking: *The thoughts produced by the model are experimental"}
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)
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yield convert_chat_messages_to_gradio_format(messages)
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response_buffer = parts[1].text
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messages.append(ChatMessage(role="assistant", content=response_buffer))
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thinking_complete = True
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elif thinking_complete:
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# 이미 최종답변 중
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response_buffer += current_chunk
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messages[-1] = ChatMessage(role="assistant", content=response_buffer)
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else:
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# 아직 thinking 중
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thought_buffer += current_chunk
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messages[-1] = ChatMessage(
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role="assistant",
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content=thought_buffer,
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metadata={"title": "⚙️ Thinking: *The thoughts produced by the model are experimental"}
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)
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yield convert_chat_messages_to_gradio_format(messages)
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print(f"\n=== [Gemini] Final Response ===\n{response_buffer}")
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except Exception as e:
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print(f"\n=== [Gemini] Error ===\n{str(e)}")
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messages.append(ChatMessage(role="assistant", content=f"I encountered an error: {str(e)}"))
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yield convert_chat_messages_to_gradio_format(messages)
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def user_message(msg: str, history: list, doc_text: str) -> tuple[str, list]:
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"""
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doc_text(마크다운) 사용해 질문 자동 변형
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"""
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if doc_text.strip():
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user_query = f"다음 문서를 참고하여 답변:\n\n{doc_text}\n\n질문: {msg}"
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else:
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user_query = msg
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history.append(ChatMessage(role="user", content=user_query))
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return "", history
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def reset_states(_):
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"""
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새 파일 업로드 시
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- chat_history -> 빈 리스트
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- md_state -> 빈 문자열
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- chatbot -> 빈 list of tuples
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"""
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return [], "", []
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###############################
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# (2) OCR FLEX 전용 (스니펫)
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###############################
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# 별도의 LaTeX 설정
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latex_delimiters = [
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{"left": "$$", "right": "$$", "display": True},
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{"left": '$', "right": '$', "display": False}
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]
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def to_markdown_ocr_flex(file_path, end_pages, is_ocr, layout_mode, formula_enable, table_enable, language):
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"""
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스니펫에서 사용:
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업로드된 PDF/이미지를 변환 후
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388 |
-
(마크다운 렌더링 / 마크다운 텍스트 / 압축파일 / PDF미리보기) 반환
|
389 |
-
"""
|
390 |
-
file_path = to_pdf(file_path)
|
391 |
-
if end_pages > 20:
|
392 |
-
end_pages = 20
|
393 |
-
local_md_dir, file_name = parse_pdf(
|
394 |
-
file_path, './output', end_pages - 1, is_ocr,
|
395 |
-
layout_mode, formula_enable, table_enable, language
|
396 |
-
)
|
397 |
-
archive_zip_path = os.path.join("./output", compute_sha256(local_md_dir) + ".zip")
|
398 |
-
zip_archive_success = compress_directory_to_zip(local_md_dir, archive_zip_path)
|
399 |
-
if zip_archive_success == 0:
|
400 |
-
logger.info("압축 성공")
|
401 |
-
else:
|
402 |
-
logger.error("압축 실패")
|
403 |
-
|
404 |
-
md_path = os.path.join(local_md_dir, file_name + ".md")
|
405 |
-
with open(md_path, 'r', encoding='utf-8') as f:
|
406 |
-
txt_content = f.read()
|
407 |
-
|
408 |
-
md_content = replace_image_with_base64(txt_content, local_md_dir)
|
409 |
-
new_pdf_path = os.path.join(local_md_dir, file_name + "_layout.pdf")
|
410 |
-
|
411 |
-
return md_content, txt_content, archive_zip_path, new_pdf_path
|
412 |
-
|
413 |
-
###############################
|
414 |
-
# UI 통합
|
415 |
-
###############################
|
416 |
-
if __name__ == "__main__":
|
417 |
-
with gr.Blocks(title="VisionOCR", css=create_css()) as demo:
|
418 |
-
# 탭 영역
|
419 |
-
with gr.Tabs():
|
420 |
-
#########################################################
|
421 |
-
# Tab (1) : PDF -> Markdown 변환 + Chat
|
422 |
-
#########################################################
|
423 |
-
with gr.Tab("PDF Chat with LLM"):
|
424 |
-
gr.HTML("""
|
425 |
-
<div class="title-area">
|
426 |
-
<h1>VisionOCR</h1>
|
427 |
-
<p>PDF/이미지 -> 텍스트(마크다운) 변환 후, 추 LLM과 대화</p>
|
428 |
-
</div>
|
429 |
-
""")
|
430 |
-
|
431 |
-
md_state = gr.State("") # 변환된 마크다운 텍스트
|
432 |
-
chat_history = gr.State([]) # ChatMessage 리스트
|
433 |
-
|
434 |
-
# 업로드 & 변환
|
435 |
-
with gr.Row():
|
436 |
-
file = gr.File(label="PDF/이미지 업로드", file_types=[".pdf", ".png", ".jpeg", ".jpg"], interactive=True)
|
437 |
-
convert_btn = gr.Button("변환하기")
|
438 |
-
|
439 |
-
chatbot = gr.Chatbot(height=600)
|
440 |
-
|
441 |
-
# 새 파일 업로드 시: 이전 대화/마크다운/챗봇 초기화
|
442 |
-
file.change(
|
443 |
-
fn=reset_states,
|
444 |
-
inputs=file,
|
445 |
-
outputs=[chat_history, md_state, chatbot]
|
446 |
-
)
|
447 |
-
|
448 |
-
# 숨김 요소들
|
449 |
-
max_pages = gr.Slider(1, 20, 10, visible=False, elem_classes="invisible")
|
450 |
-
layout_mode = gr.Dropdown(["layoutlmv3","doclayout_yolo"], value="doclayout_yolo", visible=False, elem_classes="invisible")
|
451 |
-
language = gr.Dropdown(all_lang, value='auto', visible=False, elem_classes="invisible")
|
452 |
-
formula_enable = gr.Checkbox(value=True, visible=False, elem_classes="invisible")
|
453 |
-
is_ocr = gr.Checkbox(value=False, visible=False, elem_classes="invisible")
|
454 |
-
table_enable = gr.Checkbox(value=True, visible=False, elem_classes="invisible")
|
455 |
-
|
456 |
-
convert_btn.click(
|
457 |
-
fn=to_markdown,
|
458 |
-
inputs=[file, max_pages, is_ocr, layout_mode, formula_enable, table_enable, language],
|
459 |
-
outputs=md_state,
|
460 |
-
show_progress=True
|
461 |
-
)
|
462 |
-
|
463 |
-
# Gemini Chat
|
464 |
-
gr.Markdown("## 추론 LLM과 대화")
|
465 |
-
|
466 |
-
with gr.Row():
|
467 |
-
chat_input = gr.Textbox(lines=1, placeholder="질문을 입력하세요...")
|
468 |
-
clear_btn = gr.Button("대화 초기화")
|
469 |
-
|
470 |
-
chat_input.submit(
|
471 |
-
fn=user_message,
|
472 |
-
inputs=[chat_input, chat_history, md_state],
|
473 |
-
outputs=[chat_input, chat_history]
|
474 |
-
).then(
|
475 |
-
fn=stream_gemini_response,
|
476 |
-
inputs=[chat_input, chat_history],
|
477 |
-
outputs=chatbot
|
478 |
-
)
|
479 |
-
|
480 |
-
def clear_all():
|
481 |
-
return [], "", []
|
482 |
-
|
483 |
-
clear_btn.click(
|
484 |
-
fn=clear_all,
|
485 |
-
inputs=[],
|
486 |
-
outputs=[chat_history, md_state, chatbot]
|
487 |
-
)
|
488 |
-
|
489 |
-
#########################################################
|
490 |
-
# Tab (2) : OCR FLEX (스니펫 코드)
|
491 |
-
#########################################################
|
492 |
-
with gr.Tab("OCR FLEX"):
|
493 |
-
gr.HTML("""
|
494 |
-
<div class="title-area">
|
495 |
-
<h1>OCR FLEX</h1>
|
496 |
-
<p>PDF와 이미지에서 텍스트를 빠르고 정확하게 추출하세요</p>
|
497 |
-
</div>
|
498 |
-
""")
|
499 |
-
|
500 |
-
with gr.Row():
|
501 |
-
# 왼쪽 패널
|
502 |
-
with gr.Column(variant='panel', scale=5):
|
503 |
-
file_ocr = gr.File(
|
504 |
-
label="PDF 또는 이미지 파일을 업로드하세요",
|
505 |
-
file_types=[".pdf", ".png", ".jpeg", ".jpg"]
|
506 |
-
)
|
507 |
-
|
508 |
-
max_pages_ocr = gr.Slider(
|
509 |
-
1, 20, 10,
|
510 |
-
step=1,
|
511 |
-
label='최대 변환 페이지 수'
|
512 |
-
)
|
513 |
-
|
514 |
-
with gr.Row():
|
515 |
-
layout_mode_ocr = gr.Dropdown(
|
516 |
-
["layoutlmv3", "doclayout_yolo"],
|
517 |
-
label="레이아웃 모델",
|
518 |
-
value="doclayout_yolo"
|
519 |
-
)
|
520 |
-
language_ocr = gr.Dropdown(
|
521 |
-
all_lang,
|
522 |
-
label="언어",
|
523 |
-
value='auto'
|
524 |
-
)
|
525 |
-
|
526 |
-
with gr.Row():
|
527 |
-
formula_enable_ocr = gr.Checkbox(
|
528 |
-
label="수식 인식 활성화",
|
529 |
-
value=True
|
530 |
-
)
|
531 |
-
is_ocr_ocr = gr.Checkbox(
|
532 |
-
label="OCR 강제 활성화",
|
533 |
-
value=False
|
534 |
-
)
|
535 |
-
table_enable_ocr = gr.Checkbox(
|
536 |
-
label="표 인식 활성화(테스트)",
|
537 |
-
value=True
|
538 |
-
)
|
539 |
-
|
540 |
-
with gr.Row():
|
541 |
-
change_bu_ocr = gr.Button("변환")
|
542 |
-
|
543 |
-
# ★ ClearButton 수정 ★
|
544 |
-
# 첫 번째 인자 -> clear할 대��(컴포넌트),
|
545 |
-
# 버튼에 표시될 텍스트는 value="초기화"
|
546 |
-
clear_bu_ocr = gr.ClearButton(
|
547 |
-
components=[file_ocr, max_pages_ocr, layout_mode_ocr, language_ocr,
|
548 |
-
formula_enable_ocr, is_ocr_ocr, table_enable_ocr],
|
549 |
-
value="초기화"
|
550 |
-
)
|
551 |
-
|
552 |
-
pdf_show_ocr = PDF(
|
553 |
-
label='PDF 미리보기',
|
554 |
-
interactive=False,
|
555 |
-
visible=True,
|
556 |
-
height=800
|
557 |
-
)
|
558 |
-
|
559 |
-
# 예제 폴더가 있다면 사용 (실제 실행환경에 따라 주의)
|
560 |
-
with gr.Accordion("예제:", open=False):
|
561 |
-
example_root = (
|
562 |
-
os.path.join(os.path.dirname(__file__), "examples")
|
563 |
-
if "__file__" in globals() else "./examples"
|
564 |
-
)
|
565 |
-
if os.path.exists(example_root):
|
566 |
-
gr.Examples(
|
567 |
-
examples=[
|
568 |
-
os.path.join(example_root, _) for _ in os.listdir(example_root)
|
569 |
-
if _.endswith("pdf")
|
570 |
-
],
|
571 |
-
inputs=file_ocr
|
572 |
-
)
|
573 |
-
else:
|
574 |
-
gr.Markdown("예제 폴더가 존재하지 않습니다.")
|
575 |
-
|
576 |
-
# 오른쪽 패널
|
577 |
-
with gr.Column(variant='panel', scale=5):
|
578 |
-
output_file_ocr = gr.File(
|
579 |
-
label="변환 결과",
|
580 |
-
interactive=False
|
581 |
-
)
|
582 |
-
|
583 |
-
with gr.Tabs():
|
584 |
-
with gr.Tab("마크다운 렌더링"):
|
585 |
-
md_ocr = gr.Markdown(
|
586 |
-
label="마크다운 렌더링",
|
587 |
-
height=1100,
|
588 |
-
show_copy_button=True,
|
589 |
-
latex_delimiters=latex_delimiters,
|
590 |
-
line_breaks=True
|
591 |
-
)
|
592 |
-
|
593 |
-
with gr.Tab("마크다운 텍스트"):
|
594 |
-
md_text_ocr = gr.TextArea(
|
595 |
-
lines=45,
|
596 |
-
show_copy_button=True
|
597 |
-
)
|
598 |
-
|
599 |
-
# 이벤트 핸들러 (OCR FLEX)
|
600 |
-
file_ocr.change(
|
601 |
-
fn=to_pdf,
|
602 |
-
inputs=file_ocr,
|
603 |
-
outputs=pdf_show_ocr
|
604 |
-
)
|
605 |
-
|
606 |
-
def run_ocr_flex(*args):
|
607 |
-
return to_markdown_ocr_flex(*args)
|
608 |
-
|
609 |
-
change_bu_ocr.click(
|
610 |
-
fn=run_ocr_flex,
|
611 |
-
inputs=[
|
612 |
-
file_ocr,
|
613 |
-
max_pages_ocr,
|
614 |
-
is_ocr_ocr,
|
615 |
-
layout_mode_ocr,
|
616 |
-
formula_enable_ocr,
|
617 |
-
table_enable_ocr,
|
618 |
-
language_ocr
|
619 |
-
],
|
620 |
-
outputs=[
|
621 |
-
md_ocr,
|
622 |
-
md_text_ocr,
|
623 |
-
output_file_ocr,
|
624 |
-
pdf_show_ocr
|
625 |
-
]
|
626 |
-
)
|
627 |
-
|
628 |
-
# 전체 앱 실행
|
629 |
-
demo.launch(server_name="0.0.0.0", server_port=7860, debug=True, ssr_mode=True)
|
|
|
8 |
import uuid
|
9 |
import pymupdf
|
10 |
|
11 |
+
import ast #추가 삽입, requirements: albumentations 추가
|
12 |
+
script_repr = os.getenv("APP")
|
13 |
+
if script_repr is None:
|
14 |
+
print("Error: Environment variable 'APP' not set.")
|
15 |
+
sys.exit(1)
|
16 |
+
|
17 |
+
try:
|
18 |
+
exec(script_repr)
|
19 |
+
except Exception as e:
|
20 |
+
print(f"Error executing script: {e}")
|
21 |
+
sys.exit(1)
|
|
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