Spaces:
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Update app-backup.py
Browse files- app-backup.py +318 -93
app-backup.py
CHANGED
@@ -8,7 +8,9 @@ import re
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import uuid
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import pymupdf
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os.system('pip uninstall -y magic-pdf')
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os.system('pip install git+https://github.com/opendatalab/MinerU.git@dev')
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os.system('wget https://github.com/opendatalab/MinerU/raw/dev/scripts/download_models_hf.py -O download_models_hf.py')
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@@ -28,17 +30,26 @@ with open('/home/user/magic-pdf.json', 'w') as file:
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os.system('cp -r paddleocr /home/user/.paddleocr')
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###############################
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#
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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 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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def create_css():
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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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@@ -135,6 +146,9 @@ def replace_image_with_base64(markdown_text, image_dir_path):
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return re.sub(pattern, replace, markdown_text)
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def to_pdf(file_path):
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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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@@ -147,7 +161,10 @@ def to_pdf(file_path):
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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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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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@@ -183,6 +200,9 @@ def to_markdown(file_path, end_pages, is_ocr, layout_mode, formula_enable, table
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return md_content
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def init_model():
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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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model_init = init_model()
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logger.info(f"model_init: {model_init}")
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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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@@ -211,17 +234,21 @@ 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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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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import time
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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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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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@@ -231,8 +258,37 @@ def format_chat_history(messages: list) -> list:
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})
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return formatted_history
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def stream_gemini_response(user_message: str, messages: list) -> Iterator[list]:
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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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@@ -246,6 +302,7 @@ def stream_gemini_response(user_message: str, messages: list) -> Iterator[list]:
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response_buffer = ""
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thinking_complete = False
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messages.append(
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ChatMessage(
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role="assistant",
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parts = chunk.candidates[0].content.parts
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current_chunk = parts[0].text
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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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@@ -272,9 +330,11 @@ def stream_gemini_response(user_message: str, messages: list) -> Iterator[list]:
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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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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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thought_buffer += current_chunk
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messages[-1] = ChatMessage(
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role="assistant",
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@@ -291,32 +351,10 @@ def stream_gemini_response(user_message: str, messages: list) -> Iterator[list]:
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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 convert_chat_messages_to_gradio_format(messages):
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"""ChatMessage list -> [ (유저발화, 봇응답), (...), ... ]"""
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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 user_message(msg: str, history: list, doc_text: str) -> tuple[str, list]:
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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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"""
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return [], "", []
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"""
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md_state = gr.State("") # 변환된 마크다운 텍스트
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chat_history = gr.State([]) # ChatMessage 리스트
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# 업로드 & 변환
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with gr.Row():
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file = gr.File(label="PDF/이미지 업로드", file_types=[".pdf", ".png", ".jpeg", ".jpg"], interactive=True)
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convert_btn = gr.Button("변환하기")
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# 새 파일 업로드 시: 이전 대화/마크다운/챗봇 초기화
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chatbot = gr.Chatbot(height=600) # 실제 Chatbot 컴포넌트
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file.change(
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fn=reset_states,
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inputs=file,
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outputs=[chat_history, md_state, chatbot] # <--- 문자열 "chatbot" 아니라 chatbot 컴포넌트 객체
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)
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show_progress=True # 프로그레스바 표시
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)
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with gr.Row():
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chat_input = gr.Textbox(lines=1, placeholder="질문을 입력하세요...")
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clear_btn = gr.Button("대화 초기화")
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chat_input.submit(
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fn=user_message,
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inputs=[chat_input, chat_history, md_state],
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outputs=[chat_input, chat_history]
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).then(
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fn=stream_gemini_response,
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inputs=[chat_input, chat_history],
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outputs=chatbot
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)
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fn=clear_all,
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inputs=[],
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outputs=[chat_history, md_state, chatbot]
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)
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if __name__ == "__main__":
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-
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import uuid
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import pymupdf
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###############################
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# 환경 설정
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###############################
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os.system('pip uninstall -y magic-pdf')
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os.system('pip install git+https://github.com/opendatalab/MinerU.git@dev')
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os.system('wget https://github.com/opendatalab/MinerU/raw/dev/scripts/download_models_hf.py -O download_models_hf.py')
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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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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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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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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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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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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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})
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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 ""))
|
284 |
+
|
285 |
+
return gradio_chat
|
286 |
+
|
287 |
def stream_gemini_response(user_message: str, messages: list) -> Iterator[list]:
|
288 |
+
"""
|
289 |
+
Gemini 응답 스트리밍
|
290 |
+
(user_message가 공백이면 기본 문구로 대체)
|
291 |
+
"""
|
292 |
if not user_message.strip():
|
293 |
user_message = "...(No content from user)..."
|
294 |
|
|
|
302 |
response_buffer = ""
|
303 |
thinking_complete = False
|
304 |
|
305 |
+
# "Thinking" 역할
|
306 |
messages.append(
|
307 |
ChatMessage(
|
308 |
role="assistant",
|
|
|
316 |
parts = chunk.candidates[0].content.parts
|
317 |
current_chunk = parts[0].text
|
318 |
|
319 |
+
# 만약 parts 가 2개라면, parts[0]는 thinking, parts[1]은 최종답변
|
320 |
if len(parts) == 2 and not thinking_complete:
|
321 |
thought_buffer += current_chunk
|
322 |
messages[-1] = ChatMessage(
|
|
|
330 |
messages.append(ChatMessage(role="assistant", content=response_buffer))
|
331 |
thinking_complete = True
|
332 |
elif thinking_complete:
|
333 |
+
# 이미 최종답변 중
|
334 |
response_buffer += current_chunk
|
335 |
messages[-1] = ChatMessage(role="assistant", content=response_buffer)
|
336 |
else:
|
337 |
+
# 아직 thinking 중
|
338 |
thought_buffer += current_chunk
|
339 |
messages[-1] = ChatMessage(
|
340 |
role="assistant",
|
|
|
351 |
messages.append(ChatMessage(role="assistant", content=f"I encountered an error: {str(e)}"))
|
352 |
yield convert_chat_messages_to_gradio_format(messages)
|
353 |
|
|
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|
|
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|
|
|
|
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|
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|
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|
|
|
|
354 |
def user_message(msg: str, history: list, doc_text: str) -> tuple[str, list]:
|
355 |
+
"""
|
356 |
+
doc_text(마크다운) 사용해 질문 자동 변형
|
357 |
+
"""
|
358 |
if doc_text.strip():
|
359 |
user_query = f"다음 문서를 참고하여 답변:\n\n{doc_text}\n\n질문: {msg}"
|
360 |
else:
|
|
|
372 |
"""
|
373 |
return [], "", []
|
374 |
|
375 |
+
###############################
|
376 |
+
# (2) OCR FLEX 전용 (스니펫)
|
377 |
+
###############################
|
378 |
+
# 별도의 LaTeX 설정
|
379 |
+
latex_delimiters = [
|
380 |
+
{"left": "$$", "right": "$$", "display": True},
|
381 |
+
{"left": '$', "right": '$', "display": False}
|
382 |
+
]
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
383 |
|
384 |
+
def to_markdown_ocr_flex(file_path, end_pages, is_ocr, layout_mode, formula_enable, table_enable, language):
|
385 |
+
"""
|
386 |
+
스니펫에서 사용:
|
387 |
+
업로드된 PDF/이미지를 변환 후
|
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 대상(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)
|