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Update app.py
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app.py
CHANGED
@@ -7,6 +7,225 @@ import torch
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from PIL import Image
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import numpy as np
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@app.post("/process_document")
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async def process_document(
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file: UploadFile = File(...),
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@@ -167,4 +386,12 @@ async def process_document(
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return JSONResponse(
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status_code=500,
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content={"error": str(e)}
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-
)
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from PIL import Image
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import numpy as np
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+
# Copyright (c) Opendatalab. All rights reserved.
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import base64
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import json
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import os
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import time
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import zipfile
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from pathlib import Path
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import re
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import uuid
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import pymupdf
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from io import BytesIO
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from fastapi import FastAPI, File, UploadFile
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from fastapi.responses import JSONResponse
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import uvicorn
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# Initialize FastAPI app
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app = FastAPI()
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# Setup and installation commands
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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('python download_models_hf.py')
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# Configure magic-pdf settings
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with open('/home/user/magic-pdf.json', 'r') as file:
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data = json.load(file)
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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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# Import required modules
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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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from loguru import logger
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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 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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if is_ocr:
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parse_method = "ocr"
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else:
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parse_method = "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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"""
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压缩指定目录到一个 ZIP 文件。
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:param directory_path: 要压缩的目录路径
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:param output_zip_path: 输出的 ZIP 文件路径
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"""
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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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# 遍历目录中的所有文件和子目录
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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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# 构建完整的文件路径
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file_path = os.path.join(root, file)
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# 计算相对路径
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arcname = os.path.relpath(file_path, directory_path)
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# 添加文件到 ZIP 文件
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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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# 匹配Markdown中的图片标签
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pattern = r'\!\[(?:[^\]]*)\]\(([^)]+)\)'
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# 替换图片链接
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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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# 应用替换
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return re.sub(pattern, replace, markdown_text)
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def to_markdown(file_path, end_pages, is_ocr, layout_mode, formula_enable, table_enable, language):
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file_path = to_pdf(file_path)
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if end_pages > 20:
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end_pages = 20
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# 获取识别的md文件以及压缩包文件路径
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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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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("压缩成功")
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else:
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logger.error("压缩失败")
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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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md_content = replace_image_with_base64(txt_content, local_md_dir)
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# 返回转换后的PDF路径
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new_pdf_path = os.path.join(local_md_dir, file_name + "_layout.pdf")
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return md_content, txt_content, archive_zip_path, new_pdf_path
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latex_delimiters = [{"left": "$$", "right": "$$", "display": True},
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{"left": '$', "right": '$', "display": False}]
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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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txt_model = model_manager.get_model(False, False)
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logger.info(f"txt_model init final")
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ocr_model = model_manager.get_model(True, False)
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logger.info(f"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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with open("header.html", "r") as file:
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header = file.read()
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latin_lang = [
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'af', 'az', 'bs', 'cs', 'cy', 'da', 'de', 'es', 'et', 'fr', 'ga', 'hr',
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'hu', 'id', 'is', 'it', 'ku', 'la', 'lt', 'lv', 'mi', 'ms', 'mt', 'nl',
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'no', 'oc', 'pi', 'pl', 'pt', 'ro', 'rs_latin', 'sk', 'sl', 'sq', 'sv',
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'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 = [
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'ru', 'rs_cyrillic', 'be', 'bg', 'uk', 'mn', 'abq', 'ady', 'kbd', 'ava',
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'dar', 'inh', 'che', 'lbe', 'lez', 'tab'
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]
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devanagari_lang = [
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'hi', 'mr', 'ne', 'bh', 'mai', 'ang', 'bho', 'mah', 'sck', 'new', 'gom',
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'sa', 'bgc'
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]
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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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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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else:
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pdf_bytes = f.convert_to_pdf()
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# 将pdfbytes 写入到uuid.pdf中
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# 生成唯一的文件名
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unique_filename = f"{uuid.uuid4()}.pdf"
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# 构建完整的文件路径
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tmp_file_path = os.path.join(os.path.dirname(file_path), unique_filename)
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# 将字节数据写入文件
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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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@app.post("/process_document")
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async def process_document(
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file: UploadFile = File(...),
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return JSONResponse(
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status_code=500,
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content={"error": str(e)}
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)
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# Initialize models
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model_init = init_model()
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logger.info(f"model_init: {model_init}")
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if __name__ == "__main__":
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uvicorn.run(app, host="0.0.0.0", port=7860)
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