Merge pull request #2625 from opendatalab/release-2.0.0

Release 2.0.0

Merge pull request #2625 from opendatalab/release-2.0.0
Release 2.0.0
6ab12348 · Xiaomeng Zhao · GitHub · 9487d33d · 4fbec469 · 9487d33d
Unverified Commit 6ab12348 authored Jun 13, 2025 by Xiaomeng Zhao Committed by GitHub Jun 13, 2025
20 changed files
--- a/next_docs/zh_cn/_static/image/layout_example.png
+++ b/next_docs/zh_cn/_static/image/layout_example.png
--- a/next_docs/zh_cn/_static/image/logo.png
+++ b/next_docs/zh_cn/_static/image/logo.png
--- a/next_docs/zh_cn/_static/image/pipeline.drawio.svg
+++ b/next_docs/zh_cn/_static/image/pipeline.drawio.svg
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"/></switch></g></g></g><g 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\ No newline at end of file
--- a/next_docs/zh_cn/_static/image/poly.png
+++ b/next_docs/zh_cn/_static/image/poly.png
--- a/next_docs/zh_cn/_static/image/project_panorama_en.png
+++ b/next_docs/zh_cn/_static/image/project_panorama_en.png
--- a/next_docs/zh_cn/_static/image/project_panorama_zh_cn.png
+++ b/next_docs/zh_cn/_static/image/project_panorama_zh_cn.png
--- a/next_docs/zh_cn/_static/image/spans_example.png
+++ b/next_docs/zh_cn/_static/image/spans_example.png
--- a/next_docs/zh_cn/_static/image/web_demo_1.png
+++ b/next_docs/zh_cn/_static/image/web_demo_1.png
--- a/next_docs/zh_cn/additional_notes/faq.rst
+++ b/next_docs/zh_cn/additional_notes/faq.rst
-常见问题解答
-============
-
-1.在较新版本的mac上使用命令安装pip install magic-pdf[full] zsh: no matches found: magic-pdf[full]
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-在 macOS 上，默认的 shell 从 Bash 切换到了 Z shell，而 Z shell 对于某些类型的字符串匹配有特殊的处理逻辑，这可能导致no matches found错误。 可以通过在命令行禁用globbing特性，再尝试运行安装命令
-
-.. code:: bash
-
-   setopt no_nomatch
-   pip install magic-pdf[full]
-
-2.使用过程中遇到_pickle.UnpicklingError: invalid load key, ‘v’.错误
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-可能是由于模型文件未下载完整导致，可尝试重新下载模型文件后再试。参考：https://github.com/opendatalab/MinerU/issues/143
-
-3.模型文件应该下载到哪里/models-dir的配置应该怎么填
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-模型文件的路径输入是在”magic-pdf.json”中通过
-
-.. code:: json
-
-   {
-     "models-dir": "/tmp/models"
-   }
-
-进行配置的。这个路径是绝对路径而不是相对路径，绝对路径的获取可在models目录中通过命令 “pwd” 获取。
-参考：https://github.com/opendatalab/MinerU/issues/155#issuecomment-2230216874
-
-4.在WSL2的Ubuntu22.04中遇到报错\ ``ImportError: libGL.so.1: cannot open shared object file: No such file or directory``
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-WSL2的Ubuntu22.04中缺少\ ``libgl``\ 库，可通过以下命令安装\ ``libgl``\ 库解决：
-
-.. code:: bash
-
-   sudo apt-get install libgl1-mesa-glx
-
-参考：https://github.com/opendatalab/MinerU/issues/388
-
-5.遇到报错 ``ModuleNotFoundError : Nomodulenamed 'fairscale'``
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-需要卸载该模块并重新安装
-
-.. code:: bash
-
-   pip uninstall fairscale
-   pip install fairscale
-
-参考：https://github.com/opendatalab/MinerU/issues/411
-
-6.在部分较新的设备如H100上，使用CUDA加速OCR时解析出的文字乱码。
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-cuda11对新显卡的兼容性不好，需要升级paddle使用的cuda版本
-
-.. code:: bash
-
-   pip install paddlepaddle-gpu==3.0.0b1 -i https://www.paddlepaddle.org.cn/packages/stable/cu123/
-
-参考：https://github.com/opendatalab/MinerU/issues/558
-
-7.在部分Linux服务器上，程序一运行就报错 ``非法指令 (核心已转储)`` 或 ``Illegal instruction (core dumped)``
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-可能是因为服务器CPU不支持AVX/AVX2指令集，或cpu本身支持但被运维禁用了，可以尝试联系运维解除限制或更换服务器。
-
-参考：https://github.com/opendatalab/MinerU/issues/591 ，https://github.com/opendatalab/MinerU/issues/736
--- a/next_docs/zh_cn/additional_notes/glossary.rst
+++ b/next_docs/zh_cn/additional_notes/glossary.rst
-
-
-名词解释
-===========
-
-1. jsonl 
-    TODO: add description
-
-2. magic-pdf.json
-    TODO: add description
-
--- a/next_docs/zh_cn/additional_notes/known_issues.rst
+++ b/next_docs/zh_cn/additional_notes/known_issues.rst
-已知问题
-============
-
-  阅读顺序基于模型对可阅读内容在空间中的分布进行排序，在极端复杂的排版下可能会部分区域乱序
-  不支持竖排文字
-  目录和列表通过规则进行识别，少部分不常见的列表形式可能无法识别
-  标题只有一级，目前不支持标题分级
-  代码块在layout模型里还没有支持
-  漫画书、艺术图册、小学教材、习题尚不能很好解析
-  表格识别在复杂表格上可能会出现行/列识别错误
-  在小语种PDF上，OCR识别可能会出现字符不准确的情况（如拉丁文的重音符号、阿拉伯文易混淆字符等）
-  部分公式可能会无法在markdown中渲染
-
--- a/next_docs/zh_cn/conf.py
+++ b/next_docs/zh_cn/conf.py
-# Configuration file for the Sphinx documentation builder.
-#
-# This file only contains a selection of the most common options. For a full
-# list see the documentation:
-# https://www.sphinx-doc.org/en/master/usage/configuration.html
-
-# -- Path setup --------------------------------------------------------------
-
-# If extensions (or modules to document with autodoc) are in another directory,
-# add these directories to sys.path here. If the directory is relative to the
-# documentation root, use os.path.abspath to make it absolute, like shown here.
-
-import os
-import subprocess
-import sys
-
-from sphinx.ext import autodoc
-from docutils import nodes
-from docutils.parsers.rst import Directive
-
-def install(package):
-    subprocess.check_call([sys.executable, '-m', 'pip', 'install', package])
-
-
-requirements_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', 'requirements.txt'))
-if os.path.exists(requirements_path):
-    with open(requirements_path) as f:
-        packages = f.readlines()
-    for package in packages:
-        install(package.strip())
-
-sys.path.insert(0, os.path.abspath('../..'))
-
-# -- Project information -----------------------------------------------------
-
-project = 'MinerU'
-copyright = '2024, MinerU Contributors'
-author = 'OpenDataLab'
-
-# The full version, including alpha/beta/rc tags
-version_file = '../../magic_pdf/libs/version.py'
-with open(version_file) as f:
-    exec(compile(f.read(), version_file, 'exec'))
-__version__ = locals()['__version__']
-# The short X.Y version
-version = __version__
-# The full version, including alpha/beta/rc tags
-release = __version__
-
-# -- General configuration ---------------------------------------------------
-
-# Add any Sphinx extension module names here, as strings. They can be
-# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
-# ones.
-extensions = [
-    'sphinx.ext.napoleon',
-    'sphinx.ext.viewcode',
-    'sphinx.ext.intersphinx',
-    'sphinx_copybutton',
-    'sphinx.ext.autodoc',
-    'sphinx.ext.autosummary',
-    'sphinx.ext.inheritance_diagram',
-    'myst_parser',
-    'sphinxarg.ext',
-    'sphinxcontrib.autodoc_pydantic',
-]
-
-# class hierarchy diagram
-inheritance_graph_attrs = dict(rankdir="LR", size='"8.0, 12.0"', fontsize=14, ratio='compress')
-inheritance_node_attrs = dict(shape='ellipse', fontsize=14, height=0.75)
-inheritance_edge_attrs = dict(arrow='vee')
-
-autodoc_pydantic_model_show_json = True
-autodoc_pydantic_model_show_config_summary = False
-
-# Add any paths that contain templates here, relative to this directory.
-templates_path = ['_templates']
-
-# List of patterns, relative to source directory, that match files and
-# directories to ignore when looking for source files.
-# This pattern also affects html_static_path and html_extra_path.
-exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
-
-# Exclude the prompt "$" when copying code
-copybutton_prompt_text = r'\$ '
-copybutton_prompt_is_regexp = True
-
-language = 'zh_CN'
-
-# -- Options for HTML output -------------------------------------------------
-
-# The theme to use for HTML and HTML Help pages.  See the documentation for
-# a list of builtin themes.
-#
-html_theme = 'sphinx_book_theme'
-html_logo = '_static/image/logo.png'
-html_theme_options = {
-    'path_to_docs': 'next_docs/zh_cn',
-    'repository_url': 'https://github.com/opendatalab/MinerU',
-    'use_repository_button': True,
-}
-# Add any paths that contain custom static files (such as style sheets) here,
-# relative to this directory. They are copied after the builtin static files,
-# so a file named "default.css" will overwrite the builtin "default.css".
-# html_static_path = ['_static']
-
-# Mock out external dependencies here.
-autodoc_mock_imports = [
-    'cpuinfo',
-    'torch',
-    'transformers',
-    'psutil',
-    'prometheus_client',
-    'sentencepiece',
-    'vllm.cuda_utils',
-    'vllm._C',
-    'numpy',
-    'tqdm',
-]
-
-
-class MockedClassDocumenter(autodoc.ClassDocumenter):
-    """Remove note about base class when a class is derived from object."""
-
-    def add_line(self, line: str, source: str, *lineno: int) -> None:
-        if line == '   Bases: :py:class:`object`':
-            return
-        super().add_line(line, source, *lineno)
-
-
-autodoc.ClassDocumenter = MockedClassDocumenter
-
-navigation_with_keys = False
-
-
-# add custom directive 
-
-
-class VideoDirective(Directive):
-    required_arguments = 1
-    optional_arguments = 0
-    final_argument_whitespace = True
-    option_spec = {}
-
-    def run(self):
-        url = self.arguments[0]
-        video_node = nodes.raw('', f'<iframe width="560" height="315" src="{url}" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>', format='html')
-        return [video_node]
-
-def setup(app):
-    app.add_directive('video', VideoDirective)
\ No newline at end of file
--- a/next_docs/zh_cn/index.rst
+++ b/next_docs/zh_cn/index.rst
-.. xtuner documentation master file, created by
-   sphinx-quickstart on Tue Jan  9 16:33:06 2024.
-   You can adapt this file completely to your liking, but it should at least
-   contain the root `toctree` directive.
-
-欢迎来到 MinerU 文档库
-==============================================
-
-.. figure:: ./_static/image/logo.png
-  :align: center
-  :alt: mineru
-  :class: no-scaled-link
-
-.. raw:: html
-
-   <p style="text-align:center">
-   <strong> 一站式、高质量的开源文档提取工具
-   </strong>
-   </p>
-
-   <p style="text-align:center">
-   <script async defer src="https://buttons.github.io/buttons.js"></script>
-   <a class="github-button" href="https://github.com/opendatalab/MinerU" data-show-count="true" data-size="large" aria-label="Star">Star</a>
-   <a class="github-button" href="https://github.com/opendatalab/MinerU/subscription" data-icon="octicon-eye" data-size="large" aria-label="Watch">Watch</a>
-   <a class="github-button" href="https://github.com/opendatalab/MinerU/fork" data-icon="octicon-repo-forked" data-size="large" aria-label="Fork">Fork</a>
-   </p>
-
-
-项目介绍
--------------------
-
-MinerU是一款将PDF转化为机器可读格式的工具（如markdown、json），可以很方便地抽取为任意格式。
-MinerU诞生于\ `书生-浦语 <https://github.com/InternLM/InternLM>`__\ 的预训练过程中，我们将会集中精力解决科技文献中的符号转化问题，希望在大模型时代为科技发展做出贡献。
-相比国内外知名商用产品MinerU还很年轻，如果遇到问题或者结果不及预期请到\ `issue <https://github.com/opendatalab/MinerU/issues>`__\ 提交问题，同时\ **附上相关PDF**\ 。
-
-.. video:: https://github.com/user-attachments/assets/4bea02c9-6d54-4cd6-97ed-dff14340982c
-
-主要功能
--------
-
-  删除页眉、页脚、脚注、页码等元素，确保语义连贯
-  输出符合人类阅读顺序的文本，适用于单栏、多栏及复杂排版
-  保留原文档的结构，包括标题、段落、列表等
-  提取图像、图片描述、表格、表格标题及脚注
-  自动识别并转换文档中的公式为LaTeX格式
-  自动识别并转换文档中的表格为LaTeX或HTML格式
-  自动检测扫描版PDF和乱码PDF，并启用OCR功能
-  OCR支持84种语言的检测与识别
-  支持多种输出格式，如多模态与NLP的Markdown、按阅读顺序排序的JSON、含有丰富信息的中间格式等
-  支持多种可视化结果，包括layout可视化、span可视化等，便于高效确认输出效果与质检
-  支持CPU和GPU环境
-  兼容Windows、Linux和Mac平台
-
-
-用户指南
-------------
-.. toctree::
-   :maxdepth: 2
-   :caption: 用户指南
-
-   user_guide
-
-
-API 接口
-------------
-本章节主要介绍函数、类、类方法的细节信息
-
-目前只提供英文版本的接口文档，请切换到英文版本的接口文档！
-
-
-附录
------------------
-.. toctree::
-   :maxdepth: 1
-   :caption: 附录
-
-   additional_notes/known_issues
-   additional_notes/faq
-   additional_notes/glossary
-
-
--- a/next_docs/zh_cn/make.bat
+++ b/next_docs/zh_cn/make.bat
-@ECHO OFF
-
-pushd %~dp0
-
-REM Command file for Sphinx documentation
-
-if "%SPHINXBUILD%" == "" (
-	set SPHINXBUILD=sphinx-build
-)
-set SOURCEDIR=.
-set BUILDDIR=_build
-
-%SPHINXBUILD% >NUL 2>NUL
-if errorlevel 9009 (
-	echo.
-	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
-	echo.installed, then set the SPHINXBUILD environment variable to point
-	echo.to the full path of the 'sphinx-build' executable. Alternatively you
-	echo.may add the Sphinx directory to PATH.
-	echo.
-	echo.If you don't have Sphinx installed, grab it from
-	echo.https://www.sphinx-doc.org/
-	exit /b 1
-)
-
-if "%1" == "" goto help
-
-%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
-goto end
-
-:help
-%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
-
-:end
-popd
--- a/next_docs/zh_cn/user_guide.rst
+++ b/next_docs/zh_cn/user_guide.rst
-
-
-.. toctree::
-    :maxdepth: 2
-
-    user_guide/install
-    user_guide/quick_start
-    user_guide/tutorial
-    user_guide/data
-    
--- a/next_docs/zh_cn/user_guide/data.rst
+++ b/next_docs/zh_cn/user_guide/data.rst
-
-
-数据
-=========
-
-.. toctree::
-   :maxdepth: 2
-   :caption: 数据
-
-   data/dataset
-
-   data/read_api
-
-   data/data_reader_writer 
-
-   data/io
-
-
-
-
--- a/next_docs/zh_cn/user_guide/data/data_reader_writer.rst
+++ b/next_docs/zh_cn/user_guide/data/data_reader_writer.rst
-
-数据读取和写入类 
-=================
-
-旨在从不同的媒介读取或写入字节。如果 MinerU 没有提供合适的类，你可以实现新的类以满足个人场景的需求。实现新的类非常容易，唯一的要求是继承自 DataReader 或 DataWriter。
-
-.. code:: python
-
-    class SomeReader(DataReader):
-        def read(self, path: str) -> bytes:
-            pass
-
-        def read_at(self, path: str, offset: int = 0, limit: int = -1) -> bytes:
-            pass
-
-
-    class SomeWriter(DataWriter):
-        def write(self, path: str, data: bytes) -> None:
-            pass
-
-        def write_string(self, path: str, data: str) -> None:
-            pass
-
-读者可能会对 io 和本节的区别感到好奇。乍一看，这两部分非常相似。io 提供基本功能，而本节则更注重应用层面。用户可以构建自己的类以满足特定应用需求，这些类可能共享相同的基本 IO 功能。这就是为什么我们有 io。
-
-重要类
------------
-.. code:: python
-
-    class FileBasedDataReader(DataReader):
-        def __init__(self, parent_dir: str = ''):
-            pass
-
-
-    class FileBasedDataWriter(DataWriter):
-        def __init__(self, parent_dir: str = '') -> None:
-            pass
-
-类 FileBasedDataReader 使用单个参数 parent_dir 初始化。这意味着 FileBasedDataReader 提供的每个方法将具有以下特性：
-
-#. 从绝对路径文件读取内容，parent_dir 将被忽略。
-#. 从相对路径读取文件，首先将路径与 parent_dir 连接，然后从合并后的路径读取内容。
-
-.. note::
-
-    `FileBasedDataWriter` 与 `FileBasedDataReader` 具有相同的行为。
-
-.. code:: python
-
-    class MultiS3Mixin:
-        def __init__(self, default_prefix: str, s3_configs: list[S3Config]):
-            pass
-
-    class MultiBucketS3DataReader(DataReader, MultiS3Mixin):
-        pass
-
-MultiBucketS3DataReader 提供的所有读取相关方法将具有以下特性：
-
-#. 从完整的 S3 格式路径读取对象，例如 s3://test_bucket/test_object，default_prefix 将被忽略。
-#. 从相对路径读取对象，首先将路径与 default_prefix 连接并去掉 bucket_name，然后读取内容。bucket_name 是将 default_prefix 用分隔符 \ 分割后的第一个元素。
-
-.. note::
-    MultiBucketS3DataWriter 与 MultiBucketS3DataReader 具有类似的行为。
-
-.. code:: python
-
-    class S3DataReader(MultiBucketS3DataReader):
-        pass
-
-S3DataReader 基于 MultiBucketS3DataReader 构建，但仅支持单个桶。S3DataWriter 也是类似的情况。
-
-读取示例
---------
-.. code:: python
-
-    import os 
-    from magic_pdf.data.data_reader_writer import *
-    from magic_pdf.data.data_reader_writer import MultiBucketS3DataReader
-    from magic_pdf.data.schemas import S3Config
-
-    # 初始化 reader
-    file_based_reader1 = FileBasedDataReader('')
-
-    ## 读本地文件 abc
-    file_based_reader1.read('abc')
-
-    file_based_reader2 = FileBasedDataReader('/tmp')
-
-    ## 读本地文件 /tmp/abc
-    file_based_reader2.read('abc')
-
-    ## 读本地文件 /tmp/logs/message.txt
-    file_based_reader2.read('/tmp/logs/message.txt')
-
-    # 初始化多桶 s3 reader
-    bucket = "bucket"               # 替换为有效的 bucket
-    ak = "ak"                       # 替换为有效的 access key
-    sk = "sk"                       # 替换为有效的 secret key
-    endpoint_url = "endpoint_url"   # 替换为有效的 endpoint_url
-
-    bucket_2 = "bucket_2"               # 替换为有效的 bucket
-    ak_2 = "ak_2"                       # 替换为有效的 access key
-    sk_2 = "sk_2"                       # 替换为有效的 secret key 
-    endpoint_url_2 = "endpoint_url_2"   # 替换为有效的 endpoint_url
-
-    test_prefix = 'test/unittest'
-    multi_bucket_s3_reader1 = MultiBucketS3DataReader(f"{bucket}/{test_prefix}", [S3Config(
-            bucket_name=bucket, access_key=ak, secret_key=sk, endpoint_url=endpoint_url
-        ),
-        S3Config(
-            bucket_name=bucket_2,
-            access_key=ak_2,
-            secret_key=sk_2,
-            endpoint_url=endpoint_url_2,
-        )])
-
-    ## 读文件 s3://{bucket}/{test_prefix}/abc
-    multi_bucket_s3_reader1.read('abc')
-
-    ## 读文件 s3://{bucket}/{test_prefix}/efg
-    multi_bucket_s3_reader1.read(f's3://{bucket}/{test_prefix}/efg')
-
-    ## 读文件 s3://{bucket2}/{test_prefix}/abc
-    multi_bucket_s3_reader1.read(f's3://{bucket_2}/{test_prefix}/abc')
-
-    # 初始化 s3 reader
-    s3_reader1 = S3DataReader(
-        test_prefix,
-        bucket,
-        ak,
-        sk,
-        endpoint_url
-    )
-
-    ## 读文件 s3://{bucket}/{test_prefix}/abc
-    s3_reader1.read('abc')
-
-    ## 读文件 s3://{bucket}/efg
-    s3_reader1.read(f's3://{bucket}/efg')
-
-
-写入示例
----------
-.. code:: python
-
-    import os
-    from magic_pdf.data.data_reader_writer import *
-    from magic_pdf.data.data_reader_writer import MultiBucketS3DataWriter
-    from magic_pdf.data.schemas import S3Config
-
-    # 初始化 reader
-    file_based_writer1 = FileBasedDataWriter("")
-
-    ## 写数据 123 to abc
-    file_based_writer1.write("abc", "123".encode())
-
-    ## 写数据 123 to abc
-    file_based_writer1.write_string("abc", "123")
-
-    file_based_writer2 = FileBasedDataWriter("/tmp")
-
-    ## 写数据 123 to /tmp/abc
-    file_based_writer2.write_string("abc", "123")
-
-    ## 写数据 123 to /tmp/logs/message.txt
-    file_based_writer2.write_string("/tmp/logs/message.txt", "123")
-
-    # 初始化多桶 s3 writer
-    bucket = "bucket"               # 替换为有效的 bucket
-    ak = "ak"                       # 替换为有效的 access key
-    sk = "sk"                       # 替换为有效的 secret key
-    endpoint_url = "endpoint_url"   # 替换为有效的 endpoint_url
-
-    bucket_2 = "bucket_2"               # 替换为有效的 bucket
-    ak_2 = "ak_2"                       # 替换为有效的 access key
-    sk_2 = "sk_2"                       # 替换为有效的 secret key 
-    endpoint_url_2 = "endpoint_url_2"   # 替换为有效的 endpoint_url
-
-    test_prefix = "test/unittest"
-    multi_bucket_s3_writer1 = MultiBucketS3DataWriter(
-        f"{bucket}/{test_prefix}",
-        [
-            S3Config(
-                bucket_name=bucket, access_key=ak, secret_key=sk, endpoint_url=endpoint_url
-            ),
-            S3Config(
-                bucket_name=bucket_2,
-                access_key=ak_2,
-                secret_key=sk_2,
-                endpoint_url=endpoint_url_2,
-            ),
-        ],
-    )
-
-    ## 写数据 123 to s3://{bucket}/{test_prefix}/abc
-    multi_bucket_s3_writer1.write_string("abc", "123")
-
-    ## 写数据 123 to s3://{bucket}/{test_prefix}/abc
-    multi_bucket_s3_writer1.write("abc", "123".encode())
-
-    ## 写数据 123 to s3://{bucket}/{test_prefix}/efg
-    multi_bucket_s3_writer1.write(f"s3://{bucket}/{test_prefix}/efg", "123".encode())
-
-    ## 写数据 123 to s3://{bucket_2}/{test_prefix}/abc
-    multi_bucket_s3_writer1.write(f's3://{bucket_2}/{test_prefix}/abc', '123'.encode())
-
-    # 初始化 s3 writer
-    s3_writer1 = S3DataWriter(test_prefix, bucket, ak, sk, endpoint_url)
-
-    ## 写数据 123 to s3://{bucket}/{test_prefix}/abc
-    s3_writer1.write("abc", "123".encode())
-
-    ## 写数据 123 to s3://{bucket}/{test_prefix}/abc
-    s3_writer1.write_string("abc", "123")
-
-    ## 写数据 123 to s3://{bucket}/efg
-    s3_writer1.write(f"s3://{bucket}/efg", "123".encode())
-
--- a/next_docs/zh_cn/user_guide/data/dataset.rst
+++ b/next_docs/zh_cn/user_guide/data/dataset.rst
-
-数据集
-======
-
-导入数据类
-----------
-
-数据集
-^^^^^^^^
-
-每个 PDF 或图像将形成一个 Dataset。众所周知，PDF 有两种类别：:ref:`TXT <digital_method_section>` 或 :ref:`OCR <ocr_method_section>` 方法部分。从图像中可以获得 ImageDataset，它是 Dataset 的子类；从 PDF 文件中可以获得 PymuDocDataset。ImageDataset 和 PymuDocDataset 之间的区别在于 ImageDataset 仅支持 OCR 解析方法，而 PymuDocDataset 支持 OCR 和 TXT 两种方法。
-
-.. note::
-
-    实际上，有些 PDF 可能是由图像生成的，这意味着它们不支持 `TXT` 方法。目前，由用户保证不会调用 `TXT` 方法来解析图像生成的 PDF
-
-PDF 解析方法
---------------
-
-.. _ocr_method_section:
-
-OCR
-^^^^
-通过 光学字符识别 技术提取字符。
-
-.. _digital_method_section:
-
-TXT
-^^^^^^^^
-通过第三方库提取字符，目前我们使用的是 pymupdf。
-
--- a/next_docs/zh_cn/user_guide/data/io.rst
+++ b/next_docs/zh_cn/user_guide/data/io.rst
-
-
-IO
-====
-
-旨在从不同的媒介读取或写入字节。目前，我们提供了 S3Reader 和 S3Writer 用于兼容 AWS S3 的媒介，以及 HttpReader 和 HttpWriter 用于远程 HTTP 文件。如果 MinerU 没有提供合适的类，你可以实现新的类以满足个人场景的需求。实现新的类非常容易，唯一的要求是继承自 IOReader 或 IOWriter。
-
-.. code:: python
-
-    class SomeReader(IOReader):
-        def read(self, path: str) -> bytes:
-            pass
-
-        def read_at(self, path: str, offset: int = 0, limit: int = -1) -> bytes:
-            pass
-
-
-    class SomeWriter(IOWriter):
-        def write(self, path: str, data: bytes) -> None:
-            pass
-        
--- a/next_docs/zh_cn/user_guide/data/read_api.rst
+++ b/next_docs/zh_cn/user_guide/data/read_api.rst
-
-
-read_api
-=========
-
-从文件或目录读取内容以创建 Dataset。目前，我们提供了几个覆盖某些场景的函数。如果你有新的、大多数用户都会遇到的场景，可以在官方 GitHub 问题页面上发布详细描述。同时，实现你自己的读取相关函数也非常容易。
-
-重要函数
---------
-
-read_jsonl
-^^^^^^^^^^^^^^^^
-
-从本地机器或远程 S3 上的 JSONL 文件读取内容。如果你想了解更多关于 JSONL 的信息，请参阅 :doc:`../../additional_notes/glossary`。
-
-.. code:: python
-
-    from magic_pdf.data.read_api import *
-    from magic_pdf.data.data_reader_writer import MultiBucketS3DataReader
-    from magic_pdf.data.schemas import S3Config
-
-    # 读取本地 jsonl 文件
-    datasets = read_jsonl("tt.jsonl", None)   # 替换为有效的文件
-
-    # 读取 s3 jsonl 文件
-
-    bucket = "bucket_1"                     # 替换为有效的 s3 bucket
-    ak = "access_key_1"                     # 替换为有效的 s3 access key
-    sk = "secret_key_1"                     # 替换为有效的 s3 secret key
-    endpoint_url = "endpoint_url_1"         # 替换为有效的 s3 endpoint url
-
-    bucket_2 = "bucket_2"                   # 替换为有效的 s3 bucket
-    ak_2 = "access_key_2"                   # 替换为有效的 s3 access key
-    sk_2 = "secret_key_2"                   # 替换为有效的 s3 secret key
-    endpoint_url_2 = "endpoint_url_2"       # 替换为有效的 s3 endpoint url
-
-    s3configs = [
-        S3Config(
-            bucket_name=bucket, access_key=ak, secret_key=sk, endpoint_url=endpoint_url
-        ),
-        S3Config(
-            bucket_name=bucket_2,
-            access_key=ak_2,
-            secret_key=sk_2,
-            endpoint_url=endpoint_url_2,
-        ),
-    ]
-
-    s3_reader = MultiBucketS3DataReader(bucket, s3configs)
-
-    datasets = read_jsonl(f"s3://bucket_1/tt.jsonl", s3_reader)  # 替换为有效的 s3 jsonl file
-
-
-read_local_pdfs
-^^^^^^^^^^^^^^^^
-
-从路径或目录读取 PDF 文件。
-
-.. code:: python
-
-    from magic_pdf.data.read_api import *
-
-    # 读取 PDF 路径
-    datasets = read_local_pdfs("tt.pdf")  # 替换为有效的文件
-
-    # 读取目录下的 PDF 文件
-    datasets = read_local_pdfs("pdfs/")   # 替换为有效的文件目录
-
-read_local_images
-^^^^^^^^^^^^^^^^^^^
-
-从路径或目录读取图像。
-
-.. code:: python
-
-    from magic_pdf.data.read_api import *
-
-    # 从图像路径读取
-    datasets = read_local_images("tt.png")  # 替换为有效的文件
-
-    # 从目录读取以 suffixes 数组中指定后缀结尾的文件
-    datasets = read_local_images("images/", suffixes=["png", "jpg"])  # 替换为有效的文件目录