docs: remove outdated documentation files

- Deleted .readthedocs.yaml files from multiple directories - Removed outdated API and user guide documentation files - Deleted command line usage examples - Removed CUDA acceleration guide

docs: remove outdated documentation files
- Deleted .readthedocs.yaml files from multiple directories - Removed outdated API and user guide documentation files - Deleted command line usage examples - Removed CUDA acceleration guide
cf5c8f47 · myhloli · cb57e84c · cb57e84c · cb57e84c · cb57e84c
Commit cf5c8f47 authored Jun 13, 2025 by myhloli
20 changed files
--- a/next_docs/en/user_guide/usage/api.rst
+++ b/next_docs/en/user_guide/usage/api.rst
-
-Api Usage
-===========
-
-
-PDF
----
-
-Local File Example
-^^^^^^^^^^^^^^^^^^
-
-.. code:: python
-
-    import os
-
-    from magic_pdf.data.data_reader_writer import FileBasedDataWriter, FileBasedDataReader
-    from magic_pdf.data.dataset import PymuDocDataset
-    from magic_pdf.model.doc_analyze_by_custom_model import doc_analyze
-    from magic_pdf.config.enums import SupportedPdfParseMethod
-
-    # args
-    pdf_file_name = "abc.pdf"  # replace with the real pdf path
-    name_without_suff = pdf_file_name.split(".")[0]
-
-    # prepare env
-    local_image_dir, local_md_dir = "output/images", "output"
-    image_dir = str(os.path.basename(local_image_dir))
-
-    os.makedirs(local_image_dir, exist_ok=True)
-
-    image_writer, md_writer = FileBasedDataWriter(local_image_dir), FileBasedDataWriter(
-        local_md_dir
-    )
-
-    # read bytes
-    reader1 = FileBasedDataReader("")
-    pdf_bytes = reader1.read(pdf_file_name)  # read the pdf content
-
-    # proc
-    ## Create Dataset Instance
-    ds = PymuDocDataset(pdf_bytes)
-
-    ## inference
-    if ds.classify() == SupportedPdfParseMethod.OCR:
-        infer_result = ds.apply(doc_analyze, ocr=True)
-
-        ## pipeline
-        pipe_result = infer_result.pipe_ocr_mode(image_writer)
-
-    else:
-        infer_result = ds.apply(doc_analyze, ocr=False)
-
-        ## pipeline
-        pipe_result = infer_result.pipe_txt_mode(image_writer)
-
-    ### draw model result on each page
-    infer_result.draw_model(os.path.join(local_md_dir, f"{name_without_suff}_model.pdf"))
-
-    ### get model inference result
-    model_inference_result = infer_result.get_infer_res()
-
-    ### draw layout result on each page
-    pipe_result.draw_layout(os.path.join(local_md_dir, f"{name_without_suff}_layout.pdf"))
-
-    ### draw spans result on each page
-    pipe_result.draw_span(os.path.join(local_md_dir, f"{name_without_suff}_spans.pdf"))
-
-    ### get markdown content
-    md_content = pipe_result.get_markdown(image_dir)
-
-    ### dump markdown
-    pipe_result.dump_md(md_writer, f"{name_without_suff}.md", image_dir)
-
-    ### get content list content
-    content_list_content = pipe_result.get_content_list(image_dir)
-
-    ### dump content list
-    pipe_result.dump_content_list(md_writer, f"{name_without_suff}_content_list.json", image_dir)
-
-    ### get middle json
-    middle_json_content = pipe_result.get_middle_json()
-
-    ### dump middle json
-    pipe_result.dump_middle_json(md_writer, f'{name_without_suff}_middle.json')
-
-
-
-S3 File Example
-^^^^^^^^^^^^^^^^
-
-.. code:: python
-
-    import os
-
-    from magic_pdf.data.data_reader_writer import S3DataReader, S3DataWriter
-    from magic_pdf.data.dataset import PymuDocDataset
-    from magic_pdf.model.doc_analyze_by_custom_model import doc_analyze
-    from magic_pdf.config.enums import SupportedPdfParseMethod
-
-    bucket_name = "{Your S3 Bucket Name}"  # replace with real bucket name
-    ak = "{Your S3 access key}"  # replace with real s3 access key
-    sk = "{Your S3 secret key}"  # replace with real s3 secret key
-    endpoint_url = "{Your S3 endpoint_url}"  # replace with real s3 endpoint_url
-
-    reader = S3DataReader('unittest/tmp/', bucket_name, ak, sk, endpoint_url)  # replace `unittest/tmp` with the real s3 prefix
-    writer = S3DataWriter('unittest/tmp', bucket_name, ak, sk, endpoint_url)
-    image_writer = S3DataWriter('unittest/tmp/images', bucket_name, ak, sk, endpoint_url)
-    md_writer = S3DataWriter('unittest/tmp', bucket_name, ak, sk, endpoint_url)
-
-    local_image_dir, local_md_dir = "output/images", "output"
-    image_dir = str(os.path.basename(local_image_dir))
-
-    # args
-    pdf_file_name = (
-        f"s3://{bucket_name}/unittest/tmp/bug5-11.pdf"  # replace with the real s3 path
-    )
-
-    # prepare env
-    local_dir = "output"
-    name_without_suff = os.path.basename(pdf_file_name).split(".")[0]
-
-    # read bytes
-    pdf_bytes = reader.read(pdf_file_name)  # read the pdf content
-
-    # proc
-    ## Create Dataset Instance
-    ds = PymuDocDataset(pdf_bytes)
-
-    ## inference
-    if ds.classify() == SupportedPdfParseMethod.OCR:
-        infer_result = ds.apply(doc_analyze, ocr=True)
-
-        ## pipeline
-        pipe_result = infer_result.pipe_ocr_mode(image_writer)
-
-    else:
-        infer_result = ds.apply(doc_analyze, ocr=False)
-
-        ## pipeline
-        pipe_result = infer_result.pipe_txt_mode(image_writer)
-
-    ### draw model result on each page
-    infer_result.draw_model(os.path.join(local_md_dir, f"{name_without_suff}_model.pdf"))
-
-    ### get model inference result
-    model_inference_result = infer_result.get_infer_res()
-
-    ### draw layout result on each page
-    pipe_result.draw_layout(os.path.join(local_md_dir, f"{name_without_suff}_layout.pdf"))
-
-    ### draw spans result on each page
-    pipe_result.draw_span(os.path.join(local_md_dir, f"{name_without_suff}_spans.pdf"))
-
-    ### dump markdown
-    pipe_result.dump_md(md_writer, f"{name_without_suff}.md", image_dir)
-
-    ### dump content list
-    pipe_result.dump_content_list(md_writer, f"{name_without_suff}_content_list.json", image_dir)
-
-    ### get markdown content
-    md_content = pipe_result.get_markdown(image_dir)
-
-    ### get content list content
-    content_list_content = pipe_result.get_content_list(image_dir)
-
-    ### get middle json
-    middle_json_content = pipe_result.get_middle_json()
-
-    ### dump middle json
-    pipe_result.dump_middle_json(md_writer, f'{name_without_suff}_middle.json')
-
-MS-Office
----------
-
-.. code:: python
-
-    import os
-
-    from magic_pdf.data.data_reader_writer import FileBasedDataWriter, FileBasedDataReader
-    from magic_pdf.model.doc_analyze_by_custom_model import doc_analyze
-    from magic_pdf.data.read_api import read_local_office
-
-    # prepare env
-    local_image_dir, local_md_dir = "output/images", "output"
-    image_dir = str(os.path.basename(local_image_dir))
-
-    os.makedirs(local_image_dir, exist_ok=True)
-
-    image_writer, md_writer = FileBasedDataWriter(local_image_dir), FileBasedDataWriter(
-        local_md_dir
-    )
-
-    # proc
-    ## Create Dataset Instance
-    input_file = "some_ppt.ppt"     # replace with real ms-office file
-
-    input_file_name = input_file.split(".")[0]
-    ds = read_local_office(input_file)[0]
-
-    ds.apply(doc_analyze, ocr=True).pipe_txt_mode(image_writer).dump_md(
-        md_writer, f"{input_file_name}.md", image_dir
-    )
-
-This code snippet can be used to manipulate **ppt**, **pptx**, **doc**, **docx** file
-
-
-Image
---------
-
-Single Image File
-^^^^^^^^^^^^^^^^^^^
-
-.. code:: python
-
-    import os
-
-    from magic_pdf.data.data_reader_writer import FileBasedDataWriter
-    from magic_pdf.model.doc_analyze_by_custom_model import doc_analyze
-    from magic_pdf.data.read_api import read_local_images
-
-    # prepare env
-    local_image_dir, local_md_dir = "output/images", "output"
-    image_dir = str(os.path.basename(local_image_dir))
-
-    os.makedirs(local_image_dir, exist_ok=True)
-
-    image_writer, md_writer = FileBasedDataWriter(local_image_dir), FileBasedDataWriter(
-        local_md_dir
-    )
-
-    # proc
-    ## Create Dataset Instance
-    input_file = "some_image.jpg"       # replace with real image file
-
-    input_file_name = input_file.split(".")[0]
-    ds = read_local_images(input_file)[0]
-
-    ds.apply(doc_analyze, ocr=True).pipe_ocr_mode(image_writer).dump_md(
-        md_writer, f"{input_file_name}.md", image_dir
-    )
-
-
-Directory That Contains Images
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-.. code:: python
-
-    import os
-
-    from magic_pdf.data.data_reader_writer import FileBasedDataWriter
-    from magic_pdf.model.doc_analyze_by_custom_model import doc_analyze
-    from magic_pdf.data.read_api import read_local_images
-
-    # prepare env
-    local_image_dir, local_md_dir = "output/images", "output"
-    image_dir = str(os.path.basename(local_image_dir))
-
-    os.makedirs(local_image_dir, exist_ok=True)
-
-    image_writer, md_writer = FileBasedDataWriter(local_image_dir), FileBasedDataWriter(
-        local_md_dir
-    )
-
-    # proc
-    ## Create Dataset Instance
-    input_directory = "some_image_dir/"       # replace with real directory that contains images
-
-
-    dss = read_local_images(input_directory, suffixes=['.png', '.jpg'])
-
-    count = 0
-    for ds in dss:
-        ds.apply(doc_analyze, ocr=True).pipe_ocr_mode(image_writer).dump_md(
-            md_writer, f"{count}.md", image_dir
-        )
-        count += 1
-
-
-Check :doc:`../data/data_reader_writer` for more [reader | writer] examples and check :doc:`../../api/pipe_operators` or :doc:`../../api/model_operators` for api details
--- a/next_docs/en/user_guide/usage/command_line.rst
+++ b/next_docs/en/user_guide/usage/command_line.rst
-
-
-Command Line
-===================
-
-.. code:: bash
-
-   magic-pdf --help
-   Usage: magic-pdf [OPTIONS]
-
-   Options:
-     -v, --version                display the version and exit
-     -p, --path PATH              local filepath or directory. support PDF, PPT,
-                                  PPTX, DOC, DOCX, PNG, JPG files  [required]
-     -o, --output-dir PATH        output local directory  [required]
-     -m, --method [ocr|txt|auto]  the method for parsing pdf. ocr: using ocr
-                                  technique to extract information from pdf. txt:
-                                  suitable for the text-based pdf only and
-                                  outperform ocr. auto: automatically choose the
-                                  best method for parsing pdf from ocr and txt.
-                                  without method specified, auto will be used by
-                                  default.
-     -l, --lang TEXT              Input the languages in the pdf (if known) to
-                                  improve OCR accuracy.  Optional. You should
-                                  input "Abbreviation" with language form url: ht
-                                  tps://paddlepaddle.github.io/PaddleOCR/en/ppocr
-                                  /blog/multi_languages.html#5-support-languages-
-                                  and-abbreviations
-     -d, --debug BOOLEAN          Enables detailed debugging information during
-                                  the execution of the CLI commands.
-     -s, --start INTEGER          The starting page for PDF parsing, beginning
-                                  from 0.
-     -e, --end INTEGER            The ending page for PDF parsing, beginning from
-                                  0.
-     --help                       Show this message and exit.
-
-
-   ## show version
-   magic-pdf -v
-
-   ## command line example
-   magic-pdf -p {some_pdf} -o {some_output_dir} -m auto
-
-
-.. admonition:: Important
-    :class: tip
-
-    The file must endswith with the following suffix.
-       .pdf 
-       .png
-       .jpg
-       .ppt
-       .pptx
-       .doc
-       .docx
-
-
-``{some_pdf}`` can be a single PDF file or a directory containing
-multiple PDFs. The results will be saved in the ``{some_output_dir}``
-directory. The output file list is as follows:
-
-.. code:: text
-
-   ├── some_pdf.md                          # markdown file
-   ├── images                               # directory for storing images
-   ├── some_pdf_layout.pdf                  # layout diagram
-   ├── some_pdf_middle.json                 # MinerU intermediate processing result
-   ├── some_pdf_model.json                  # model inference result
-   ├── some_pdf_origin.pdf                  # original PDF file
-   ├── some_pdf_spans.pdf                   # smallest granularity bbox position information diagram
-   └── some_pdf_content_list.json           # Rich text JSON arranged in reading order
-
-.. admonition:: Tip
-   :class: tip
-   
-
-   For more information about the output files, please refer to the :doc:`../inference_result` or :doc:`../pipe_result`
--- a/next_docs/en/user_guide/usage/docker.rst
+++ b/next_docs/en/user_guide/usage/docker.rst
-
-
-Docker 
-=======
-
-.. admonition:: Important
-   :class: tip
-
-   Docker requires a GPU with at least 16GB of VRAM, and all acceleration features are enabled by default.
-
-   Before running this Docker, you can use the following command to check if your device supports CUDA acceleration on Docker. 
-
-   .. code-block:: bash
-
-      bash  docker run --rm --gpus=all nvidia/cuda:12.1.0-base-ubuntu22.04 nvidia-smi
-
-
-.. code:: sh
-
-   wget https://github.com/opendatalab/MinerU/raw/master/Dockerfile
-   docker build -t mineru:latest .
-   docker run --rm -it --gpus=all mineru:latest /bin/bash
-   magic-pdf --help
-
--- a/next_docs/requirements.txt
+++ b/next_docs/requirements.txt
-numpy==1.26.4
-click==8.1.7
-fast-langdetect==0.2.2
-Brotli==1.1.0
-boto3>=1.28.43
-loguru>=0.6.0
-myst-parser
-Pillow==8.4.0
-pydantic>=2.7.2,<2.8.0
-PyMuPDF>=1.24.9
-pdfminer.six==20231228
-sphinx
-sphinx-argparse>=0.5.2
-sphinx-book-theme>=1.1.3
-sphinx-copybutton>=0.5.2
-sphinx_rtd_theme>=3.0.1
-autodoc_pydantic>=2.2.0
--- a/next_docs/zh_cn/.readthedocs.yaml
+++ b/next_docs/zh_cn/.readthedocs.yaml
-version: 2
-
-build:
-  os: ubuntu-22.04
-  tools:
-    python: "3.10"
-
-formats:
-  - epub
-
-python:
-  install:
-    - requirements: next_docs/requirements.txt
-
-sphinx:
-  configuration: next_docs/zh_cn/conf.py
--- a/next_docs/zh_cn/Makefile
+++ b/next_docs/zh_cn/Makefile
-# Minimal makefile for Sphinx documentation
-#
-
-# You can set these variables from the command line, and also
-# from the environment for the first two.
-SPHINXOPTS    ?=
-SPHINXBUILD   ?= sphinx-build
-SOURCEDIR     = .
-BUILDDIR      = _build
-
-# Put it first so that "make" without argument is like "make help".
-help:
-	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
-
-.PHONY: help Makefile
-
-# Catch-all target: route all unknown targets to Sphinx using the new
-# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
-%: Makefile
-	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
--- a/next_docs/zh_cn/_static/image/MinerU-logo-hq.png
+++ b/next_docs/zh_cn/_static/image/MinerU-logo-hq.png
--- a/next_docs/zh_cn/_static/image/MinerU-logo.png
+++ b/next_docs/zh_cn/_static/image/MinerU-logo.png
--- a/next_docs/zh_cn/_static/image/ReadTheDocs.svg
+++ b/next_docs/zh_cn/_static/image/ReadTheDocs.svg
-<?xml version="1.0" encoding="UTF-8" standalone="no" ?>
-<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
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line-height: 1.2; pointer-events: all; white-space: normal; overflow-wrap: normal;">Dataset</div></div></div></foreignObject><image x="159" y="53.5" width="118" height="17" 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"/></switch></g></g></g><g 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