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docling-convert文档转换

Agent Skill

docling-convert 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

272

周安装

11

GitHub Stars

1

下载量

85
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:docling-convert(文档转换)
来源仓库:https://github.com/mhliulgy/my-skills
仓库路径:skills/docling-convert
安装命令:
npx skills add https://github.com/mhliulgy/my-skills --skill docling-convert
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/mhliulgy/my-skills --skill docling-convert

简介

通过本地 Docling 服务执行批量文档转换。

  • 封装 Gradio API 调用和归档提取流程。
  • 支持重复性工作脚本化执行。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。
  • 需预先部署本地服务并配置访问地址。
  • docling-convert 属于前端设计类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Docling Convert

Use this skill to run document conversion through a local Docling service instead of ad-hoc parsing.

Quick Start

  • Assume the Docling service is already deployed locally and reachable at http://localhost:5001.
  • Prefer scripts/docling_gradio_convert.py for repeatable work. It wraps the documented Gradio API and handles submission, waiting, and archive extraction.
  • Install the required client before running the script:
pip install gradio_client
  • If URL jobs need placeholder image repair and beautifulsoup4 is missing, install it:
pip install beautifulsoup4 lxml
  • Read references/gradio-api-workflow.md only when changing endpoints, tuning advanced options, or debugging output layouts.

Workflow

  1. Classify the inputs. Use the file flow for local paths and the URL flow for web pages. Do not mix files and URLs in one API request; if the user gives both, run two jobs.
  2. Choose the outputs. Default to md. Add json when the user also needs structured output. Add html, text, or doctags only when the task explicitly needs them.
  3. Choose the processing options. Keep pipeline=standard, ocr=true, force_ocr=false, pdf_backend=dlparse_v4, and table_mode=accurate unless the task calls for a change. Keep image_export_mode=embedded when the goal is to preserve extracted images. The wrapper post-processes embedded Markdown images into real files under images/. Turn on enrichment flags only when the user explicitly wants code, formulas, picture classification, or picture descriptions. For URL jobs, the wrapper also normalizes Markdown output by injecting stable front matter, preserving unknown existing front matter keys, and prepending # title only when the document body does not already start with that title.
  4. Run the wrapper script.
# Single file
python scripts/docling_gradio_convert.py report.pdf

# Batch files with Markdown + JSON
python scripts/docling_gradio_convert.py "*.pdf" --to-format md --to-format json

# Single URL
python scripts/docling_gradio_convert.py https://example.com/article --output-dir ./article

# Single URL with optional sidecar files
python scripts/docling_gradio_convert.py https://example.com/article --save-source-html --save-manifest

# Alternate service URL
python scripts/docling_gradio_convert.py slides.pptx --service-url http://localhost:5001
  1. Verify the extracted results. The script always requests return_as_file=true, downloads the returned artifact, extracts it into the chosen output directory, rewrites embedded Markdown images into local files when needed, and for URL conversions can backfill Docling image placeholders from the source page. URL Markdown outputs are post-processed after extraction so the final .md contains normalized front matter plus a title heading when needed. Inspect the produced Markdown plus any extracted image assets before presenting the result to the user.

Output Conventions

  • Prefer the script defaults unless the user asks for a different layout.
  • For a single local file, extract into a sibling directory named after the input stem.
  • For a single URL, extract into docling-<slug> under the current working directory.
  • For multiple inputs, extract into docling-files-batch or docling-urls-batch under the current working directory, unless --output-dir is supplied.
  • If the user supplies --output-dir and both file and URL jobs are needed, the script creates files/ and urls/ subdirectories to keep the results separate.

Script Notes

  • Use scripts/docling_gradio_convert.py --dry-run... to verify grouping, endpoint selection, and destination paths without contacting the service.
  • Let the script infer the Gradio UI URL from the service root. http://localhost:5001 becomes http://localhost:5001/ui/.
  • Let the script ask /change_ocr_lang for the default OCR language set when --ocr-lang is not provided. Fall back to en,fr,de,es if the endpoint is unavailable.
  • Treat a missing gradio_client installation as an environment issue and fix it with pip install gradio_client instead of rewriting the workflow.
  • If a URL conversion returns <!-- 🖼️❌ Image not available... -->, let the wrapper fetch the source page, collect article images, download them into images/, and replace placeholders in order.
  • URL post-processing fetches the source page once and reuses that HTML for metadata extraction, title normalization, and optional sidecar output instead of maintaining a separate capture flow.
  • Existing front matter keys outside the managed set are preserved; managed keys are url, title, description, author, published, cover_image, language, captured_at, converter, pipeline, ocr, and ocr_lang.
  • Use --save-source-html to write source.html for single URL jobs, and --save-manifest to write manifest.json with the conversion settings and output summary.
  • Sidecar files are skipped for multi-URL batch jobs even if the flags are set.

Resources

scripts/docling_gradio_convert.py

Use this wrapper for deterministic Docling conversions. It supports:

  • local files, URLs, and wildcard expansion
  • batch conversion
  • OCR and enrichment flags
  • archive download and extraction
  • output directory planning
  • dry-run validation

references/gradio-api-workflow.md

Read this reference when you need:

  • the endpoint mapping for file versus URL jobs
  • the argument names expected by the Gradio client
  • the wait_task_finish tuple layout
  • the defaults adopted by this skill

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.14%
按下载量换算32

Claude

29.1%
按下载量换算25

Cursor

20.82%
按下载量换算18

Gemini CLI

10.13%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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