Xberg 文档智能技能合集
通过 Xberg 多语言处理工具提取和分析文档。
官方插件技能指导文档提取、配置、OCR、服务集成以及支持格式的相关处理流程。
适用场景
- 提取文本、表格、图片和元数据
- 将文档处理接入应用
使用方法
安装所需 Xberg 语言绑定或命令行工具并使用官方插件。准备提取运行环境，其他插件技能目录是宿主镜像。
Skills
batch-extraction
Use when extracting from many files at once with shared config, bounded parallelism, per-file overrides, and error recovery. Covers the `batch` command, `--file-configs`, `--max-concurrent`, and output layout.
xberg-io/xbergchunking
Use when splitting extracted text into chunks for LLM context windows or RAG ingestion. Covers chunk size, overlap, markdown/yaml/semantic chunkers, tokenizer-based sizing, and the standalone `chunk` command.
xberg-io/xbergextracting-keywords
Use when extracting keywords (YAKE/RAKE) from documents — and, secondarily, when detecting document language or generating embeddings for RAG and search. Covers the keyword config (and its feature gating), `--detect-language`, and the standalone `embed` command with real flags.
xberg-io/xbergextracting-tables
Use when extracting tabular data from PDFs, spreadsheets, or images. Covers layout-aware table detection, table model selection, output formats (markdown / JSON cells), and known limits.
xberg-io/xbergextracting-with-ocr
Use when extracting text from scanned PDFs, photographed pages, or images that have no embedded text layer. Covers OCR backends, language packs, force-OCR, and performance tuning.
xberg-io/xbergpicking-a-format
Use when choosing an output format for extracted documents — plain text, markdown, djot, HTML, JSON, or DocTags. Maps consumer (LLM, parser, archive) to the right `--format` / `--content-format` pair.
xberg-io/xbergxberg
Extract text, tables, metadata, and images from 107 document formats (PDF, Office, images, HTML, email, archives, academic) using Xberg. Use when writing code that calls Xberg APIs in Python, Node.js/TypeScript, Rust, or CLI. Covers installation, extraction (sync/async), configuration (OCR, chunking, output format), batch processing, error handling, and plugins.
xberg-io/xberg