LandingAI 推出文档提取 Agent 技能

meng shao (@shao__meng) 转发了 Sumanth (@Sumanth_077) 的帖子： Turn Claude Code into a document processing agent! Traditional OCR extracts text but loses critical information. Table structures with merged cells disappear. Relationships between charts and captions break. Multi-column reading order gets scrambled. That's why most document pipelines need manual templates per document type, and break the moment a vendor changes their invoice format. Agentic Document Extraction (ADE) takes a different approach. It's vision-first, understanding layout the way a person reading the page would. Handles complex tables, dense forms, multi-column pages, and scanned documents. LandingAI now released the ADE skills for AI coding agents. Instead of calling the API directly, your agent writes Python scripts that parse, extract, classify, and chain these steps into full pipelines. Every extracted value comes with bounding boxes, page coordinates, and confidence scores traceable back to the source document. Two skills make up the system: 1. Document-extraction - parsing into structured Markdown, extracting fields with JSON schemas or Pydantic models, splitting and classifying multi-document batches. 2. Document-workflows - batch processing in parallel, classify-then-extract pipelines, RAG preparation with chunking and embeddings, exporting to DataFrames or Snowflake, building Streamlit UIs. Once installed, you describe what you need in plain English. Ask your agent to extract line items from a folder of invoices, pull every figure from a scientific paper as PNGs, or read account statements across pages into a single CSV. Key capabilities: • Parses 20+ file formats with layout-aware structured output • Vision-first model, no templates required • Bounding boxes, page coordinates, and confidence scores per extraction • Classify-then-extract pipelines for mixed document batches • Works with Claude Code, Cursor, Roo Code, or any Agent Skills-compatible Agent I've shared the link in the replies!