教程：为RAG将PDF解析为关系型DataFrames（涵盖线条、页面、目录等）
英文摘要
This Towards Data Science tutorial presents a PDF parsing method that outputs relational DataFrames instead of flat text. It extracts structured elements including lines, pages, table of contents, images, cross-references, captions, spans, and a parsing summary. The relational shape is designed to improve retrieval-augmented generation (RAG) workflows by preserving document structure. The post is part of the 'Enterprise Document Intelligence' series.
中文摘要
该Towards Data Science教程介绍了一种PDF解析方法，输出关系型DataFrames而非纯文本，提取线条、页面、目录、图像、交叉引用、标题、文本段和解析摘要等结构化元素。这种关系型结构旨在通过保留文档结构来改进检索增强生成（RAG）流程。文章属于“企业文档智能”系列。
关键要点
The tutorial advocates replacing flat text with relational DataFrames for PDF extraction.
教程提倡用关系型DataFrames替代纯文本进行PDF提取。
Extracted elements include lines, pages, table of contents, images, cross-references, captions, spans, and a parsing summary.
提取的元素涵盖线条、页面、目录、图像、交叉引用、标题、文本段和解析摘要。