Unstructured is an open-source Python library that turns messy documents, such as PDFs, web pages, Word files and images, into clean, structured pieces ready for language models.
In plain words
Before a RAG app can search your files, it must pull the text out of them, which is hard for complicated PDFs, emails or scans. Unstructured partitions a document into elements, such as titles, paragraphs and tables, and keeps metadata about each one. It can also split the result into chunks for embedding. The open-source library is meant for prototyping; the company also sells a hosted pipeline product for production use.
A quick example
Imagine a folder of mixed company files: PDFs, Word documents and saved web pages. You run each through Unstructured to get a list of elements with their type and source page, then group them into chunks and store them in a vector database for a RAG chatbot.
Where you'll meet it
- Preparing documents for RAG pipelines.
- Extracting text and tables from PDFs and scans.
Related
Sources
- DocsUnstructured-IO/unstructured, Unstructured (GitHub) · read 29 Sept 2026
- DocsOpen source overview, Unstructured documentation · read 29 Sept 2026
Checked by WhatIsAI against the sources above · 29 Sept 2026. Spotted an error? Report it.