Unstructured Core Library
The unstructured
library is designed to help preprocess and structure unstructured text documents for use in downstream machine learning tasks. Examples of documents that can be processed
using the unstructured
library include PDFs, XML and HTML documents.
Library Documentation
- Installation
Instructions on how to install the
unstructured
library on your system.- Unstructured API Services
Access all the power of
unstructured
through theunstructured-api
or learn to host it locally.- Unstructured Platform
Explore the enterprise-grade platform for enterprises and high-growth companies with large data volume looking to automatically retrieve, transform, and stage their data for LLMs.
- Core Functionality
Learn more about the core partitioning, chunking, cleaning, and staging functionality within the Unstructured library.
- Ingest
Connect to your favorite data storage platforms for an effortless batch processing of your files.
- Metadata
Learn more about how metadata is tracked in the
unstructured
library.- Examples
Examples of other types of workflows within the
unstructured
package.- Integrations
We make it easy for you to connect your output with other popular ML services.
- Best Practices
Learn best practices to optimize document information extraction using
unstructured
library.