The unstructured library provides open-source components for ingesting and pre-processing images and text documents, such as PDFs, HTML, Word docs, and many more. The use cases of unstructured revolve around streamlining and optimizing the data processing workflow for LLMs. unstructured modular bricks and connectors form a cohesive system that simplifies data ingestion and pre-processing, making it adaptable to different platforms and is efficient in transforming unstructured data into structured outputs.
Features
- We are releasing the beta version of our Chipper model to deliver superior performance when processing high-resolution, complex documents
- Run the library in a container
- You can also build your own Docker image
- Installation Instructions for Local Development
- Create a virtualenv to work in and activate it
- Chipper Model
Project Samples
Categories
Large Language Models (LLM)License
Apache License V2.0Follow Unstructured.IO
You Might Also Like
Gen AI apps are built with MongoDB Atlas
MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of Unstructured.IO!