Unstructured
Convert documents to structured data effortlessly. Unstructured is open-source ETL solution for transforming complex documents into clean, structured formats for language models. Visit our website to learn more about our enterprise grade Platform product for production grade workflows, partitioning, enrichments, chunking and embedding.
Install / Use
/learn @Unstructured-IO/UnstructuredREADME
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<a href="https://pypi.python.org/pypi/unstructured/">
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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 functions and connectors form a cohesive system that simplifies data ingestion and pre-processing, making it adaptable to different platforms and efficient in transforming unstructured data into structured outputs.
Try the Unstructured Platform Product
Ready to move your data processing pipeline to production, and take advantage of advanced features? Check out Unstructured Platform. In addition to better processing performance, take advantage of chunking, embedding, and image and table enrichment generation, all from a low code UI or an API. Request a demo from our sales team to learn more about how to get started.
:eight_pointed_black_star: Quick Start
There are several ways to use the unstructured library:
- Run the library in a container or
- Install the library
- For installation with
condaon Windows system, please refer to the documentation
Run the library in a container
The following instructions are intended to help you get up and running using Docker to interact with unstructured.
See here if you don't already have docker installed on your machine.
NOTE: we build multi-platform images to support both x86_64 and Apple silicon hardware. docker pull should download the corresponding image for your architecture, but you can specify with --platform (e.g. --platform linux/amd64) if needed.
We build Docker images for all pushes to main. We tag each image with the corresponding short commit hash (e.g. fbc7a69) and the application version (e.g. 0.5.5-dev1). We also tag the most recent image with latest. To leverage this, docker pull from our image repository.
docker pull downloads.unstructured.io/unstructured-io/unstructured:latest
Once pulled, you can create a container from this image and shell to it.
# create the container
docker run -dt --name unstructured downloads.unstructured.io/unstructured-io/unstructured:latest
# this will drop you into a bash shell where the Docker image is running
docker exec -it unstructured bash
You can also build your own Docker image. Note that the base image is wolfi-base, which is
updated regularly. If you are building the image locally, it is possible docker-build could
fail due to upstream changes in wolfi-base.
If you only plan on parsing one type of data you can speed up building the image by commenting out some of the packages/requirements necessary for other data types. See Dockerfile to know which lines are necessary for your use case.
make docker-build
# this will drop you into a bash shell where the Docker image is running
make docker-start-bash
Once in the running container, you can try things directly in Python interpreter's interactive mode.
# this will drop you into a python console so you can run the below partition functions
python3
>>> from unstructured.partition.pdf import partition_pdf
>>> elements = partition_pdf(filename="example-docs/layout-parser-paper-fast.pdf")
>>> from unstructured.partition.text import partition_text
>>> elements = partition_text(filename="example-docs/fake-text.txt")
Installing the library
Use the following instructions to get up and running with unstructured and test your
installation.
- Install the Python SDK to support all document types with
pip install "unstructured[all-docs]"- For plain text files, HTML, XML, JSON and Emails that do not require any extra dependencies, you can run
pip install unstructured - To process other doc types, you can install the extras required for those documents, such as
pip install "unstructured[docx,pptx]"
- For plain text files, HTML, XML, JSON and Emails that do not require any extra dependencies, you can run
- Install the following system dependencies if they are not already available on your system.
Depending on what document types you're parsing, you may not need all of these.
libmagic-dev(filetype detection)poppler-utils(images and PDFs)tesseract-ocr(images and PDF
