The unstructured package from Unstructured.IO extracts clean text from raw source documents like PDFs and Word documents. This page covers how to use the unstructured ecosystem within LangChain.

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Installation and Setup

If you are using a loader that runs locally, use the following steps to get unstructured and its dependencies running.
  • For the smallest installation footprint and to take advantage of features not available in the open-source unstructured package, install the Python SDK with pip install unstructured-client along with pip install langchain-unstructured to use the UnstructuredLoader and partition remotely against the Unstructured API. This loader lives in a LangChain partner repo instead of the langchain-community repo and you will need an api_key, which you can generate a free key here.
  • To run everything locally, install the open-source python package with pip install unstructured along with pip install langchain-community and use the same UnstructuredLoader as mentioned above.
    • You can install document specific dependencies with extras, e.g. pip install "unstructured[docx]". Learn more about extras here.
    • To install the dependencies for all document types, use pip install "unstructured[all-docs]".
  • Install the following system dependencies if they are not already available on your system with e.g. brew install for Mac. 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 PDFs)
    • qpdf (PDFs)
    • libreoffice (MS Office docs)
    • pandoc (EPUBs)
  • When running locally, Unstructured also recommends using Docker by following this guide to ensure all system dependencies are installed correctly.
The Unstructured API requires API keys to make requests. You can request an API key here and start using it today! Checkout the README here here to get started making API calls. We’d love to hear your feedback, let us know how it goes in our community slack. And stay tuned for improvements to both quality and performance! Check out the instructions here if you’d like to self-host the Unstructured API or run it locally.

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Data Loaders

The primary usage of Unstructured is in data loaders.

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UnstructuredLoader

See a usage example to see how you can use this loader for both partitioning locally and remotely with the serverless Unstructured API. 
from langchain_unstructured import UnstructuredLoader

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UnstructuredCHMLoader

CHM means Microsoft Compiled HTML Help. 
from langchain_community.document_loaders import UnstructuredCHMLoader

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UnstructuredCSVLoader

A comma-separated values (CSV) file is a delimited text file that uses a comma to separate values. Each line of the file is a data record. Each record consists of one or more fields, separated by commas. See a usage example. 
from langchain_community.document_loaders import UnstructuredCSVLoader

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UnstructuredEmailLoader

See a usage example. 
from langchain_community.document_loaders import UnstructuredEmailLoader

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UnstructuredEPubLoader

EPUB is an e-book file format that uses the “.epub” file extension. The term is short for electronic publication and is sometimes styled ePub. EPUB is supported by many e-readers, and compatible software is available for most smartphones, tablets, and computers. See a usage example. 
from langchain_community.document_loaders import UnstructuredEPubLoader

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UnstructuredExcelLoader

See a usage example. 
from langchain_community.document_loaders import UnstructuredExcelLoader

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UnstructuredFileIOLoader

See a usage example. 
from langchain_community.document_loaders import UnstructuredFileIOLoader

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UnstructuredHTMLLoader

See a usage example. 
from langchain_community.document_loaders import UnstructuredHTMLLoader

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UnstructuredImageLoader

See a usage example. 
from langchain_community.document_loaders import UnstructuredImageLoader

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UnstructuredMarkdownLoader

See a usage example. 
from langchain_community.document_loaders import UnstructuredMarkdownLoader

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UnstructuredODTLoader

The Open Document Format for Office Applications (ODF), also known as OpenDocument, is an open file format for word processing documents, spreadsheets, presentations and graphics and using ZIP-compressed XML files. It was developed with the aim of providing an open, XML-based file format specification for office applications. See a usage example. 
from langchain_community.document_loaders import UnstructuredODTLoader

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UnstructuredOrgModeLoader

An Org Mode document is a document editing, formatting, and organizing mode, designed for notes, planning, and authoring within the free software text editor Emacs. See a usage example. 
from langchain_community.document_loaders import UnstructuredOrgModeLoader

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UnstructuredPDFLoader

See a usage example. 
from langchain_community.document_loaders import UnstructuredPDFLoader

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UnstructuredPowerPointLoader

See a usage example. 
from langchain_community.document_loaders import UnstructuredPowerPointLoader

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UnstructuredRSTLoader

A reStructured Text (RST) file is a file format for textual data used primarily in the Python programming language community for technical documentation. See a usage example. 
from langchain_community.document_loaders import UnstructuredRSTLoader

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UnstructuredRTFLoader

See a usage example in the API documentation. 
from langchain_community.document_loaders import UnstructuredRTFLoader

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UnstructuredTSVLoader

A tab-separated values (TSV) file is a simple, text-based file format for storing tabular data. Records are separated by newlines, and values within a record are separated by tab characters. See a usage example. 
from langchain_community.document_loaders import UnstructuredTSVLoader

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UnstructuredURLLoader

See a usage example. 
from langchain_community.document_loaders import UnstructuredURLLoader

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UnstructuredWordDocumentLoader

See a usage example. 
from langchain_community.document_loaders import UnstructuredWordDocumentLoader

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UnstructuredXMLLoader

See a usage example. 
from langchain_community.document_loaders import UnstructuredXMLLoader