langchain/docs/integrations/unstructured.md
Matt Robinson 4c8aad0d1b
docs: unstructured no longer requires installing detectron2 from source (#5524)
# Update Unstructured docs to remove the `detectron2` install
instructions

Removes `detectron2` installation instructions from the Unstructured
docs because installing `detectron2` is no longer required for
`unstructured>=0.7.0`. The `detectron2` model now runs using the ONNX
runtime.

## Who can review?

@hwchase17 
@eyurtsev
2023-05-31 15:03:21 -07:00

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Markdown

# Unstructured
>The `unstructured` package from
[Unstructured.IO](https://www.unstructured.io/) extracts clean text from raw source documents like
PDFs and Word documents.
This page covers how to use the [`unstructured`](https://github.com/Unstructured-IO/unstructured)
ecosystem within LangChain.
## Installation and Setup
If you are using a loader that runs locally, use the following steps to get `unstructured` and
its dependencies running locally.
- Install the Python SDK with `pip install "unstructured[local-inference]"`
- 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 PDFs)
- `libreoffice` (MS Office docs)
- `pandoc` (EPUBs)
If you want to get up and running with less set up, you can
simply run `pip install unstructured` and use `UnstructuredAPIFileLoader` or
`UnstructuredAPIFileIOLoader`. That will process your document using the hosted Unstructured API.
Note that currently (as of 1 May 2023) the Unstructured API is open, but it will soon require
an API. The [Unstructured documentation page](https://unstructured-io.github.io/) will have
instructions on how to generate an API key once they're available. Check out the instructions
[here](https://github.com/Unstructured-IO/unstructured-api#dizzy-instructions-for-using-the-docker-image)
if you'd like to self-host the Unstructured API or run it locally.
## Wrappers
### Data Loaders
The primary `unstructured` wrappers within `langchain` are data loaders. The following
shows how to use the most basic unstructured data loader. There are other file-specific
data loaders available in the `langchain.document_loaders` module.
```python
from langchain.document_loaders import UnstructuredFileLoader
loader = UnstructuredFileLoader("state_of_the_union.txt")
loader.load()
```
If you instantiate the loader with `UnstructuredFileLoader(mode="elements")`, the loader
will track additional metadata like the page number and text type (i.e. title, narrative text)
when that information is available.