mirror of
https://github.com/hwchase17/langchain
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54 lines
2.4 KiB
Plaintext
54 lines
2.4 KiB
Plaintext
# Unstructured
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>The `unstructured` package from
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[Unstructured.IO](https://www.unstructured.io/) extracts clean text from raw source documents like
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PDFs and Word documents.
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This page covers how to use the [`unstructured`](https://github.com/Unstructured-IO/unstructured)
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ecosystem within LangChain.
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## Installation and Setup
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If you are using a loader that runs locally, use the following steps to get `unstructured` and
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its dependencies running locally.
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- Install the Python SDK with `pip install "unstructured[local-inference]"`
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- Install the following system dependencies if they are not already available on your system.
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Depending on what document types you're parsing, you may not need all of these.
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- `libmagic-dev` (filetype detection)
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- `poppler-utils` (images and PDFs)
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- `tesseract-ocr`(images and PDFs)
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- `libreoffice` (MS Office docs)
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- `pandoc` (EPUBs)
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If you want to get up and running with less set up, you can
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simply run `pip install unstructured` and use `UnstructuredAPIFileLoader` or
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`UnstructuredAPIFileIOLoader`. That will process your document using the hosted Unstructured API.
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The Unstructured API requires API keys to make requests.
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You can generate a free API key [here](https://www.unstructured.io/api-key) and start using it today!
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Checkout the README [here](https://github.com/Unstructured-IO/unstructured-api) here to get started making API calls.
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We'd love to hear your feedback, let us know how it goes in our [community slack](https://join.slack.com/t/unstructuredw-kbe4326/shared_invite/zt-1x7cgo0pg-PTptXWylzPQF9xZolzCnwQ).
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And stay tuned for improvements to both quality and performance!
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Check out the instructions
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[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.
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## Wrappers
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### Data Loaders
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The primary `unstructured` wrappers within `langchain` are data loaders. The following
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shows how to use the most basic unstructured data loader. There are other file-specific
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data loaders available in the `langchain.document_loaders` module.
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```python
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from langchain.document_loaders import UnstructuredFileLoader
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loader = UnstructuredFileLoader("state_of_the_union.txt")
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loader.load()
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```
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If you instantiate the loader with `UnstructuredFileLoader(mode="elements")`, the loader
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will track additional metadata like the page number and text type (i.e. title, narrative text)
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when that information is available.
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