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### Summary We no longer use the "bricks" terminology for partioning functions, etc in the library. This PR updates various references to bricks within the repo and the docs. This is just an initial pass to swap the terminology out, it'll likely be helpful to reorganize the docs a bit as well. --------- Co-authored-by: qued <64741807+qued@users.noreply.github.com> Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
56 lines
1.6 KiB
ReStructuredText
56 lines
1.6 KiB
ReStructuredText
Unstructured Core Library
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=========================
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The ``unstructured`` library is designed to help preprocess structure unstructured text documents
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for use in downstream machine learning tasks. Examples of documents that can be processed
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using the ``unstructured`` library include PDFs, XML and HTML documents.
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Library Documentation
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---------------------
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:doc:`installing`
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Instructions on how to install the ``unstructured`` library on your system.
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:doc:`api`
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Access all the power of ``unstructured`` through the ``unstructured-api`` or learn to host it locally.
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:doc:`core`
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Learn more about the core partitioning, chunking, cleaning, and staging functionality within the
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Unstructured library.
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:doc:`source_connectors`
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Connect to your favorite data storage platforms for an effortless batch processing of your files.
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:doc:`destination_connectors`
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Connect to your favorite data storage platforms to write you ingest results to.
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:doc:`metadata`
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Learn more about how metadata is tracked in the ``unstructured`` library.
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:doc:`examples`
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Examples of other types of workflows within the ``unstructured`` package.
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:doc:`integrations`
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We make it easy for you to connect your output with other popular ML services.
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:doc:`best_practices`
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Learn best practices to optimize document information extraction using ``unstructured`` library.
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.. Hidden TOCs
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.. toctree::
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:caption: Documentation
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:maxdepth: 2
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:hidden:
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introduction
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installing
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api
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core
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source_connectors
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destination_connectors
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metadata
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examples
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integrations
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best_practices
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