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To test: > cd docs && make html > click "Ask AI" button on the bottom right-hand corner Changelogs: * Installed kapa.ai widget * fixed sphinx errors in opensearch & elasticsearch documentation
42 lines
1.5 KiB
ReStructuredText
42 lines
1.5 KiB
ReStructuredText
Elasticsearch
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======================
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Batch process all your records using ``unstructured-ingest`` to store structured outputs locally on your filesystem and upload those local files to an Elasticsearch index.
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First you'll need to install Elasticsearch dependencies as shown here.
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.. code:: shell
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pip install "unstructured[elasticsearch]"
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Run Locally
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-----------
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The upstream connector can be any of the ones supported, but for convenience here, showing a sample command using the
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upstream local connector.
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.. tabs::
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.. tab:: Shell
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.. literalinclude:: ./code/bash/elasticsearch.sh
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:language: bash
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.. tab:: Python
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.. literalinclude:: ./code/python/elasticsearch.py
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:language: python
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For a full list of the options the CLI accepts check ``unstructured-ingest <upstream connector> elasticsearch --help``.
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NOTE: Keep in mind that you will need to have all the appropriate extras and dependencies for the file types of the documents contained in your data storage platform if you're running this locally. You can find more information about this in the `installation guide <https://unstructured-io.github.io/unstructured/installing.html>`_.
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Vector Search Sample Mapping
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----------------------------
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To make sure the schema of the index matches the data being written to it, a sample mapping json can be used.
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.. literalinclude:: ./data/elasticsearch_elements_mappings.json
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:language: json
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:linenos:
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:caption: Object description |