The blog article 'Query your local search engines' has been renamed 'Local Search Engines', revised and moved into admin's chapter 'Engine & Settings'. Signed-off-by: Markus Heiser <markus.heiser@darmarit.de>
		
			
				
	
	
		
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====================
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Local Search Engines
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====================
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.. sidebar:: further read
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   - `Comparison to alternatives
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     <https://docs.meilisearch.com/learn/what_is_meilisearch/comparison_to_alternatives.html>`_
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Administrators might find themselves wanting to integrate locally running search
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engines.  The following ones are supported for now:
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* `Elasticsearch`_
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* `Meilisearch`_
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* `Solr`_
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Each search engine is powerful, capable of full-text search.  All of the engines
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above are added to ``settings.yml`` just commented out, as you have to
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``base_url`` for all them.
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Please note that if you are not using HTTPS to access these engines, you have to enable
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HTTP requests by setting ``enable_http`` to ``True``.
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Futhermore, if you do not want to expose these engines on a public instance, you
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can still add them and limit the access by setting ``tokens`` as described in
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section :ref:`private engines`.
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.. _engine meilisearch:
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MeiliSearch
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===========
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.. sidebar:: info
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   - :origin:`meilisearch.py <searx/engines/meilisearch.py>`
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   - `MeiliSearch <https://www.meilisearch.com>`_
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   - `MeiliSearch Documentation <https://docs.meilisearch.com/>`_
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   - `Install MeiliSearch
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     <https://docs.meilisearch.com/learn/getting_started/installation.html>`_
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MeiliSearch_ is aimed at individuals and small companies.  It is designed for
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small-scale (less than 10 million documents) data collections.  E.g. it is great
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for storing web pages you have visited and searching in the contents later.
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The engine supports faceted search, so you can search in a subset of documents
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of the collection.  Furthermore, you can search in MeiliSearch_ instances that
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require authentication by setting ``auth_token``.
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Here is a simple example to query a Meilisearch instance:
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.. code:: yaml
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  - name: meilisearch
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    engine: meilisearch
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    shortcut: mes
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    base_url: http://localhost:7700
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    index: my-index
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    enable_http: true
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.. _engine elasticsearch:
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Elasticsearch
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=============
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.. sidebar:: info
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   - :origin:`elasticsearch.py <searx/engines/elasticsearch.py>`
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   - `Elasticsearch <https://www.elastic.co/elasticsearch/>`_
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   - `Elasticsearch Guide
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     <https://www.elastic.co/guide/en/elasticsearch/reference/current/index.html>`_
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   - `Install Elasticsearch
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     <https://www.elastic.co/guide/en/elasticsearch/reference/current/install-elasticsearch.html>`_
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Elasticsearch_ supports numerous ways to query the data it is storing.  At the
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moment the engine supports the most popular search methods (``query_type``):
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- ``match``,
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- ``simple_query_string``,
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- ``term`` and
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- ``terms``.
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If none of the methods fit your use case, you can select ``custom`` query type
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and provide the JSON payload to submit to Elasticsearch in
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``custom_query_json``.
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The following is an example configuration for an Elasticsearch_ instance with
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authentication configured to read from ``my-index`` index.
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.. code:: yaml
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  - name: elasticsearch
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    shortcut: es
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    engine: elasticsearch
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    base_url: http://localhost:9200
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    username: elastic
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    password: changeme
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    index: my-index
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    query_type: match
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    # custom_query_json: '{ ... }'
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    enable_http: true
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.. _engine solr:
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Solr
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====
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.. sidebar:: info
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   - :origin:`solr.py <searx/engines/solr.py>`
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   - `Solr <https://solr.apache.org>`_
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   - `Solr Resources <https://solr.apache.org/resources.html>`_
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   - `Install Solr <https://solr.apache.org/guide/installing-solr.html>`_
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Solr_ is a popular search engine based on Lucene, just like Elasticsearch_.  But
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instead of searching in indices, you can search in collections.
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This is an example configuration for searching in the collection
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``my-collection`` and get the results in ascending order.
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.. code:: yaml
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  - name: solr
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    engine: solr
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    shortcut: slr
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    base_url: http://localhost:8983
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    collection: my-collection
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    sort: asc
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    enable_http: true
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Acknowledgment
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==============
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This development was sponsored by `Search and Discovery Fund
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<https://nlnet.nl/discovery>`_ of `NLnet Foundation <https://nlnet.nl/>`_.
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