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searx/engines/meilisearch.py

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+# SPDX-License-Identifier: AGPL-3.0-or-later
+""".. sidebar:: info
+
+   - :origin:`meilisearch.py <searx/engines/meilisearch.py>`
+   - `MeiliSearch <https://www.meilisearch.com>`_
+   - `MeiliSearch Documentation <https://docs.meilisearch.com/>`_
+   - `Install MeiliSearch
+     <https://docs.meilisearch.com/learn/getting_started/installation.html>`_
+
+MeiliSearch_ is aimed at individuals and small companies.  It is designed for
+small-scale (less than 10 million documents) data collections.  E.g. it is great
+for storing web pages you have visited and searching in the contents later.
+
+The engine supports faceted search, so you can search in a subset of documents
+of the collection.  Furthermore, you can search in MeiliSearch_ instances that
+require authentication by setting `auth_key`_.
+
+.. _auth_key: https://www.meilisearch.com/docs/reference/api/overview#authorization
+
+Example
+=======
+
+Here is a simple example to query a Meilisearch instance:
+
+.. code:: yaml
+
+  - name: meilisearch
+    engine: meilisearch
+    shortcut: mes
+    base_url: http://localhost:7700
+    index: my-index
+    enable_http: true
+    # auth_key: Bearer XXXXX
+
+"""
+
+# pylint: disable=global-statement
+
+from json import dumps
+from searx.result_types import EngineResults
+from searx.extended_types import SXNG_Response
+
+base_url = 'http://localhost:7700'
+index = ''
+auth_key = ''
+facet_filters = []
+_search_url = ''
+categories = ['general']
+paging = True
+
+
+def init(_):
+    if index == '':
+        raise ValueError('index cannot be empty')
+
+    global _search_url
+    _search_url = base_url + '/indexes/' + index + '/search'
+
+
+def request(query, params):
+    if auth_key != '':
+        params['headers']['Authorization'] = auth_key
+
+    params['headers']['Content-Type'] = 'application/json'
+    params['url'] = _search_url
+    params['method'] = 'POST'
+
+    data = {
+        'q': query,
+        'offset': 10 * (params['pageno'] - 1),
+        'limit': 10,
+    }
+    if len(facet_filters) > 0:
+        data['facetFilters'] = facet_filters
+
+    params['data'] = dumps(data)
+
+    return params
+
+
+def response(resp: SXNG_Response) -> EngineResults:
+    res = EngineResults()
+
+    resp_json = resp.json()
+    for row in resp_json['hits']:
+        kvmap = {key: str(value) for key, value in row.items()}
+        res.add(res.types.KeyValue(kvmap=kvmap))
+
+    return res