mirror of
https://github.com/searxng/searxng.git
synced 2024-11-11 07:20:13 +01:00
88 lines
2.1 KiB
Python
88 lines
2.1 KiB
Python
# 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_token``.
|
|
|
|
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
|
|
|
|
"""
|
|
|
|
# pylint: disable=global-statement
|
|
|
|
from json import loads, dumps
|
|
|
|
|
|
base_url = 'http://localhost:7700'
|
|
index = ''
|
|
auth_key = ''
|
|
facet_filters = []
|
|
_search_url = ''
|
|
result_template = 'key-value.html'
|
|
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']['X-Meili-API-Key'] = 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):
|
|
results = []
|
|
|
|
resp_json = loads(resp.text)
|
|
for result in resp_json['hits']:
|
|
r = {key: str(value) for key, value in result.items()}
|
|
r['template'] = result_template
|
|
results.append(r)
|
|
|
|
return results
|