Create single data directory for all models / input data
mkdir data
Obtain TargetSize150.zip
, unpack and move into data directory
unzip -qq TargetSize150.zip && mv TargetSize150/* data && rmdir TargetSize150
Obtain doc2vec.csv
, then store in data directory
mv doc2vec.csv data
After local deploy (requires ./data setup as per "Local setup" instructions)
docker-compose up --build
Add a user:
curl -XPOST http://localhost:3000/users -d '${username}'
List of snippets:
http://localhost:8080/es/snippets/_search
Single snippet:
http://localhost:8080/es/snippets/snippet/$id
More like this:
curl -XGET -H 'Content-Type: application/json' \
http://localhost:8080/es/snippets/_search -d '{
"query": {
"more_like_this": {
"fields": ["text", "lemma"],
"boost_terms": 1,
"max_query_terms": 150,
"min_doc_freq": 1,
"min_term_freq": 1,
"like": [{
"_index": "snippets",
"_type": "snippet",
"_id": "'${id}'"
}]
}
}
}'
More like this:
curl http://localhost:8080/doc2vec/$id
Paging in doc2vec
is done using request parameters from
(default 0
) and size
(default 10
)
curl http://localhost:8080/doc2vec/$id?from=3&size=8
Copyright 2016-2019 Koninklijke Nederlandse Academie van Wetenschappen
Distributed under the terms of the GNU General Public License, version 3. See the file LICENSE for details.