With this plugin you can query documents with vectors and score them based on dot product or cosine similarity. This plugin is the same as Vector Scoring Plugin for Elasticsearch.
The plugin was developed and tested on Solr 7.4.0.
- Build the jar using maven
mvn -Prelease clean package
- Copy the jar Vector-Plugin-deploy-*.jar to {solr.install.dir}/dist/plugins/
- Add the library to solrconfig.xml file:
<lib dir="${solr.install.dir:../../../..}/dist/plugins/" regex=".*\.jar" />
- Add the plugin Query parser to solrconfig.xml:
<queryParser name="vp" class="com.github.saaay71.solr.query.VectorQParserPlugin" />
- Add the fieldType
VectorFieldto schema file(managed-schema):
<fieldType name="VectorField" class="solr.BinaryField" stored="true" indexed="false" multiValued="false"/>
- Add the field
vectorto schema file:
<field name="_vector_" type="VectorField" />
<field name="_lsh_hash_" type="string" indexed="true" stored="true" multiValued="true"/>
<field name="vector" type="string" indexed="true" stored="true"/>
- Add the LSH urp to solrconfig.xml
<updateRequestProcessorChain name="LSH">
<processor class="com.github.saaay71.solr.updateprocessor.LSHUpdateProcessorFactory" >
<int name="seed">5</int>
<int name="buckets">50</int>
<int name="stages">50</int>
<int name="dimensions">6</int>
<str name="field">vector</str>
</processor>
<processor class="solr.RunUpdateProcessorFactory" />
</updateRequestProcessorChain>
- Start Solr!
curl -X POST -H "Content-Type: application/json" http://localhost:8983/solr/{your-collection-name}/update?update.chain=LSH&commit=true --data-binary '
[
{"id":"1", "vector":"1.55,3.53,2.3,0.7,3.44,2.33"},
{"id":"2", "vector":"3.54,0.4,4.16,4.88,4.28,4.25"}
]'Open your browser and copy the links
http://localhost:8983/solr/{your-collection-name}/query?fl=name,score,vector&q={!vp f=vector vector=\"1.55,3.53,2.3,0.7,3.44,2.33\" lsh=\"true\" reRankDocs=\"5\"}&fl=name,score,vector,_vector_,_lsh_hash_
You should see the following result:
{
"responseHeader":{
"status":0,
"QTime":8,
"params":{
"q":"{!vp f=vector vector=\"1.55,3.53,2.3,0.7,3.44,2.33\" lsh=\"true\" reRankDocs=\"5\"}",
"fl":"id, score, vector, _vector_, _lsh_hash_",
"wt":"xml"}},
"response":{"numFound":1,"start":0,"maxScore":36.65736,"docs":[
{
"id": "1",
"vector":"1.55,3.53,2.3,0.7,3.44,2.33",
"_vector_":"/z/GZmZAYeuFQBMzMz8zMzNAXCj2QBUeuA==",
"_lsh_hash_":["0_8",
"1_35",
"2_7",
"3_10",
"4_2",
"5_35",
"6_16",
"7_30",
"8_27",
"9_12",
"10_7",
"11_32",
"12_48",
"13_36",
"14_10",
"15_7",
"16_42",
"17_5",
"18_3",
"19_2",
"20_1",
"21_0",
"22_24",
"23_18",
"24_42",
"25_31",
"26_35",
"27_8",
"28_1",
"29_24",
"30_47",
"31_14",
"32_22",
"33_39",
"34_0",
"35_34",
"36_34",
"37_39",
"38_27",
"39_27",
"40_45",
"41_10",
"42_21",
"43_34",
"44_41",
"45_9",
"46_31",
"47_0",
"48_4",
"49_43"],
"score":36.65736}
]
}
}
Quering on other fields and with vector scoring.
http://localhost:8983/solr/{your-collection-name}/query?fl=name,score,vector&q={!vp f=vector vector=\"3.54,0.4,4.16,4.88,4.28,4.25\" lsh=\"true\" reRankDocs=\"5\" v=\"id:2\"}&fl=name,score,vector,_vector_,_lsh_hash_
or
http://localhost:8983/solr/{your-collection-name}/query?fl=name,score,vector&q={!vp f=vector vector=\"3.54,0.4,4.16,4.88,4.28,4.25\" lsh=\"true\" reRankDocs=\"5\"} id:2&fl=name,score,vector,_vector_,_lsh_hash_
result of query 2:
{
"responseHeader":{
"status":0,
"QTime":9,
"params":{
"q":"{!vp f=vector vector=\"3.54,0.4,4.16,4.88,4.28,4.25\" lsh=\"true\" reRankDocs=\"5\" v=\"id:2\"}",
"fl":"name, score, vector, _vector_, _lsh_hash_",
"wt":"xml"}},
"response":{"numFound":1,"start":0,"maxScore":38.649788,"docs":[
{
"id": "2",
"vector":"3.54,0.4,4.16,4.88,4.28,4.25",
"_vector_":"/0Bij1w+zMzNQIUeuECcKPZAiPXDQIgAAA==",
"_lsh_hash_":["0_2",
"1_33",
"2_39",
"3_49",
"4_38",
"5_12",
"6_21",
"7_26",
"8_44",
"9_25",
"10_15",
"11_25",
"12_24",
"13_8",
"14_22",
"15_43",
"16_1",
"17_17",
"18_14",
"19_1",
"20_26",
"21_47",
"22_15",
"23_36",
"24_21",
"25_41",
"26_32",
"27_35",
"28_13",
"29_4",
"30_2",
"31_39",
"32_19",
"33_36",
"34_15",
"35_30",
"36_17",
"37_0",
"38_39",
"39_32",
"40_5",
"41_1",
"42_33",
"43_0",
"44_32",
"45_21",
"46_23",
"47_4",
"48_24",
"49_16"],
"score":38.649788}]
}
}
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