Query tensor in vespa.ai - vespa

Question

Imitating: https://blog.vespa.ai/billion-scale-knn/
Command line:
curl -s -d '{"yql":"select * from user where {\"targetHits\":10}nearestNeighbor(approximate, q_binary_code);","ranking.features.query(q_binary_code)":[1,2,3,4,5,6,7,8,9,10],"hits":10}' -H "Content-Type: application/json" -X POST http://localhost:8080/search/ | jq .
Error message:
{
"root": {
"id": "toplevel",
"relevance": 1,
"fields": {
"totalCount": 0
},
"errors": [
{
"code": 4,
"summary": "Invalid query parameter",
"source": "content",
"message": "Expected a tensor value of 'query(q_binary_code)' but has [1,2,3,4,5,6,7,8,9,10]"
}
]
}
}
Question: How pass q_binary_code?

Answer 1

With recent Vespa versions, you can define the query tensor in the schema. It must be defined
schema code {
document code {
field id type int {..}
field binary_code type tensor<int8>(b[16]) {..}
}
rank-profile coarse-ranking {
inputs {
query(q_binary_code) tensor<int8>(b[16])
}
num-threads-per-search:12
first-phase { expression { closeness(field,binary_code) } }
}
You also must define the rank profile in the query request:
curl -s -d '{"yql":"select * from user where {\"targetHits\":10}nearestNeighbor(binary_code, q_binary_code);","ranking.features.query(q_binary_code)":[1,2,3,4,5,6,7,8,9,10],"hits":10, "ranking": "coarse-ranking"}' -H "Content-Type: application/json" -X POST http://localhost:8080/search/ | jq .