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Vespa schema changes for query control & general quality of life #163

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Vespa schema changes for query control & general quality of life #163

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9048c5b
set document language to english
kdutia Dec 18, 2024
9b8ea4a
remove unused 'exact' rank-profile
kdutia Dec 18, 2024
59084c5
add weights with defaults to hybrid profile
kdutia Dec 18, 2024
401105e
hybrid_no_closeness schema inherits from hybrid
kdutia Dec 18, 2024
6a7c6b0
remove hybrid_no_description_embedding rank-profile
kdutia Dec 18, 2024
780bfa4
search_summary_with_tokens inherits search_summary
kdutia Dec 18, 2024
7e2411d
add all features to rank profile summary-features
kdutia Dec 18, 2024
4f238b1
add nativerank profiles
kdutia Dec 18, 2024
7ab8260
add field variants with bolding
kdutia Dec 18, 2024
d6e21d8
bump version to 1.12.0
kdutia Dec 18, 2024
3aec5fc
add summary to family_name_bolding & family_description_bolding
kdutia Dec 18, 2024
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20 changes: 6 additions & 14 deletions tests/local_vespa/test_app/schemas/document_passage.sd
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Original file line number Diff line number Diff line change
Expand Up @@ -197,27 +197,19 @@ schema document_passage {
rank-profile hybrid inherits default {
inputs {
query(query_embedding) tensor<float>(x[768])
query(passage_bm25_weight) double: 1.0
query(passage_closeness_weight) double: 1.0
}
function text_score() {
expression: attribute(passage_weight) * (bm25(text_block) + closeness(text_embedding))
expression: attribute(passage_weight) * (query(passage_bm25_weight) * bm25(text_block) + query(passage_closeness_weight) * closeness(text_embedding))
}
first-phase {
expression: text_score()
}
summary-features: text_score() bm25(text_block) closeness(text_embedding)
}

rank-profile hybrid_custom_weight inherits default {
inputs {
query(query_embedding) tensor<float>(x[768])
query(bm25_weight) double
}
function text_score() {
expression: attribute(passage_weight) * (query(bm25_weight) * bm25(text_block) + closeness(text_embedding))
}
first-phase {
expression: text_score()
}
summary-features: text_score() bm25(text_block) closeness(text_embedding)

rank-profile hybrid_no_embedding inherits hybrid {
}

}
40 changes: 7 additions & 33 deletions tests/local_vespa/test_app/schemas/family_document.sd
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Expand Up @@ -201,53 +201,27 @@ schema family_document {
rank-profile hybrid inherits default {
inputs {
query(query_embedding) tensor<float>(x[768])
query(description_bm25_weight) double: 1.0
query(description_closeness_weight) double: 1.0
}
function name_score() {
expression: attribute(name_weight) * bm25(family_name_index)
expression: bm25(family_name_index)
}
function description_score() {
expression: attribute(description_weight) * (bm25(family_description_index) + closeness(family_description_embedding))
expression: query(description_bm25_weight) * bm25(family_description_index) + query(descriptione_closeness_weight) * closeness(family_description_embedding)
}
first-phase {
expression: name_score() + description_score()
expression: (attribute(name_weight) * name_score()) + (attribute(description_weight) * description_score())
}
summary-features: name_score() description_score()
}

rank-profile hybrid_no_description_embedding inherits default {
rank-profile hybrid_no_description_embedding inherits hybrid {
inputs {
query(query_embedding) tensor<float>(x[768])
}
function name_score() {
expression: attribute(name_weight) * bm25(family_name_index)
query(description_closeness_weight) double: 0.0
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Getting my head around this, does setting this to 0.0 make it have no effect?

}
function description_score() {
expression: attribute(description_weight) * bm25(family_description_index)
}
first-phase {
expression: name_score() + description_score()
}
summary-features: name_score() description_score()
}

rank-profile hybrid_custom_weight inherits default {
inputs {
query(query_embedding) tensor<float>(x[768])
query(bm25_weight) double
}
function name_score() {
expression: attribute(name_weight) * bm25(family_name_index)
}
function description_score() {
expression: attribute(description_weight) * bm25(family_description_index)
}
first-phase {
expression: name_score() + description_score()
}
summary-features: name_score() description_score()
}


document-summary search_summary {
summary family_name {}
summary family_description {}
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