diff --git a/model/database/spans.yaml b/model/database/spans.yaml index 466f568c9f..3c3147c31a 100644 --- a/model/database/spans.yaml +++ b/model/database/spans.yaml @@ -803,34 +803,34 @@ groups: If the query doesn't target a specific index, this field MUST NOT be set. examples: ['my_index', 'index1, index2'] - ref: db.search.similarity_metric - brief: specify the metric used in similarity search (e.g. cosine) + brief: Specifies the metric used in similarity search (e.g. cosine) note: > Some vector databases allow specifying the similarity search during a search, while others only allow it when creating an index or collection. requirement_level: conditionally_required: If available. examples: ['cosine', 'dot', 'euclidean', 'manhattan'] - ref: db.record.id - brief: the ID of the record (e.g. the ID of the vector) + brief: The ID of the record (e.g. the ID of the vector) note: > Some vector databases identify a vector using an ID. requirement_level: conditionally_required: If available. examples: ['1', '5c56c793-69f3-4fbf-87e6-c4bf54c28c26'] - ref: db.vector.field_name - brief: the name field of the vector embedding + brief: The name field of the vector embedding note: > Some vector databases use a field name to store the vector. requirement_level: conditionally_required: If available. examples: ['image_vector', 'embedding_field'] - ref: db.vector.dimension_count - brief: the dimension of the vector (e.g. 1536) + brief: The dimension of the vector (e.g. 1536) note: > The dimension of a vector is typically defined when building an index/collection. requirement_level: recommended examples: [3, 1536] - ref: db.vector.query.top_k - brief: the top-k most similar vectors returned by a query + brief: The top-k most similar vectors returned by a query note: > The top-k parameter is usually specified when executing a vector search (i.e. query) requirement_level: