Torch Object Storage
Field name | Type | Required | Example value | Description |
Field name | Type | Required | Example value | Description |
vectorBucketName | String | Yes | test-vector-bucket | Name of the vector bucket. |
indexName | String | Yes | test-index | name of the vector index |
filter | JSON value | No | {"$and": [{"key_a": "va"}]} | Metadata filters applied during the query. |
queryVector | VectorData | Yes | { "float32": [ 0.1, 0.1, 0.1, 0.1, 0.1] } | Query vector. Ensure the query vector's dimension matches the dimension of the indexed vectors. |
returnDistance | boolean | No | true | Indicates whether to include the calculated distance in the response. Default: false. |
returnMetadata | boolean | No | true | Indicates whether to include metadata in the response. Default: false. |
topK | integer | Yes | 10 | The number of results returned for each query. Valid range: minimum 1, maximum 30. |
Field name | Type | Example value | Description |
Field name | Type | Example value | Description |
float32 | float32[] | [0.1, 0.1, 0.1, 0.1, 0.1] | Vector data. The vector dimension must match the vector index dimension defined in CreateIndex. |
Field | Condition operator type | Example value | Description |
Field | Condition operator type | Example value | Description |
vectors | []QueryOutputVector | see the table below | An array containing vector search results. |
Name | Type | Example value | Description |
Name | Type | Example value | Description |
data | VectorData | [0.1, 0.1, 0.1, 0.1, 0.1] | Vector data. Ensure the query vector's dimension matches the dimension of the vector index being queried. |
distance | float | 0.050000004 | Distance between query vector and result vector. |
key | String | key0 | Unique identifier of the vector. |
metadata | JSON value | { "key_a": "va", "key_b": "vb", "key_c": "vc1", "key_d": "vd" } | Metadata associated with the vector |