gcloud beta vector-search collections data-objects search

NAME

gcloud beta vector-search collections data-objects search - search data objects from a Vector Search collection

SYNOPSIS

gcloud beta vector-search collections data-objects search --collection=COLLECTION --location=LOCATION (--semantic-search-field=SEMANTIC_SEARCH_FIELD --semantic-search-text=SEMANTIC_SEARCH_TEXT --semantic-task-type=SEMANTIC_TASK_TYPE     | --text-search-data-fields=[DATA_FIELD_NAME,…] --text-search-text=TEXT_SEARCH_TEXT     | [--vector-from-file=VECTOR_FROM_FILE --vector-search-field=VECTOR_SEARCH_FIELD : --distance-metric=DISTANCE_METRIC]) [--json-filter=JSON_FILTER] [--top-k=TOP_K] [--output-data-fields=[DATA_OUTPUT_FIELD,…] --output-metadata-fields=[METADATA_OUTPUT_FIELD,…] --output-vector-fields=[VECTOR_OUTPUT_FIELD,…]] [--use-knn     | [--use-index=INDEX_NAME : --dense-scann-initial-candidate-count=CANDIDATE_COUNT --dense-scann-search-leaves-pct=PERCENTAGE]] [GCLOUD_WIDE_FLAG …]

DESCRIPTION

(BETA) Search data objects from a Vector Search collection.

EXAMPLES

To search data objects from collection my-collection in location us-central1 using text search and return 10 results, run:

gcloud beta vector-search collections data-objects search --collection=my-collection --location=us-central1 --text-search-text="test" --text-search-data-fields="text_field" --top-k=10

REQUIRED FLAGS

--collection=COLLECTION

The collection to search data objects from.

--location=LOCATION

Location of the collection.

Search type

Exactly one of these must be specified:

Semantic Search

--semantic-search-field=SEMANTIC_SEARCH_FIELD

The vector field to search.

This flag argument must be specified if any of the other arguments in this group are specified.

--semantic-search-text=SEMANTIC_SEARCH_TEXT

The query text for semantic search.

This flag argument must be specified if any of the other arguments in this group are specified.

--semantic-task-type=SEMANTIC_TASK_TYPE

The task type of the query embedding for semantic search. SEMANTIC_TASK_TYPE must be one of:

classification

Specifies that the given text will be classified.

clustering

Specifies that the embeddings will be used for clustering.

code-retrieval-query

Specifies that the embeddings will be used for code retrieval.

fact-verification

Specifies that the embeddings will be used for fact verification.

question-answering

Specifies that the embeddings will be used for question answering.

retrieval-document

Specifies the given text is a document from the corpus being searched.

retrieval-query

Specifies the given text is a query in a search/retrieval setting.

semantic-similarity

Specifies the given text will be used for STS.

This flag argument must be specified if any of the other arguments in this group are specified.

Text Search

--text-search-data-fields=[DATA_FIELD_NAME,…]

The data field names to search.

This flag argument must be specified if any of the other arguments in this group are specified.

--text-search-text=TEXT_SEARCH_TEXT

The query text for text search.

This flag argument must be specified if any of the other arguments in this group are specified.

Vector Search

--vector-from-file=VECTOR_FROM_FILE

Path to a JSON file containing dense or sparse vector to search with.

This flag argument must be specified if any of the other arguments in this group are specified.

--vector-search-field=VECTOR_SEARCH_FIELD

The vector field to search.

This flag argument must be specified if any of the other arguments in this group are specified.

--distance-metric=DISTANCE_METRIC

The distance metric to use for the KNN search. If not specified, dot-product will be used as the default. DISTANCE_METRIC must be one of:

cosine-distance

Cosine distance metric.

dot-product

Dot product distance metric.

OPTIONAL FLAGS

--json-filter=JSON_FILTER

A filter expression in JSON format to apply to the search, e.g. '{"genre": {"$eq": "sci-fi"}}'.

--top-k=TOP_K

The number of nearest neighbors to return. Default is 10.

Output fields

--output-data-fields=[DATA_OUTPUT_FIELD,…]

List of data fields to include in the output. Use * to include all data fields.

--output-metadata-fields=[METADATA_OUTPUT_FIELD,…]

List of metadata fields to include in the output. Use * to include all metadata fields.

--output-vector-fields=[VECTOR_OUTPUT_FIELD,…]

List of vector fields to include in the output. Use * to include all vector fields.

Search Hint

At most one of these can be specified:

--use-knn

If set to true, the search will use the system's default K-Nearest Neighbor (KNN) index engine.

This flag is compatible only with Semantic Search and Vector Search.

Or at least one of these can be specified:

Use Index Options

--use-index=INDEX_NAME

The resource name of the index to use for the search.

This flag is compatible only with Semantic Search and Vector Search.

This flag argument must be specified if any of the other arguments in this group are specified.

--dense-scann-initial-candidate-count=CANDIDATE_COUNT

The number of initial candidates for dense ScaNN.

--dense-scann-search-leaves-pct=PERCENTAGE

The percentage of leaves to search for dense ScaNN, in the range [0, 100].

GCLOUD WIDE FLAGS

These flags are available to all commands: --access-token-file, --account, --billing-project, --configuration, --flags-file, --flatten, --format, --help, --impersonate-service-account, --log-http, --project, --quiet, --trace-token, --user-output-enabled, --verbosity.

Run $ gcloud help for details.

NOTES

This command is currently in beta and might change without notice.