gcloud: Wed Feb 11 11:28:24 UTC 2026

gcloud/beta/vector-search/collections/create

@@ -0,0 +1,190 @@
+NAME
+    gcloud beta vector-search collections create - create a collection
+
+SYNOPSIS
+    gcloud beta vector-search collections create
+        (COLLECTION : --location=LOCATION) [--async]
+        [--data-schema=DATA_SCHEMA] [--description=DESCRIPTION]
+        [--display-name=DISPLAY_NAME] [--labels=[LABELS,...]]
+        [--request-id=REQUEST_ID] [--schema=SCHEMA]
+        [--vector-schema=[VECTOR_SCHEMA,...]] [GCLOUD_WIDE_FLAG ...]
+
+DESCRIPTION
+    (BETA) Create a collection.
+
+EXAMPLES
+    To create a collection my-collection in project my-project and location
+    us-central1 to store dense embedding vectors with 100 dimensions, run:
+
+        $ gcloud beta vector-search collections create my-collection \
+            --location=us-central1 --display-name='My Collection' \
+            --vector-schema='{"my-embedding-field": {"denseVector":
+         {"dimensions": 100}}}' --project=my-project
+
+    To create a collection my-collection in project my-project and location
+    us-central1 with data schema and vector schema, run:
+
+        $ gcloud beta vector-search collections create my-collection \
+            --location=us-central1 --display-name='My Collection' \
+            --data-schema='{"type":"object","properties":{"year":{"type":"nu\
+        mber"},"genre":{"type":"string"},"director":{"type":"string"},"title\
+        ":{"type":"string"}}}' \
+            --vector-schema='{"plot_embedding":{"denseVector":{"dimensions":\
+        3}},"genre_embedding":{"denseVector":{"dimensions":4}},"sparse_embed\
+        ding":{"sparseVector":{}}}' --project=my-project
+
+POSITIONAL ARGUMENTS
+     Collection resource - Identifier. name of resource The arguments in this
+     group can be used to specify the attributes of this resource. (NOTE) Some
+     attributes are not given arguments in this group but can be set in other
+     ways.
+
+     To set the project attribute:
+      ◆ provide the argument collection on the command line with a fully
+        specified name;
+      ◆ provide the argument --project on the command line;
+      ◆ set the property core/project.
+
+     This must be specified.
+
+       COLLECTION
+          ID of the collection or fully qualified identifier for the
+          collection.
+
+          To set the collection attribute:
+          ▸ provide the argument collection on the command line.
+
+          This positional argument must be specified if any of the other
+          arguments in this group are specified.
+
+       --location=LOCATION
+          The location id of the collection resource.
+
+          To set the location attribute:
+          ▸ provide the argument collection on the command line with a fully
+            specified name;
+          ▸ provide the argument --location on the command line.
+
+FLAGS
+     --async
+        Return immediately, without waiting for the operation in progress to
+        complete.
+
+     --data-schema=DATA_SCHEMA
+        JSON Schema for data. Field names must contain only alphanumeric
+        characters, underscores, and hyphens.
+
+     --description=DESCRIPTION
+        User-specified description of the collection
+
+     --display-name=DISPLAY_NAME
+        User-specified display name of the collection
+
+     --labels=[LABELS,...]
+        Labels as key value pairs.
+
+         KEY
+            Keys must start with a lowercase character and contain only hyphens
+            (-), underscores (_), lowercase characters, and numbers.
+
+         VALUE
+            Values must contain only hyphens (-), underscores (_), lowercase
+            characters, and numbers.
+
+        Shorthand Example:
+
+            --labels=string=string
+
+        JSON Example:
+
+            --labels='{"string": "string"}'
+
+        File Example:
+
+            --labels=path_to_file.(yaml|json)
+
+     --request-id=REQUEST_ID
+        An optional request ID to identify requests. Specify a unique request
+        ID so that if you must retry your request, the server will know to
+        ignore the request if it has already been completed. The server will
+        guarantee that for at least 60 minutes since the first request.
+
+        For example, consider a situation where you make an initial request and
+        the request times out. If you make the request again with the same
+        request ID, the server can check if original operation with the same
+        request ID was received, and if so, will ignore the second request.
+        This prevents clients from accidentally creating duplicate commitments.
+
+        The request ID must be a valid UUID with the exception that zero UUID
+        is not supported (00000000-0000-0000-0000-000000000000).
+
+     --schema=SCHEMA
+        Deprecated: JSON Schema for data. Please use data_schema instead.
+
+     --vector-schema=[VECTOR_SCHEMA,...]
+        Schema for vector fields. Only vector fields in this schema will be
+        searchable. Field names must contain only alphanumeric characters,
+        underscores, and hyphens.
+
+         KEY
+            Sets KEY value.
+
+         VALUE
+            Sets VALUE value.
+
+             denseVector
+                Dense vector field.
+
+                 dimensions
+                    Dimensionality of the vector field.
+
+                 vertexEmbeddingConfig
+                    Configuration for generating embeddings for the vector
+                    field. If not specified, the embedding field must be
+                    populated in the DataObject.
+
+                     modelId
+                        Required: ID of the embedding model to use. See
+                        https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#embeddings-models
+                        for the list of supported models.
+
+                     taskType
+                        Required: Task type for the embeddings.
+
+                     textTemplate
+                        Required: Text template for the input to the model. The
+                        template must contain one or more references to fields
+                        in the DataObject, e.g.: "Movie Title: {title} ----
+                        Movie Plot: {plot}".
+
+             sparseVector
+                Sparse vector field.
+
+        Shorthand Example:
+
+            --vector-schema=string={denseVector={dimensions=int,vertexEmbeddingConfig={modelId=string,taskType=string,textTemplate=string}},sparseVector}
+
+        JSON Example:
+
+            --vector-schema='{"string": {"denseVector": {"dimensions": int, "vertexEmbeddingConfig": {"modelId": "string", "taskType": "string", "textTemplate": "string"}}, "sparseVector": {}}}'
+
+        File Example:
+
+            --vector-schema=path_to_file.(yaml|json)
+
+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.
+
+API REFERENCE
+    This command uses the vectorsearch/v1beta API. The full documentation for
+    this API can be found at:
+    https://docs.cloud.google.com/vertex-ai/docs/vector-search-2/overview
+
+NOTES
+    This command is currently in beta and might change without notice.
+