REST Resource: projects.locations.collections

Resource: Collection

Message describing Collection object

JSON representation 
{
  "name": string,
  "displayName": string,
  "description": string,
  "createTime": string,
  "updateTime": string,
  "labels": {
    string: string,
    ...
  },
  "schema": {
    object
  },
  "vectorSchema": {
    string: {
      object (VectorField)
    },
    ...
  },
  "dataSchema": {
    object
  }
}
Fields
name

string

Identifier. name of resource
displayName

string

Optional. User-specified display name of the collection
description

string

Optional. User-specified description of the collection
createTime

string (Timestamp format)

Output only. [Output only] Create time stamp

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".
updateTime

string (Timestamp format)

Output only. [Output only] Update time stamp

Uses RFC 3339, where generated output will always be Z-normalized and use 0, 3, 6 or 9 fractional digits. Offsets other than "Z" are also accepted. Examples: "2014-10-02T15:01:23Z", "2014-10-02T15:01:23.045123456Z" or "2014-10-02T15:01:23+05:30".
labels

map (key: string, value: string)

Optional. Labels as key value pairs.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.
schema
(deprecated)

object (Struct format)

Optional. Deprecated: JSON Schema for data. Please use dataSchema instead.
vectorSchema

map (key: string, value: object (VectorField))

Optional. Schema for vector fields. Only vector fields in this schema will be searchable. Field names must contain only alphanumeric characters, underscores, and hyphens.

An object containing a list of "key": value pairs. Example: { "name": "wrench", "mass": "1.3kg", "count": "3" }.
dataSchema

object (Struct format)

Optional. JSON Schema for data. Field names must contain only alphanumeric characters, underscores, and hyphens.

VectorField

Message describing a vector field.

JSON representation 
{

  // Union field vector_type_config can be only one of the following:
  "denseVector": {
    object (DenseVectorField)
  },
  "sparseVector": {
    object (SparseVectorField)
  }
  // End of list of possible types for union field vector_type_config.
}
Fields
Union field vector_type_config. Vector type configuration. vector_type_config can be only one of the following:
denseVector

object (DenseVectorField)

Dense vector field.
sparseVector

object (SparseVectorField)

Sparse vector field.

DenseVectorField

Message describing a dense vector field.

JSON representation 
{
  "dimensions": integer,
  "vertexEmbeddingConfig": {
    object (VertexEmbeddingConfig)
  }
}
Fields
dimensions

integer

Dimensionality of the vector field.
vertexEmbeddingConfig

object (VertexEmbeddingConfig)

Optional. Configuration for generating embeddings for the vector field. If not specified, the embedding field must be populated in the DataObject.

VertexEmbeddingConfig

Message describing the configuration for generating embeddings for a vector field using Vertex AI embeddings API.

JSON representation 
{
  "modelId": string,
  "textTemplate": string,
  "taskType": enum (EmbeddingTaskType)
}
Fields
modelId

string

Required. 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.
textTemplate

string

Required. 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}".
taskType

enum (EmbeddingTaskType)

Required. Required: Task type for the embeddings.

EmbeddingTaskType

Represents the task the embeddings will be used for.

Enums
EMBEDDING_TASK_TYPE_UNSPECIFIED Unspecified task type.
RETRIEVAL_QUERY Specifies the given text is a query in a search/retrieval setting.
RETRIEVAL_DOCUMENT Specifies the given text is a document from the corpus being searched.
SEMANTIC_SIMILARITY Specifies the given text will be used for STS.
CLASSIFICATION Specifies that the given text will be classified.
CLUSTERING Specifies that the embeddings will be used for clustering.
QUESTION_ANSWERING Specifies that the embeddings will be used for question answering.
FACT_VERIFICATION Specifies that the embeddings will be used for fact verification.
CODE_RETRIEVAL_QUERY Specifies that the embeddings will be used for code retrieval.

SparseVectorField

This type has no fields.

Message describing a sparse vector field.

Methods

create

 Creates a new Collection in a given project and location.

delete

 Deletes a single Collection.

exportDataObjects

 Initiates a Long-Running Operation to export DataObjects from a Collection.

get

 Gets details of a single Collection.

importDataObjects

 Initiates a Long-Running Operation to import DataObjects into a Collection.

list

 Lists Collections in a given project and location.

patch

 Updates the parameters of a single Collection.