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vertex_ai_index

vertex_ai_index represents the google_vertex_ai_index Terraform resource.

This package contains functions and utilities for setting up the resource using Jsonnet code.

Index

Fields

fn new

new()

google.vertex_ai_index.new injects a new google_vertex_ai_index Terraform resource block into the root module document.

Additionally, this inserts a private function into the _ref attribute that generates references to attributes of the resource. For example, if you added a new instance to the root using:

# arguments omitted for brevity
google.vertex_ai_index.new('some_id')

You can get the reference to the id field of the created google.vertex_ai_index using the reference:

$._ref.google_vertex_ai_index.some_id.get('id')

This is the same as directly entering "${ google_vertex_ai_index.some_id.id }" as the value.

NOTE: if you are chaining multiple resources together in a merge operation, you may not be able to use super, self, or $ to refer to the root object. Instead, make an explicit outer object using local.

Args:

  • resourceLabel (string): The name label of the block.
  • description (string): The description of the Index. When null, the description field will be omitted from the resulting object.
  • display_name (string): The display name of the Index. The name can be up to 128 characters long and can consist of any UTF-8 characters.
  • index_update_method (string): The update method to use with this Index. The value must be the followings. If not set, BATCH_UPDATE will be used by default.
  • BATCH_UPDATE: user can call indexes.patch with files on Cloud Storage of datapoints to update.
  • STREAM_UPDATE: user can call indexes.upsertDatapoints/DeleteDatapoints to update the Index and the updates will be applied in corresponding DeployedIndexes in nearly real-time. When null, the index_update_method field will be omitted from the resulting object.
    • labels (obj): The labels with user-defined metadata to organize your Indexes. When null, the labels field will be omitted from the resulting object.
    • project (string): Set the project field on the resulting resource block. When null, the project field will be omitted from the resulting object.
    • region (string): The region of the index. eg us-central1 When null, the region field will be omitted from the resulting object.
    • metadata (list[obj]): An additional information about the Index When null, the metadata sub block will be omitted from the resulting object. When setting the sub block, it is recommended to construct the object using the google.vertex_ai_index.metadata.new constructor.
    • timeouts (obj): Set the timeouts field on the resulting resource block. When null, the timeouts sub block will be omitted from the resulting object. When setting the sub block, it is recommended to construct the object using the google.vertex_ai_index.timeouts.new constructor.

Returns:

  • A mixin object that injects the new resource into the root Terraform configuration.

fn newAttrs

newAttrs()

google.vertex_ai_index.newAttrs constructs a new object with attributes and blocks configured for the vertex_ai_index Terraform resource.

Unlike google.vertex_ai_index.new, this function will not inject the resource block into the root Terraform document. Instead, this must be passed in as the attrs argument for the tf.withResource function to build a complete block.

This is most useful when you need to preprocess the attributes with functions, conditional, or looping logic prior to injecting into a complete block.

Args:

  • description (string): The description of the Index. When null, the description field will be omitted from the resulting object.
  • display_name (string): The display name of the Index. The name can be up to 128 characters long and can consist of any UTF-8 characters.
  • index_update_method (string): The update method to use with this Index. The value must be the followings. If not set, BATCH_UPDATE will be used by default.
  • BATCH_UPDATE: user can call indexes.patch with files on Cloud Storage of datapoints to update.
  • STREAM_UPDATE: user can call indexes.upsertDatapoints/DeleteDatapoints to update the Index and the updates will be applied in corresponding DeployedIndexes in nearly real-time. When null, the index_update_method field will be omitted from the resulting object.
    • labels (obj): The labels with user-defined metadata to organize your Indexes. When null, the labels field will be omitted from the resulting object.
    • project (string): Set the project field on the resulting object. When null, the project field will be omitted from the resulting object.
    • region (string): The region of the index. eg us-central1 When null, the region field will be omitted from the resulting object.
    • metadata (list[obj]): An additional information about the Index When null, the metadata sub block will be omitted from the resulting object. When setting the sub block, it is recommended to construct the object using the google.vertex_ai_index.metadata.new constructor.
    • timeouts (obj): Set the timeouts field on the resulting object. When null, the timeouts sub block will be omitted from the resulting object. When setting the sub block, it is recommended to construct the object using the google.vertex_ai_index.timeouts.new constructor.

Returns:

  • An attribute object that can be used with tf.withResource to construct a new vertex_ai_index resource into the root Terraform configuration.

fn withDescription

withDescription()

google.string.withDescription constructs a mixin object that can be merged into the string Terraform resource block to set or update the description field.

Args:

  • resourceLabel (string): The name label of the block to update.
  • value (string): The value to set for the description field.

fn withDisplayName

withDisplayName()

google.string.withDisplayName constructs a mixin object that can be merged into the string Terraform resource block to set or update the display_name field.

Args:

  • resourceLabel (string): The name label of the block to update.
  • value (string): The value to set for the display_name field.

fn withIndexUpdateMethod

withIndexUpdateMethod()

google.string.withIndexUpdateMethod constructs a mixin object that can be merged into the string Terraform resource block to set or update the index_update_method field.

Args:

  • resourceLabel (string): The name label of the block to update.
  • value (string): The value to set for the index_update_method field.

fn withLabels

withLabels()

google.obj.withLabels constructs a mixin object that can be merged into the obj Terraform resource block to set or update the labels field.

Args:

  • resourceLabel (string): The name label of the block to update.
  • value (obj): The value to set for the labels field.

fn withMetadata

withMetadata()

google.list[obj].withMetadata constructs a mixin object that can be merged into the list[obj] Terraform resource block to set or update the metadata field.

This function will replace the array with the passed in value. If you wish to instead append the passed in value to the existing array, use the google.list[obj].withMetadataMixin function.

Args:

  • resourceLabel (string): The name label of the block to update.
  • value (list[obj]): The value to set for the metadata field.

fn withMetadataMixin

withMetadataMixin()

google.list[obj].withMetadataMixin constructs a mixin object that can be merged into the list[obj] Terraform resource block to set or update the metadata field.

This function will append the passed in array or object to the existing array. If you wish to instead replace the array with the passed in value, use the google.list[obj].withMetadata function.

Args:

  • resourceLabel (string): The name label of the block to update.
  • value (list[obj]): The value to set for the metadata field.

fn withProject

withProject()

google.string.withProject constructs a mixin object that can be merged into the string Terraform resource block to set or update the project field.

Args:

  • resourceLabel (string): The name label of the block to update.
  • value (string): The value to set for the project field.

fn withRegion

withRegion()

google.string.withRegion constructs a mixin object that can be merged into the string Terraform resource block to set or update the region field.

Args:

  • resourceLabel (string): The name label of the block to update.
  • value (string): The value to set for the region field.

fn withTimeouts

withTimeouts()

google.obj.withTimeouts constructs a mixin object that can be merged into the obj Terraform resource block to set or update the timeouts field.

This function will replace the map with the passed in value. If you wish to instead merge the passed in value to the existing map, use the google.obj.withTimeoutsMixin function.

Args:

  • resourceLabel (string): The name label of the block to update.
  • value (obj): The value to set for the timeouts field.

fn withTimeoutsMixin

withTimeoutsMixin()

google.obj.withTimeoutsMixin constructs a mixin object that can be merged into the obj Terraform resource block to set or update the timeouts field.

This function will merge the passed in value to the existing map. If you wish to instead replace the entire map with the passed in value, use the google.obj.withTimeouts function.

Args:

  • resourceLabel (string): The name label of the block to update.
  • value (obj): The value to set for the timeouts field.

obj metadata

fn metadata.new

new()

google.vertex_ai_index.metadata.new constructs a new object with attributes and blocks configured for the metadata Terraform sub block.

Args:

  • contents_delta_uri (string): Allows inserting, updating or deleting the contents of the Matching Engine Index. The string must be a valid Cloud Storage directory path. If this field is set when calling IndexService.UpdateIndex, then no other Index field can be also updated as part of the same call. The expected structure and format of the files this URI points to is described at https://cloud.google.com/vertex-ai/docs/matching-engine/using-matching-engine#input-data-format When null, the contents_delta_uri field will be omitted from the resulting object.
  • is_complete_overwrite (bool): If this field is set together with contentsDeltaUri when calling IndexService.UpdateIndex, then existing content of the Index will be replaced by the data from the contentsDeltaUri. When null, the is_complete_overwrite field will be omitted from the resulting object.
  • config (list[obj]): The configuration of the Matching Engine Index. When null, the config sub block will be omitted from the resulting object. When setting the sub block, it is recommended to construct the object using the google.vertex_ai_index.metadata.config.new constructor.

Returns:

  • An attribute object that represents the metadata sub block.

obj metadata.config

fn metadata.config.new

new()

google.vertex_ai_index.metadata.config.new constructs a new object with attributes and blocks configured for the config Terraform sub block.

Args:

  • approximate_neighbors_count (number): The default number of neighbors to find via approximate search before exact reordering is performed. Exact reordering is a procedure where results returned by an approximate search algorithm are reordered via a more expensive distance computation. Required if tree-AH algorithm is used. When null, the approximate_neighbors_count field will be omitted from the resulting object.
  • dimensions (number): The number of dimensions of the input vectors.
  • distance_measure_type (string): The distance measure used in nearest neighbor search. The value must be one of the followings:
  • SQUARED_L2_DISTANCE: Euclidean (L_2) Distance
  • L1_DISTANCE: Manhattan (L_1) Distance
  • COSINE_DISTANCE: Cosine Distance. Defined as 1 - cosine similarity.
  • DOT_PRODUCT_DISTANCE: Dot Product Distance. Defined as a negative of the dot product When null, the distance_measure_type field will be omitted from the resulting object.
    • feature_norm_type (string): Type of normalization to be carried out on each vector. The value must be one of the followings:
  • UNIT_L2_NORM: Unit L2 normalization type
  • NONE: No normalization type is specified. When null, the feature_norm_type field will be omitted from the resulting object.
    • shard_size (string): Index data is split into equal parts to be processed. These are called "shards". The shard size must be specified when creating an index. The value must be one of the followings:
  • SHARD_SIZE_SMALL: Small (2GB)
  • SHARD_SIZE_MEDIUM: Medium (20GB)
  • SHARD_SIZE_LARGE: Large (50GB) When null, the shard_size field will be omitted from the resulting object.
    • algorithm_config (list[obj]): The configuration with regard to the algorithms used for efficient search. When null, the algorithm_config sub block will be omitted from the resulting object. When setting the sub block, it is recommended to construct the object using the google.vertex_ai_index.metadata.config.algorithm_config.new constructor.

Returns:

  • An attribute object that represents the config sub block.

obj metadata.config.algorithm_config

fn metadata.config.algorithm_config.new

new()

google.vertex_ai_index.metadata.config.algorithm_config.new constructs a new object with attributes and blocks configured for the algorithm_config Terraform sub block.

Args:

Returns:

  • An attribute object that represents the algorithm_config sub block.

obj metadata.config.algorithm_config.brute_force_config

fn metadata.config.algorithm_config.brute_force_config.new

new()

google.vertex_ai_index.metadata.config.algorithm_config.brute_force_config.new constructs a new object with attributes and blocks configured for the brute_force_config Terraform sub block.

Returns:

  • An attribute object that represents the brute_force_config sub block.

obj metadata.config.algorithm_config.tree_ah_config

fn metadata.config.algorithm_config.tree_ah_config.new

new()

google.vertex_ai_index.metadata.config.algorithm_config.tree_ah_config.new constructs a new object with attributes and blocks configured for the tree_ah_config Terraform sub block.

Args:

  • leaf_node_embedding_count (number): Number of embeddings on each leaf node. The default value is 1000 if not set. When null, the leaf_node_embedding_count field will be omitted from the resulting object.
  • leaf_nodes_to_search_percent (number): The default percentage of leaf nodes that any query may be searched. Must be in range 1-100, inclusive. The default value is 10 (means 10%) if not set. When null, the leaf_nodes_to_search_percent field will be omitted from the resulting object.

Returns:

  • An attribute object that represents the tree_ah_config sub block.

obj timeouts

fn timeouts.new

new()

google.vertex_ai_index.timeouts.new constructs a new object with attributes and blocks configured for the timeouts Terraform sub block.

Args:

  • create (string): Set the create field on the resulting object. When null, the create field will be omitted from the resulting object.
  • delete (string): Set the delete field on the resulting object. When null, the delete field will be omitted from the resulting object.
  • update (string): Set the update field on the resulting object. When null, the update field will be omitted from the resulting object.

Returns:

  • An attribute object that represents the timeouts sub block.