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Google Cloud Classic v7.19.0 published on Thursday, Apr 18, 2024 by Pulumi

gcp.vertex.getAiIndex

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Google Cloud Classic v7.19.0 published on Thursday, Apr 18, 2024 by Pulumi

    A representation of a collection of database items organized in a way that allows for approximate nearest neighbor (a.k.a ANN) algorithms search.

    Using getAiIndex

    Two invocation forms are available. The direct form accepts plain arguments and either blocks until the result value is available, or returns a Promise-wrapped result. The output form accepts Input-wrapped arguments and returns an Output-wrapped result.

    function getAiIndex(args: GetAiIndexArgs, opts?: InvokeOptions): Promise<GetAiIndexResult>
    function getAiIndexOutput(args: GetAiIndexOutputArgs, opts?: InvokeOptions): Output<GetAiIndexResult>
    def get_ai_index(name: Optional[str] = None,
                     project: Optional[str] = None,
                     region: Optional[str] = None,
                     opts: Optional[InvokeOptions] = None) -> GetAiIndexResult
    def get_ai_index_output(name: Optional[pulumi.Input[str]] = None,
                     project: Optional[pulumi.Input[str]] = None,
                     region: Optional[pulumi.Input[str]] = None,
                     opts: Optional[InvokeOptions] = None) -> Output[GetAiIndexResult]
    func LookupAiIndex(ctx *Context, args *LookupAiIndexArgs, opts ...InvokeOption) (*LookupAiIndexResult, error)
    func LookupAiIndexOutput(ctx *Context, args *LookupAiIndexOutputArgs, opts ...InvokeOption) LookupAiIndexResultOutput

    > Note: This function is named LookupAiIndex in the Go SDK.

    public static class GetAiIndex 
    {
        public static Task<GetAiIndexResult> InvokeAsync(GetAiIndexArgs args, InvokeOptions? opts = null)
        public static Output<GetAiIndexResult> Invoke(GetAiIndexInvokeArgs args, InvokeOptions? opts = null)
    }
    public static CompletableFuture<GetAiIndexResult> getAiIndex(GetAiIndexArgs args, InvokeOptions options)
    // Output-based functions aren't available in Java yet
    
    fn::invoke:
      function: gcp:vertex/getAiIndex:getAiIndex
      arguments:
        # arguments dictionary

    The following arguments are supported:

    Name string
    The name of the index.
    Region string
    The region of the index.


    Project string
    The ID of the project in which the resource belongs.
    Name string
    The name of the index.
    Region string
    The region of the index.


    Project string
    The ID of the project in which the resource belongs.
    name String
    The name of the index.
    region String
    The region of the index.


    project String
    The ID of the project in which the resource belongs.
    name string
    The name of the index.
    region string
    The region of the index.


    project string
    The ID of the project in which the resource belongs.
    name str
    The name of the index.
    region str
    The region of the index.


    project str
    The ID of the project in which the resource belongs.
    name String
    The name of the index.
    region String
    The region of the index.


    project String
    The ID of the project in which the resource belongs.

    getAiIndex Result

    The following output properties are available:

    CreateTime string
    DeployedIndexes List<GetAiIndexDeployedIndex>
    Description string
    DisplayName string
    EffectiveLabels Dictionary<string, string>
    Etag string
    Id string
    The provider-assigned unique ID for this managed resource.
    IndexStats List<GetAiIndexIndexStat>
    IndexUpdateMethod string
    Labels Dictionary<string, string>
    MetadataSchemaUri string
    Metadatas List<GetAiIndexMetadata>
    Name string
    PulumiLabels Dictionary<string, string>
    Region string
    UpdateTime string
    Project string
    CreateTime string
    DeployedIndexes []GetAiIndexDeployedIndex
    Description string
    DisplayName string
    EffectiveLabels map[string]string
    Etag string
    Id string
    The provider-assigned unique ID for this managed resource.
    IndexStats []GetAiIndexIndexStat
    IndexUpdateMethod string
    Labels map[string]string
    MetadataSchemaUri string
    Metadatas []GetAiIndexMetadata
    Name string
    PulumiLabels map[string]string
    Region string
    UpdateTime string
    Project string
    createTime String
    deployedIndexes List<GetAiIndexDeployedIndex>
    description String
    displayName String
    effectiveLabels Map<String,String>
    etag String
    id String
    The provider-assigned unique ID for this managed resource.
    indexStats List<GetAiIndexIndexStat>
    indexUpdateMethod String
    labels Map<String,String>
    metadataSchemaUri String
    metadatas List<GetAiIndexMetadata>
    name String
    pulumiLabels Map<String,String>
    region String
    updateTime String
    project String
    createTime string
    deployedIndexes GetAiIndexDeployedIndex[]
    description string
    displayName string
    effectiveLabels {[key: string]: string}
    etag string
    id string
    The provider-assigned unique ID for this managed resource.
    indexStats GetAiIndexIndexStat[]
    indexUpdateMethod string
    labels {[key: string]: string}
    metadataSchemaUri string
    metadatas GetAiIndexMetadata[]
    name string
    pulumiLabels {[key: string]: string}
    region string
    updateTime string
    project string
    createTime String
    deployedIndexes List<Property Map>
    description String
    displayName String
    effectiveLabels Map<String>
    etag String
    id String
    The provider-assigned unique ID for this managed resource.
    indexStats List<Property Map>
    indexUpdateMethod String
    labels Map<String>
    metadataSchemaUri String
    metadatas List<Property Map>
    name String
    pulumiLabels Map<String>
    region String
    updateTime String
    project String

    Supporting Types

    GetAiIndexDeployedIndex

    DeployedIndexId string
    The ID of the DeployedIndex in the above IndexEndpoint.
    IndexEndpoint string
    A resource name of the IndexEndpoint.
    DeployedIndexId string
    The ID of the DeployedIndex in the above IndexEndpoint.
    IndexEndpoint string
    A resource name of the IndexEndpoint.
    deployedIndexId String
    The ID of the DeployedIndex in the above IndexEndpoint.
    indexEndpoint String
    A resource name of the IndexEndpoint.
    deployedIndexId string
    The ID of the DeployedIndex in the above IndexEndpoint.
    indexEndpoint string
    A resource name of the IndexEndpoint.
    deployed_index_id str
    The ID of the DeployedIndex in the above IndexEndpoint.
    index_endpoint str
    A resource name of the IndexEndpoint.
    deployedIndexId String
    The ID of the DeployedIndex in the above IndexEndpoint.
    indexEndpoint String
    A resource name of the IndexEndpoint.

    GetAiIndexIndexStat

    ShardsCount int
    The number of shards in the Index.
    VectorsCount string
    The number of vectors in the Index.
    ShardsCount int
    The number of shards in the Index.
    VectorsCount string
    The number of vectors in the Index.
    shardsCount Integer
    The number of shards in the Index.
    vectorsCount String
    The number of vectors in the Index.
    shardsCount number
    The number of shards in the Index.
    vectorsCount string
    The number of vectors in the Index.
    shards_count int
    The number of shards in the Index.
    vectors_count str
    The number of vectors in the Index.
    shardsCount Number
    The number of shards in the Index.
    vectorsCount String
    The number of vectors in the Index.

    GetAiIndexMetadata

    Configs List<GetAiIndexMetadataConfig>
    The configuration of the Matching Engine Index.
    ContentsDeltaUri 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
    IsCompleteOverwrite 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.
    Configs []GetAiIndexMetadataConfig
    The configuration of the Matching Engine Index.
    ContentsDeltaUri 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
    IsCompleteOverwrite 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.
    configs List<GetAiIndexMetadataConfig>
    The configuration of the Matching Engine Index.
    contentsDeltaUri 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
    isCompleteOverwrite Boolean
    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.
    configs GetAiIndexMetadataConfig[]
    The configuration of the Matching Engine Index.
    contentsDeltaUri 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
    isCompleteOverwrite boolean
    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.
    configs Sequence[GetAiIndexMetadataConfig]
    The configuration of the Matching Engine Index.
    contents_delta_uri str
    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
    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.
    configs List<Property Map>
    The configuration of the Matching Engine Index.
    contentsDeltaUri 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
    isCompleteOverwrite Boolean
    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.

    GetAiIndexMetadataConfig

    AlgorithmConfigs List<GetAiIndexMetadataConfigAlgorithmConfig>
    The configuration with regard to the algorithms used for efficient search.
    ApproximateNeighborsCount int
    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.
    Dimensions int
    The number of dimensions of the input vectors.
    DistanceMeasureType 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
    FeatureNormType 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.
    ShardSize 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)
    AlgorithmConfigs []GetAiIndexMetadataConfigAlgorithmConfig
    The configuration with regard to the algorithms used for efficient search.
    ApproximateNeighborsCount int
    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.
    Dimensions int
    The number of dimensions of the input vectors.
    DistanceMeasureType 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
    FeatureNormType 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.
    ShardSize 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)
    algorithmConfigs List<GetAiIndexMetadataConfigAlgorithmConfig>
    The configuration with regard to the algorithms used for efficient search.
    approximateNeighborsCount Integer
    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.
    dimensions Integer
    The number of dimensions of the input vectors.
    distanceMeasureType 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
    featureNormType 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.
    shardSize 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)
    algorithmConfigs GetAiIndexMetadataConfigAlgorithmConfig[]
    The configuration with regard to the algorithms used for efficient search.
    approximateNeighborsCount 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.
    dimensions number
    The number of dimensions of the input vectors.
    distanceMeasureType 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
    featureNormType 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.
    shardSize 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)
    algorithm_configs Sequence[GetAiIndexMetadataConfigAlgorithmConfig]
    The configuration with regard to the algorithms used for efficient search.
    approximate_neighbors_count int
    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.
    dimensions int
    The number of dimensions of the input vectors.
    distance_measure_type str
    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
    feature_norm_type str
    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.
    shard_size str
    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)
    algorithmConfigs List<Property Map>
    The configuration with regard to the algorithms used for efficient search.
    approximateNeighborsCount 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.
    dimensions Number
    The number of dimensions of the input vectors.
    distanceMeasureType 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
    featureNormType 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.
    shardSize 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)

    GetAiIndexMetadataConfigAlgorithmConfig

    BruteForceConfigs List<GetAiIndexMetadataConfigAlgorithmConfigBruteForceConfig>
    Configuration options for using brute force search, which simply implements the standard linear search in the database for each query.
    TreeAhConfigs List<GetAiIndexMetadataConfigAlgorithmConfigTreeAhConfig>
    Configuration options for using the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396
    BruteForceConfigs []GetAiIndexMetadataConfigAlgorithmConfigBruteForceConfig
    Configuration options for using brute force search, which simply implements the standard linear search in the database for each query.
    TreeAhConfigs []GetAiIndexMetadataConfigAlgorithmConfigTreeAhConfig
    Configuration options for using the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396
    bruteForceConfigs List<GetAiIndexMetadataConfigAlgorithmConfigBruteForceConfig>
    Configuration options for using brute force search, which simply implements the standard linear search in the database for each query.
    treeAhConfigs List<GetAiIndexMetadataConfigAlgorithmConfigTreeAhConfig>
    Configuration options for using the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396
    bruteForceConfigs GetAiIndexMetadataConfigAlgorithmConfigBruteForceConfig[]
    Configuration options for using brute force search, which simply implements the standard linear search in the database for each query.
    treeAhConfigs GetAiIndexMetadataConfigAlgorithmConfigTreeAhConfig[]
    Configuration options for using the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396
    brute_force_configs Sequence[GetAiIndexMetadataConfigAlgorithmConfigBruteForceConfig]
    Configuration options for using brute force search, which simply implements the standard linear search in the database for each query.
    tree_ah_configs Sequence[GetAiIndexMetadataConfigAlgorithmConfigTreeAhConfig]
    Configuration options for using the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396
    bruteForceConfigs List<Property Map>
    Configuration options for using brute force search, which simply implements the standard linear search in the database for each query.
    treeAhConfigs List<Property Map>
    Configuration options for using the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396

    GetAiIndexMetadataConfigAlgorithmConfigTreeAhConfig

    LeafNodeEmbeddingCount int
    Number of embeddings on each leaf node. The default value is 1000 if not set.
    LeafNodesToSearchPercent int
    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.
    LeafNodeEmbeddingCount int
    Number of embeddings on each leaf node. The default value is 1000 if not set.
    LeafNodesToSearchPercent int
    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.
    leafNodeEmbeddingCount Integer
    Number of embeddings on each leaf node. The default value is 1000 if not set.
    leafNodesToSearchPercent Integer
    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.
    leafNodeEmbeddingCount number
    Number of embeddings on each leaf node. The default value is 1000 if not set.
    leafNodesToSearchPercent 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.
    leaf_node_embedding_count int
    Number of embeddings on each leaf node. The default value is 1000 if not set.
    leaf_nodes_to_search_percent int
    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.
    leafNodeEmbeddingCount Number
    Number of embeddings on each leaf node. The default value is 1000 if not set.
    leafNodesToSearchPercent 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.

    Package Details

    Repository
    Google Cloud (GCP) Classic pulumi/pulumi-gcp
    License
    Apache-2.0
    Notes
    This Pulumi package is based on the google-beta Terraform Provider.
    gcp logo
    Google Cloud Classic v7.19.0 published on Thursday, Apr 18, 2024 by Pulumi