AiSearchIndex

laktory.models.resources.databricks.AiSearchIndex

Bases: AiSearchIndexBase

Databricks AI Search Index

Searchable collection of records hosted on an AI Search endpoint, kept in sync with a source Delta table (DELTA_SYNC) or written to through the API (DIRECT_ACCESS). Replacement of VectorSearchIndex. Can also be declared directly in the indexes of an AiSearchEndpoint.

Examples:

import io

from laktory import models

index_yaml = '''
parent: workspaces/1234567890/endpoints/default
index_id: dev.finance.stock_news_index
primary_key: id
index_type: DELTA_SYNC
delta_sync_index_spec:
  source_table: dev.finance.slv_stock_news
  pipeline_type: TRIGGERED
  embedding_source_columns:
  - name: text
    embedding_model_endpoint: databricks-gte-large-en
'''
index = models.resources.databricks.AiSearchIndex.model_validate_yaml(
    io.StringIO(index_yaml)
)

References

• Databricks AI Search
• Terraform databricks_ai_search_index

BASE	DESCRIPTION
delta_sync_index_spec	Specification for a Delta Sync index. Set when index_type is DELTA_SYNC TYPE: AiSearchIndexDeltaSyncIndexSpec | None | VariableType DEFAULT: None
direct_access_index_spec	Specification for a Direct Access index. Set when index_type is DIRECT_ACCESS TYPE: AiSearchIndexDirectAccessIndexSpec | None | VariableType DEFAULT: None
index_id	The user-supplied Unity Catalog table name for the Index, per AIP-133. The server composes the full Index.name as {parent}/indexes/{index_id}. AIP-133 does not list index_id as a fields-may-be-required entry, so we annotate it OPTIONAL on the wire; the server still rejects empty values with INVALID_PARAMETER_VALUE TYPE: str | None | VariableType DEFAULT: None
index_subtype	The subtype of the index. Set on create and immutable thereafter. Possible values are: FULL_TEXT, HYBRID, VECTOR TYPE: str | None | VariableType DEFAULT: None
index_type	Type of index. Required on create and immutable thereafter. Possible values are: DELTA_SYNC, DIRECT_ACCESS TYPE: str | VariableType
parent	Endpoint hosting the index, in the format workspaces/{workspace_id}/endpoints/{endpoint_id}. Set automatically when declared in the indexes of an endpoint. TYPE: str | VariableType DEFAULT: None
primary_key	Primary key of the index. Set on create and immutable thereafter TYPE: str | VariableType
provider_config	Configure the provider for management through account provider TYPE: AiSearchIndexProviderConfig | None | VariableType DEFAULT: None

---

laktory.models.resources.databricks.aisearchindex.AiSearchIndexDeltaSyncIndexSpec

Bases: BaseModel

PARAMETER	DESCRIPTION
columns_to_sync	[Optional] Select the columns to sync with the index. If left blank, all columns from the source table are synced. The primary key column and embedding source or vector column are always synced TYPE: list[str] | None | VariableType DEFAULT: None
embedding_source_columns	The columns that contain the embedding source TYPE: list[AiSearchIndexDeltaSyncIndexSpecEmbeddingSourceColumns] | None | VariableType DEFAULT: None
embedding_vector_columns	The columns that contain the embedding vectors TYPE: list[AiSearchIndexDeltaSyncIndexSpecEmbeddingVectorColumns] | None | VariableType DEFAULT: None
embedding_writeback_table	[Optional] Name of the Delta table to sync the index contents and computed embeddings to TYPE: str | None | VariableType DEFAULT: None
pipeline_type	Pipeline execution mode. Required on create — the backend rejects an unset value. Storage Optimized endpoints accept only TRIGGERED; Standard endpoints accept both. No explicit stage — a REQUIRED field staged below its service would be dropped from combined specs while remaining in required, tripping the OpenAPI required-vs-properties consistency check. The field inherits the service's launch stage. Possible values are: CONTINUOUS, TRIGGERED TYPE: str | VariableType
source_table	The full name of the source Delta table TYPE: str | None | VariableType DEFAULT: None

---

laktory.models.resources.databricks.aisearchindex.AiSearchIndexDeltaSyncIndexSpecEmbeddingSourceColumns

Bases: BaseModel

PARAMETER	DESCRIPTION
embedding_model_endpoint	Name of the embedding model endpoint, used by default for both ingestion and querying TYPE: str | None | VariableType DEFAULT: None
model_endpoint_name_for_query	Name of the embedding model endpoint which, if specified, is used for querying (not ingestion) TYPE: str | None | VariableType DEFAULT: None
name	Name of the AI Search index. Server-assigned full resource path (workspaces/{workspace}/endpoints/{endpoint}/indexes/{index}) on output, where {index} is the index's Unity Catalog table name. On create, the user-supplied UC table name is conveyed via CreateIndexRequest.index_id; the server composes the full name and returns it on the response TYPE: str | None | VariableType DEFAULT: None

---

laktory.models.resources.databricks.aisearchindex.AiSearchIndexDeltaSyncIndexSpecEmbeddingVectorColumns

Bases: BaseModel

PARAMETER	DESCRIPTION
embedding_dimension	Dimension of the embedding vector TYPE: int | None | VariableType DEFAULT: None
name	Name of the AI Search index. Server-assigned full resource path (workspaces/{workspace}/endpoints/{endpoint}/indexes/{index}) on output, where {index} is the index's Unity Catalog table name. On create, the user-supplied UC table name is conveyed via CreateIndexRequest.index_id; the server composes the full name and returns it on the response TYPE: str | None | VariableType DEFAULT: None

---

laktory.models.resources.databricks.aisearchindex.AiSearchIndexDirectAccessIndexSpec

Bases: BaseModel

PARAMETER	DESCRIPTION
embedding_source_columns	The columns that contain the embedding source TYPE: list[AiSearchIndexDirectAccessIndexSpecEmbeddingSourceColumns] | None | VariableType DEFAULT: None
embedding_vector_columns	The columns that contain the embedding vectors TYPE: list[AiSearchIndexDirectAccessIndexSpecEmbeddingVectorColumns] | None | VariableType DEFAULT: None
schema_json_	The schema of the index in JSON format. Supported types are integer, long, float, double, boolean, string, date, timestamp. Supported types for vector columns: array<float>, array<double> TYPE: str | None | VariableType DEFAULT: None

---

laktory.models.resources.databricks.aisearchindex.AiSearchIndexDirectAccessIndexSpecEmbeddingSourceColumns

Bases: BaseModel

PARAMETER	DESCRIPTION
embedding_model_endpoint	Name of the embedding model endpoint, used by default for both ingestion and querying TYPE: str | None | VariableType DEFAULT: None
model_endpoint_name_for_query	Name of the embedding model endpoint which, if specified, is used for querying (not ingestion) TYPE: str | None | VariableType DEFAULT: None
name	Name of the AI Search index. Server-assigned full resource path (workspaces/{workspace}/endpoints/{endpoint}/indexes/{index}) on output, where {index} is the index's Unity Catalog table name. On create, the user-supplied UC table name is conveyed via CreateIndexRequest.index_id; the server composes the full name and returns it on the response TYPE: str | None | VariableType DEFAULT: None

---

laktory.models.resources.databricks.aisearchindex.AiSearchIndexDirectAccessIndexSpecEmbeddingVectorColumns

Bases: BaseModel

PARAMETER	DESCRIPTION
embedding_dimension	Dimension of the embedding vector TYPE: int | None | VariableType DEFAULT: None
name	Name of the AI Search index. Server-assigned full resource path (workspaces/{workspace}/endpoints/{endpoint}/indexes/{index}) on output, where {index} is the index's Unity Catalog table name. On create, the user-supplied UC table name is conveyed via CreateIndexRequest.index_id; the server composes the full name and returns it on the response TYPE: str | None | VariableType DEFAULT: None

---

laktory.models.resources.databricks.aisearchindex.AiSearchIndexProviderConfig

Bases: BaseModel

PARAMETER	DESCRIPTION
workspace_id	Workspace ID which the resource belongs to. This workspace must be part of the account which the provider is configured with TYPE: str | None | VariableType DEFAULT: None