Summary of entries of Classes for langchain-google-spanner.
Classes
SpannerChatMessageHistory
Chat message history that stores history in Spanner.
Column
Column(name: str, data_type: str, nullable: bool = True)
SpannerDocumentSaver
Save docs to Google Cloud Spanner.
SpannerLoader
Loads data from Google Cloud Spanner.
DialectSemantics
Abstract base class for dialect semantics.
DistanceStrategy
Enum for distance calculation strategies.
GoogleSqlSemnatics
Implementation of dialect semantics for Google SQL.
PGSqlSemnatics
Implementation of dialect semantics for PostgreSQL.
QueryParameters
Class representing query parameters for nearest neighbors search.
NearestNeighborsAlgorithm
Enum for nearest neighbors search algorithms.
SecondaryIndex
SecondaryIndex(index_name: 'str', columns: 'list[str]', storing_columns: 'Optional[list[str]]' = None)
SpannerVectorStore
Initialize the SpannerVectorStore.
Parameters:
- instance_id (str): The ID of the Spanner instance.
- database_id (str): The ID of the Spanner database.
- table_name (str): The name of the table.
- embedding_service (Embeddings): The embedding service.
- id_column (str): The name of the row ID column. Defaults to ID_COLUMN_NAME.
- content_column (str): The name of the content column. Defaults to CONTENT_COLUMN_NAME.
- embedding_column (str): The name of the embedding column. Defaults to EMBEDDING_COLUMN_NAME.
- client (Client): The Spanner client. Defaults to Client().
- metadata_columns (Optional[List[str]]): List of metadata columns. Defaults to None.
- ignore_metadata_columns (Optional[List[str]]): List of metadata columns to ignore. Defaults to None.
- metadata_json_column (Optional[str]): The generic metadata column. Defaults to None.
- query_parameters (QueryParameters): The query parameters. Defaults to QueryParameters().
TableColumn
Represents column configuration, to be used as part of create DDL statement for table creation.
Modules
chat_message_history
Cloud Spanner-based chat message history
loader
API documentation for loader module.
vector_store
API documentation for vector_store module.