Class PostgresEngine (0.6.0)

PostgresEngine(
    engine: sqlalchemy.ext.asyncio.engine.AsyncEngine,
    loop: typing.Optional[asyncio.events.AbstractEventLoop],
    thread: typing.Optional[threading.Thread],
)

A class for managing connections to a Cloud SQL for Postgres database.

Methods

_aexecute

_aexecute(query: str, params: typing.Optional[dict] = None)

Execute a SQL query.

_aexecute_outside_tx

_aexecute_outside_tx(query: str)

Execute a SQL query.

_aload_table_schema

_aload_table_schema(table_name: str) -> sqlalchemy.sql.schema.Table

Load table schema from existing table in PgSQL database.

Returns
Type	Description
`(sqlalchemy.Table)`	The loaded table.

ainit_document_table

ainit_document_table(
    table_name: str,
    content_column: str = "page_content",
    metadata_columns: typing.List[langchain_google_cloud_sql_pg.engine.Column] = [],
    metadata_json_column: str = "langchain_metadata",
    store_metadata: bool = True,
) -> None

Create a table for saving of langchain documents.

Parameters
Name	Description
`table_name`	`str` The PgSQL database table name.
`metadata_columns`	`List[sqlalchemy.Column]` A list of SQLAlchemy Columns to create for custom metadata. Optional.
`store_metadata`	`bool` Whether to store extra metadata in a metadata column if not described in 'metadata' field list (Default: True).

ainit_vectorstore_table

ainit_vectorstore_table(
    table_name: str,
    vector_size: int,
    content_column: str = "content",
    embedding_column: str = "embedding",
    metadata_columns: typing.List[langchain_google_cloud_sql_pg.engine.Column] = [],
    metadata_json_column: str = "langchain_metadata",
    id_column: str = "langchain_id",
    overwrite_existing: bool = False,
    store_metadata: bool = True,
) -> None

Create a table for saving of vectors to be used with PostgresVectorStore.

Parameters
Name	Description
`table_name`	`str` The Postgres database table name.
`vector_size`	`int` Vector size for the embedding model to be used.
`content_column`	`str` Name of the column to store document content. Default: "page_content".
`embedding_column`	`str` Name of the column to store vector embeddings. Default: "embedding".
`metadata_columns`	`List[Column]` A list of Columns to create for custom metadata. Default: []. Optional.
`metadata_json_column`	`str` The column to store extra metadata in JSON format. Default: "langchain_metadata". Optional.
`id_column`	`str` Name of the column to store ids. Default: "langchain_id". Optional,
`overwrite_existing`	`bool` Whether to drop existing table. Default: False.
`store_metadata`	`bool` Whether to store metadata in the table. Default: True.