Class PostgresEngine (0.8.0)

PostgresEngine(
    key: object,
    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

PostgresEngine

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

PostgresEngine constructor.

Parameters
Name	Description
`key`	`object` Prevent direct constructor usage.
`engine`	`AsyncEngine` Async engine connection pool.
`loop`	`Optional[asyncio.AbstractEventLoop]` Async event loop used to create the engine.
`thread`	`Optional[Thread] = None` Thread used to create the engine async.

Exceptions
Type	Description
`Exception`	If the constructor is called directly by the user.

_aexecute

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

Execute a SQL query.

_aexecute_outside_tx

_aexecute_outside_tx(query: str) -> None

Execute a SQL query in a new transaction.

_afetch

_afetch(
    query: str, params: typing.Optional[dict] = None
) -> typing.Sequence[sqlalchemy.engine.row.RowMapping]

Fetch results from a SQL query.

_afetch_with_query_options

_afetch_with_query_options(
    query: str, query_options: str
) -> typing.Sequence[sqlalchemy.engine.row.RowMapping]

Set temporary database flags and fetch results from 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.

_create

_create(
    project_id: str,
    region: str,
    instance: str,
    database: str,
    ip_type: typing.Union[str, google.cloud.sql.connector.enums.IPTypes],
    user: typing.Optional[str] = None,
    password: typing.Optional[str] = None,
    loop: typing.Optional[asyncio.events.AbstractEventLoop] = None,
    thread: typing.Optional[threading.Thread] = None,
    quota_project: typing.Optional[str] = None,
    iam_account_email: typing.Optional[str] = None,
) -> langchain_google_cloud_sql_pg.engine.PostgresEngine

Create a PostgresEngine instance.

Parameters
Name	Description
`project_id`	`str` GCP project ID.
`region`	`str` Postgres instance region.
`instance`	`str` Postgres instance name.
`database`	`str` Database name.
`ip_type`	`Union[str, IPTypes], optional` IP address type. Defaults to IPTypes.PUBLIC.
`user`	`Optional[str], optional` Postgres user name. Defaults to None.
`password`	`Optional[str], optional` Postgres user password. Defaults to None.
`loop`	`Optional[asyncio.AbstractEventLoop]` Async event loop used to create the engine.
`thread`	`Optional[Thread] = None` Thread used to create the engine async.
`quota_project`	`Optional[str]` Project that provides quota for API calls.
`iam_account_email`	`Optional[str], optional` IAM service account email. Defaults to None.

Exceptions
Type	Description
`ValueError`	If only one of `user` and `password` is specified.

_execute

_execute(query: str, params: typing.Optional[dict] = None) -> None

Execute a SQL query.

_fetch

_fetch(
    query: str, params: typing.Optional[dict] = None
) -> typing.Sequence[sqlalchemy.engine.row.RowMapping]

Fetch results from a SQL query.

_run_as_sync

_run_as_sync(
    coro: typing.Awaitable[langchain_google_cloud_sql_pg.engine.T],
) -> langchain_google_cloud_sql_pg.engine.T

Run an async coroutine synchronously

afrom_instance

afrom_instance(
    project_id: str,
    region: str,
    instance: str,
    database: str,
    user: typing.Optional[str] = None,
    password: typing.Optional[str] = None,
    ip_type: typing.Union[
        str, google.cloud.sql.connector.enums.IPTypes
    ] = IPTypes.PUBLIC,
    quota_project: typing.Optional[str] = None,
    iam_account_email: typing.Optional[str] = None,
) -> langchain_google_cloud_sql_pg.engine.PostgresEngine

Create a PostgresEngine from a Postgres instance.

Parameters
Name	Description
`project_id`	`str` GCP project ID.
`region`	`str` Postgres instance region.
`instance`	`str` Postgres instance name.
`database`	`str` Database name.
`user`	`Optional[str], optional` Postgres user name. Defaults to None.
`password`	`Optional[str], optional` Postgres user password. Defaults to None.
`ip_type`	`Union[str, IPTypes], optional` IP address type. Defaults to IPTypes.PUBLIC.
`quota_project`	`Optional[str]` Project that provides quota for API calls.
`iam_account_email`	`Optional[str], optional` IAM service account email. Defaults to None.

Returns
Type	Description
`PostgresEngine`	A newly created PostgresEngine instance.

ainit_chat_history_table

ainit_chat_history_table(table_name: str) -> None

Create a Cloud SQL table to store chat history.

Parameter
Name	Description
`table_name`	`str` Table name to store chat history.

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.
`content_column`	`str` Name of the column to store document content. Default: "page_content".
`metadata_columns`	`List[sqlalchemy.Column]` A list of SQLAlchemy Columns to create for custom metadata. Optional.
`metadata_json_column`	`str` The column to store extra metadata in JSON format. Default: "langchain_metadata". Optional.
`store_metadata`	`bool` Whether to store extra metadata in a metadata column if not described in 'metadata' field list (Default: True).

Exceptions
Type	Description
`DuplicateTableErro`

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.

Exceptions
Type	Description
`DuplicateTableErro`

from_engine

from_engine(
    engine: sqlalchemy.ext.asyncio.engine.AsyncEngine,
) -> langchain_google_cloud_sql_pg.engine.PostgresEngine

Create an PostgresEngine instance from an AsyncEngine.

from_instance

from_instance(
    project_id: str,
    region: str,
    instance: str,
    database: str,
    user: typing.Optional[str] = None,
    password: typing.Optional[str] = None,
    ip_type: typing.Union[
        str, google.cloud.sql.connector.enums.IPTypes
    ] = IPTypes.PUBLIC,
    quota_project: typing.Optional[str] = None,
    iam_account_email: typing.Optional[str] = None,
) -> langchain_google_cloud_sql_pg.engine.PostgresEngine

Create a PostgresEngine from a Postgres instance.

Parameters
Name	Description
`project_id`	`str` GCP project ID.
`region`	`str` Postgres instance region.
`instance`	`str` Postgres instance name.
`database`	`str` Database name.
`user`	`Optional[str], optional` Postgres user name. Defaults to None.
`password`	`Optional[str], optional` Postgres user password. Defaults to None.
`ip_type`	`Union[str, IPTypes], optional` IP address type. Defaults to IPTypes.PUBLIC.
`quota_project`	`Optional[str]` Project that provides quota for API calls.
`iam_account_email`	`Optional[str], optional` IAM service account email. Defaults to None.

Returns
Type	Description
`PostgresEngine`	A newly created PostgresEngine instance.

init_chat_history_table

init_chat_history_table(table_name: str) -> None

Create a Cloud SQL table to store chat history.

Parameter
Name	Description
`table_name`	`str` Table name to store chat history.

init_document_table

init_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.
`content_column`	`str` Name of the column to store document content.
`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).

init_vectorstore_table

init_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.