Package Methods (0.2.0)

Summary of entries of Methods for langchain-google-cloud-sql-mssql.

langchain_google_cloud_sql_mssql.chat_message_history.MSSQLChatMessageHistory._verify_schema

_verify_schema() -> None

Verify table exists with required schema for MSSQLChatMessageHistory class.

See more: langchain_google_cloud_sql_mssql.chat_message_history.MSSQLChatMessageHistory._verify_schema

langchain_google_cloud_sql_mssql.chat_message_history.MSSQLChatMessageHistory.add_message

add_message(message: langchain_core.messages.base.BaseMessage) -> None

langchain_google_cloud_sql_mssql.chat_message_history.MSSQLChatMessageHistory.clear

clear() -> None

langchain_google_cloud_sql_mssql.engine.MSSQLEngine._create_connector_engine

_create_connector_engine(
    instance_connection_name: str, database: str, user: str, password: str
) -> sqlalchemy.engine.base.Engine

Create a SQLAlchemy engine using the Cloud SQL Python Connector.

See more: langchain_google_cloud_sql_mssql.engine.MSSQLEngine._create_connector_engine

langchain_google_cloud_sql_mssql.engine.MSSQLEngine._load_document_table

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

Load table schema from existing table in MSSQL database.

See more: langchain_google_cloud_sql_mssql.engine.MSSQLEngine._load_document_table

langchain_google_cloud_sql_mssql.engine.MSSQLEngine.connect

connect() -> sqlalchemy.engine.base.Connection

Create a connection from SQLAlchemy connection pool.

See more: langchain_google_cloud_sql_mssql.engine.MSSQLEngine.connect

langchain_google_cloud_sql_mssql.engine.MSSQLEngine.from_instance

from_instance(
    project_id: str, region: str, instance: str, database: str, user: str, password: str
) -> langchain_google_cloud_sql_mssql.engine.MSSQLEngine

Create an instance of MSSQLEngine from Cloud SQL instance details.

See more: langchain_google_cloud_sql_mssql.engine.MSSQLEngine.from_instance

langchain_google_cloud_sql_mssql.engine.MSSQLEngine.init_chat_history_table

init_chat_history_table(table_name: str) -> None

Create table with schema required for MSSQLChatMessageHistory class.

See more: langchain_google_cloud_sql_mssql.engine.MSSQLEngine.init_chat_history_table

langchain_google_cloud_sql_mssql.engine.MSSQLEngine.init_document_table

init_document_table(
    table_name: str,
    metadata_columns: typing.List[sqlalchemy.sql.schema.Column] = [],
    content_column: str = "page_content",
    metadata_json_column: typing.Optional[str] = "langchain_metadata",
    overwrite_existing: bool = False,
) -> None

Create a table for saving of langchain documents.

See more: langchain_google_cloud_sql_mssql.engine.MSSQLEngine.init_document_table

langchain_google_cloud_sql_mssql.loader.MSSQLDocumentSaver

MSSQLDocumentSaver(
    engine: langchain_google_cloud_sql_mssql.engine.MSSQLEngine,
    table_name: str,
    content_column: typing.Optional[str] = None,
    metadata_json_column: typing.Optional[str] = None,
)

MSSQLDocumentSaver allows for saving of langchain documents in a database.

See more: langchain_google_cloud_sql_mssql.loader.MSSQLDocumentSaver

langchain_google_cloud_sql_mssql.loader.MSSQLDocumentSaver.add_documents

add_documents(docs: typing.List[langchain_core.documents.base.Document]) -> None

Save documents in the DocumentSaver table.

See more: langchain_google_cloud_sql_mssql.loader.MSSQLDocumentSaver.add_documents

langchain_google_cloud_sql_mssql.loader.MSSQLDocumentSaver.delete

delete(docs: typing.List[langchain_core.documents.base.Document]) -> None

Delete all instances of a document from the DocumentSaver table by matching the entire Document object.

See more: langchain_google_cloud_sql_mssql.loader.MSSQLDocumentSaver.delete

langchain_google_cloud_sql_mssql.loader.MSSQLLoader

MSSQLLoader(
    engine: langchain_google_cloud_sql_mssql.engine.MSSQLEngine,
    table_name: str = "",
    query: str = "",
    content_columns: typing.Optional[typing.List[str]] = None,
    metadata_columns: typing.Optional[typing.List[str]] = None,
    metadata_json_column: typing.Optional[str] = None,
)

Document page content defaults to the first column present in the query or table and metadata defaults to all other columns.

See more: langchain_google_cloud_sql_mssql.loader.MSSQLLoader

langchain_google_cloud_sql_mssql.loader.MSSQLLoader.lazy_load

lazy_load() -> typing.Iterator[langchain_core.documents.base.Document]

Lazy Load langchain documents from a Cloud SQL MSSQL database.

See more: langchain_google_cloud_sql_mssql.loader.MSSQLLoader.lazy_load

langchain_google_cloud_sql_mssql.loader.MSSQLLoader.load

load() -> typing.List[langchain_core.documents.base.Document]

Load langchain documents from a Cloud SQL MSSQL database.

See more: langchain_google_cloud_sql_mssql.loader.MSSQLLoader.load