Summary of entries of Methods for langchain-google-cloud-sql-mssql.
langchain_google_cloud_sql_mssql.chat_message_history.MSSQLChatMessageHistory._verify_schema
_verify_schema() -> NoneVerify 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) -> NoneAppend the message to the record in Cloud SQL.
See more: langchain_google_cloud_sql_mssql.chat_message_history.MSSQLChatMessageHistory.add_message
langchain_google_cloud_sql_mssql.chat_message_history.MSSQLChatMessageHistory.clear
clear() -> NoneClear session memory from Cloud SQL.
See more: langchain_google_cloud_sql_mssql.chat_message_history.MSSQLChatMessageHistory.clear
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.EngineCreate 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.TableLoad 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.ConnectionCreate 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.MSSQLEngineCreate 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) -> NoneCreate 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,
) -> NoneCreate 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]) -> NoneSave 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]) -> NoneDelete 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