Package Methods (0.6.0)

init_chat_history_table( instance_id: str, table_id: str, client: typing.Optional[google.cloud.bigtable.client.Client] = None, ) -> None

init_key_value_store_table( instance_id: str, table_id: str, project_id: typing.Optional[str] = None, client: typing.Optional[google.cloud.bigtable.client.Client] = None, column_families: typing.List[str] = ["kv"], ) -> None

init_document_table( instance_id: str, table_id: str, client: typing.Optional[google.cloud.bigtable.client.Client] = None, content_column_family: str = "langchain", metadata_mappings: typing.List[ langchain_google_bigtable.loader.MetadataMapping ] = [], metadata_as_json_column_family: typing.Optional[str] = None, ) -> None

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

add_messages( messages: typing.Sequence[langchain_core.messages.base.BaseMessage], ) -> None

clear() -> None

BigtableEngine( key: object, client: typing.Optional[ google.cloud.bigtable.data._async.client.BigtableDataClientAsync ], loop: typing.Optional[asyncio.events.AbstractEventLoop], thread: typing.Optional[threading.Thread], )

__start_background_loop( project_id: typing.Optional[str], credentials: typing.Optional[google.auth.credentials.Credentials] = None, client_options: typing.Optional[typing.Any] = None, **kwargs: typing.Any ) -> concurrent.futures._base.Future

_create( project_id: typing.Optional[str] = None, loop: typing.Optional[asyncio.events.AbstractEventLoop] = None, thread: typing.Optional[threading.Thread] = None, client: typing.Optional[ google.cloud.bigtable.data._async.client.BigtableDataClientAsync ] = None, credentials: typing.Optional[google.auth.credentials.Credentials] = None, client_options: typing.Optional[typing.Any] = None, **kwargs: typing.Any ) -> langchain_google_bigtable.engine.BigtableEngine

_run_as_async(coro: typing.Any) -> typing.Any

_run_as_sync(coro: typing.Any) -> typing.Any

async_initialize( project_id: typing.Optional[str] = None, credentials: typing.Optional[google.auth.credentials.Credentials] = None, client_options: typing.Optional[typing.Any] = None, **kwargs: typing.Any ) -> langchain_google_bigtable.engine.BigtableEngine

close() -> None

get_async_table( instance_id: str, table_id: str, app_profile_id: typing.Optional[str] = None, **kwargs: typing.Any ) -> google.cloud.bigtable.data._async.client.TableAsync

initialize( project_id: typing.Optional[str] = None, credentials: typing.Optional[google.auth.credentials.Credentials] = None, client_options: typing.Optional[typing.Any] = None, **kwargs: typing.Any ) -> langchain_google_bigtable.engine.BigtableEngine

shutdown_default_loop() -> None

_get_async_store( **kwargs: typing.Any, ) -> langchain_google_bigtable.async_key_value_store.AsyncBigtableByteStore

amdelete(keys: typing.Sequence[str]) -> None

amget(keys: typing.Sequence[str]) -> typing.List[typing.Optional[bytes]]

amset(key_value_pairs: typing.Sequence[typing.Tuple[str, bytes]]) -> None

ayield_keys(*, prefix: typing.Optional[str] = None) -> typing.AsyncIterator[str]

create( instance_id: str, table_id: str, *, engine: typing.Optional[langchain_google_bigtable.engine.BigtableEngine] = None, project_id: typing.Optional[str] = None, app_profile_id: typing.Optional[str] = None, column_family: str = "kv", column_qualifier: typing.Union[str, bytes] = b"val", credentials: typing.Optional[google.auth.credentials.Credentials] = None, client_options: typing.Optional[typing.Dict[str, typing.Any]] = None, **kwargs: typing.Any ) -> langchain_google_bigtable.key_value_store.BigtableByteStore

create_sync( instance_id: str, table_id: str, *, engine: typing.Optional[langchain_google_bigtable.engine.BigtableEngine] = None, project_id: typing.Optional[str] = None, app_profile_id: typing.Optional[str] = None, column_family: str = "kv", column_qualifier: typing.Union[str, bytes] = b"val", credentials: typing.Optional[google.auth.credentials.Credentials] = None, client_options: typing.Optional[typing.Dict[str, typing.Any]] = None, **kwargs: typing.Any ) -> langchain_google_bigtable.key_value_store.BigtableByteStore

get_engine() -> langchain_google_bigtable.engine.BigtableEngine

mdelete(keys: typing.Sequence[str]) -> None

mget(keys: typing.Sequence[str]) -> typing.List[typing.Optional[bytes]]

mset(key_value_pairs: typing.Sequence[typing.Tuple[str, bytes]]) -> None

yield_keys(*, prefix: typing.Optional[str] = None) -> typing.Iterator[str]

BigtableLoader( instance_id: str, table_id: str, row_set: typing.Optional[google.cloud.bigtable.row_set.RowSet] = None, filter: typing.Optional[google.cloud.bigtable.row_filters.RowFilter] = None, client: typing.Optional[google.cloud.bigtable.client.Client] = None, content_encoding: langchain_google_bigtable.loader.Encoding = Encoding.UTF8, content_column_family: str = "langchain", content_column_name: str = "content", metadata_mappings: typing.List[ langchain_google_bigtable.loader.MetadataMapping ] = [], metadata_as_json_column_family: typing.Optional[str] = None, metadata_as_json_column_name: typing.Optional[str] = None, metadata_as_json_encoding: langchain_google_bigtable.loader.Encoding = Encoding.UTF8, )

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

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

BigtableSaver( instance_id: str, table_id: str, client: typing.Optional[google.cloud.bigtable.client.Client] = None, content_encoding: langchain_google_bigtable.loader.Encoding = Encoding.UTF8, content_column_family: str = "langchain", content_column_name: str = "content", metadata_mappings: typing.List[ langchain_google_bigtable.loader.MetadataMapping ] = [], metadata_as_json_column_family: typing.Optional[str] = None, metadata_as_json_column_name: typing.Optional[str] = None, metadata_as_json_encoding: langchain_google_bigtable.loader.Encoding = Encoding.UTF8, )

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

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