Package Methods (0.6.0)

Summary of entries of Methods for langchain-google-bigtable.

langchain_google_bigtable.chat_message_history.init_chat_history_table

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

Create a table to store chat history.

See more: langchain_google_bigtable.chat_message_history.init_chat_history_table

langchain_google_bigtable.key_value_store.init_key_value_store_table

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

Create a table for saving of LangChain Key-value pairs.

See more: langchain_google_bigtable.key_value_store.init_key_value_store_table

langchain_google_bigtable.loader.init_document_table

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

Create a table for saving of langchain documents.

See more: langchain_google_bigtable.loader.init_document_table

langchain_google_bigtable.chat_message_history.BigtableChatMessageHistory.add_message

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

Write a message to the table.

See more: langchain_google_bigtable.chat_message_history.BigtableChatMessageHistory.add_message

langchain_google_bigtable.chat_message_history.BigtableChatMessageHistory.add_messages

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

Write messages to the table.

See more: langchain_google_bigtable.chat_message_history.BigtableChatMessageHistory.add_messages

langchain_google_bigtable.chat_message_history.BigtableChatMessageHistory.clear

clear() -> None

Clear session memory from DB.

See more: langchain_google_bigtable.chat_message_history.BigtableChatMessageHistory.clear

langchain_google_bigtable.engine.BigtableEngine

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

Initializes the engine with a running event loop and a client.

See more: langchain_google_bigtable.engine.BigtableEngine

langchain_google_bigtable.engine.BigtableEngine.__start_background_loop

__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

Creates and starts the default background loop and thread.

See more: langchain_google_bigtable.engine.BigtableEngine.__start_background_loop

langchain_google_bigtable.engine.BigtableEngine._create

_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

Asynchronously instantiates the BigtableEngine Object.

See more: langchain_google_bigtable.engine.BigtableEngine._create

langchain_google_bigtable.engine.BigtableEngine._run_as_async

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

Runs a coroutine on the background loop without blocking the main loop.

See more: langchain_google_bigtable.engine.BigtableEngine._run_as_async

langchain_google_bigtable.engine.BigtableEngine._run_as_sync

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

Runs a coroutine on the background loop and waits for the result.

See more: langchain_google_bigtable.engine.BigtableEngine._run_as_sync

langchain_google_bigtable.engine.BigtableEngine.async_initialize

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

Creates a BigtableEngine instance with a background event loop and a new data client asynchronously .

See more: langchain_google_bigtable.engine.BigtableEngine.async_initialize

langchain_google_bigtable.engine.BigtableEngine.close

close() -> None

Closes the underlying client for this specific engine instance.

See more: langchain_google_bigtable.engine.BigtableEngine.close

langchain_google_bigtable.engine.BigtableEngine.get_async_table

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

Returns the table using this class's client.

See more: langchain_google_bigtable.engine.BigtableEngine.get_async_table

langchain_google_bigtable.engine.BigtableEngine.initialize

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

Creates a BigtableEngine instance with a background event loop and a new data client synchronously.

See more: langchain_google_bigtable.engine.BigtableEngine.initialize

langchain_google_bigtable.engine.BigtableEngine.shutdown_default_loop

shutdown_default_loop() -> None

Closes the default class-level shared loop and terminates the thread associated with it.

See more: langchain_google_bigtable.engine.BigtableEngine.shutdown_default_loop

langchain_google_bigtable.key_value_store.BigtableByteStore._get_async_store

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

Returns a AsyncBigtableByteStore object to be used for data operations.

See more: langchain_google_bigtable.key_value_store.BigtableByteStore._get_async_store

langchain_google_bigtable.key_value_store.BigtableByteStore.amdelete

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

Asynchronously deletes key-value pairs from the Bigtable.

See more: langchain_google_bigtable.key_value_store.BigtableByteStore.amdelete

langchain_google_bigtable.key_value_store.BigtableByteStore.amget

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

Asynchronously retrieves values for a sequence of keys.

See more: langchain_google_bigtable.key_value_store.BigtableByteStore.amget

langchain_google_bigtable.key_value_store.BigtableByteStore.amset

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

Asynchronously stores key-value pairs in the Bigtable.

See more: langchain_google_bigtable.key_value_store.BigtableByteStore.amset

langchain_google_bigtable.key_value_store.BigtableByteStore.ayield_keys

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

Asynchronously yields keys matching a given prefix.

See more: langchain_google_bigtable.key_value_store.BigtableByteStore.ayield_keys

langchain_google_bigtable.key_value_store.BigtableByteStore.create

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

Creates an async-initialized instance of the BigtableByteStore.

See more: langchain_google_bigtable.key_value_store.BigtableByteStore.create

langchain_google_bigtable.key_value_store.BigtableByteStore.create_sync

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

Creates a sync-initialized instance of the BigtableByteStore.

See more: langchain_google_bigtable.key_value_store.BigtableByteStore.create_sync

langchain_google_bigtable.key_value_store.BigtableByteStore.get_engine

get_engine() -> langchain_google_bigtable.engine.BigtableEngine

Returns the BigtableEngine being used for this object.

See more: langchain_google_bigtable.key_value_store.BigtableByteStore.get_engine

langchain_google_bigtable.key_value_store.BigtableByteStore.mdelete

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

Synchronously deletes key-value pairs from the Bigtable.

See more: langchain_google_bigtable.key_value_store.BigtableByteStore.mdelete

langchain_google_bigtable.key_value_store.BigtableByteStore.mget

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

Synchronously retrieves values for a sequence of keys.

See more: langchain_google_bigtable.key_value_store.BigtableByteStore.mget

langchain_google_bigtable.key_value_store.BigtableByteStore.mset

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

Synchronously stores key-value pairs in the Bigtable.

See more: langchain_google_bigtable.key_value_store.BigtableByteStore.mset

langchain_google_bigtable.key_value_store.BigtableByteStore.yield_keys

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

Synchronously yields keys matching a given prefix.

See more: langchain_google_bigtable.key_value_store.BigtableByteStore.yield_keys

langchain_google_bigtable.loader.BigtableLoader

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,
)

Initialize Bigtable document loader.

See more: langchain_google_bigtable.loader.BigtableLoader

langchain_google_bigtable.loader.BigtableLoader.lazy_load

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

A lazy loader for Documents.

See more: langchain_google_bigtable.loader.BigtableLoader.lazy_load

langchain_google_bigtable.loader.BigtableLoader.load

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

Load data into Document objects.

See more: langchain_google_bigtable.loader.BigtableLoader.load

langchain_google_bigtable.loader.BigtableSaver

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,
)

Initialize Bigtable document saver.

See more: langchain_google_bigtable.loader.BigtableSaver

langchain_google_bigtable.loader.BigtableSaver.add_documents

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

Save documents in the DocumentSaver table.

See more: langchain_google_bigtable.loader.BigtableSaver.add_documents

langchain_google_bigtable.loader.BigtableSaver.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_bigtable.loader.BigtableSaver.delete