AstraDBChatMessageHistory#
- class langchain_community.chat_message_histories.astradb.AstraDBChatMessageHistory(*, session_id: str, collection_name: str = 'langchain_message_store', token: str | None = None, api_endpoint: str | None = None, astra_db_client: AstraDB | None = None, async_astra_db_client: AsyncAstraDB | None = None, namespace: str | None = None, setup_mode: SetupMode = SetupMode.SYNC, pre_delete_collection: bool = False)[source]#
Deprecated since version 0.0.25: Use
langchain_astradb.AstraDBChatMessageHistoryinstead.Chat message history that stores history in Astra DB.
- Parameters:
session_id (str) – arbitrary key that is used to store the messages of a single chat session.
collection_name (str) – name of the Astra DB collection to create/use.
token (Optional[str]) – API token for Astra DB usage.
api_endpoint (Optional[str]) – full URL to the API endpoint, such as “https://<DB-ID>-us-east1.apps.astra.datastax.com”.
astra_db_client (Optional[AstraDB]) – alternative to token+api_endpoint, you can pass an already-created ‘astrapy.db.AstraDB’ instance.
async_astra_db_client (Optional[AsyncAstraDB]) – alternative to token+api_endpoint, you can pass an already-created ‘astrapy.db.AsyncAstraDB’ instance.
namespace (Optional[str]) – namespace (aka keyspace) where the collection is created. Defaults to the database’s “default namespace”.
setup_mode (SetupMode) – mode used to create the Astra DB collection (SYNC, ASYNC or OFF).
pre_delete_collection (bool) – whether to delete the collection before creating it. If False and the collection already exists, the collection will be used as is.
Attributes
messagesRetrieve all session messages from DB
Methods
__init__(*, session_id[, collection_name, ...])Chat message history that stores history in Astra DB.
aadd_messages(messages)Async add a list of messages.
aclear()Async remove all messages from the store
add_ai_message(message)Convenience method for adding an AI message string to the store.
add_message(message)Add a Message object to the store.
add_messages(messages)Add a list of messages.
add_user_message(message)Convenience method for adding a human message string to the store.
Async version of getting messages.
clear()Remove all messages from the store
- __init__(*, session_id: str, collection_name: str = 'langchain_message_store', token: str | None = None, api_endpoint: str | None = None, astra_db_client: AstraDB | None = None, async_astra_db_client: AsyncAstraDB | None = None, namespace: str | None = None, setup_mode: SetupMode = SetupMode.SYNC, pre_delete_collection: bool = False) None[source]#
Chat message history that stores history in Astra DB.
- Parameters:
session_id (str) – arbitrary key that is used to store the messages of a single chat session.
collection_name (str) – name of the Astra DB collection to create/use.
token (Optional[str]) – API token for Astra DB usage.
api_endpoint (Optional[str]) – full URL to the API endpoint, such as “https://<DB-ID>-us-east1.apps.astra.datastax.com”.
astra_db_client (Optional[AstraDB]) – alternative to token+api_endpoint, you can pass an already-created ‘astrapy.db.AstraDB’ instance.
async_astra_db_client (Optional[AsyncAstraDB]) – alternative to token+api_endpoint, you can pass an already-created ‘astrapy.db.AsyncAstraDB’ instance.
namespace (Optional[str]) – namespace (aka keyspace) where the collection is created. Defaults to the database’s “default namespace”.
setup_mode (SetupMode) – mode used to create the Astra DB collection (SYNC, ASYNC or OFF).
pre_delete_collection (bool) – whether to delete the collection before creating it. If False and the collection already exists, the collection will be used as is.
- Return type:
None
- async aadd_messages(messages: Sequence[BaseMessage]) None[source]#
Async add a list of messages.
- Parameters:
messages (Sequence[BaseMessage]) – A sequence of BaseMessage objects to store.
- Return type:
None
- add_ai_message(message: AIMessage | str) None#
Convenience method for adding an AI message string to the store.
Please note that this is a convenience method. Code should favor the bulk add_messages interface instead to save on round-trips to the underlying persistence layer.
This method may be deprecated in a future release.
- Parameters:
message (AIMessage | str) – The AI message to add.
- Return type:
None
- add_message(message: BaseMessage) None#
Add a Message object to the store.
- Parameters:
message (BaseMessage) – A BaseMessage object to store.
- Raises:
NotImplementedError – If the sub-class has not implemented an efficient add_messages method.
- Return type:
None
- add_messages(messages: Sequence[BaseMessage]) None[source]#
Add a list of messages.
Implementations should over-ride this method to handle bulk addition of messages in an efficient manner to avoid unnecessary round-trips to the underlying store.
- Parameters:
messages (Sequence[BaseMessage]) – A sequence of BaseMessage objects to store.
- Return type:
None
- add_user_message(message: HumanMessage | str) None#
Convenience method for adding a human message string to the store.
Please note that this is a convenience method. Code should favor the bulk add_messages interface instead to save on round-trips to the underlying persistence layer.
This method may be deprecated in a future release.
- Parameters:
message (HumanMessage | str) – The human message to add to the store.
- Return type:
None
- async aget_messages() List[BaseMessage][source]#
Async version of getting messages.
Can over-ride this method to provide an efficient async implementation.
In general, fetching messages may involve IO to the underlying persistence layer.
- Return type:
List[BaseMessage]
Examples using AstraDBChatMessageHistory