Memory components in Langflow

Memory components store and retrieve chat messages by session_id.

They are distinct from vector store components, because they are built specifically for storing and retrieving chat messages from external databases.

Memory components provide access to their respective external databases as memory. This allows Large Language Models (LLMs) or agents to access external memory for persistence and context retention.

Use a memory component in a flow

This example flow stores and retrieves chat history from an Astra DB Chat Memory component with Store Message and Chat Memory components.

The Store Message helper component stores chat memories as Data objects, and the Message History helper component retrieves chat messages as Data objects or strings.

AstraDBChatMemory Component

This component creates an AstraDBChatMessageHistory instance, which stores and retrieves chat messages using Astra DB, a cloud-native database service.

Inputs

Name	Type	Description
collection_name	String	Name of the Astra DB collection for storing messages. Required.
token	SecretString	Authentication token for Astra DB access. Required.
api_endpoint	SecretString	API endpoint URL for the Astra DB service. Required.
namespace	String	Optional namespace within Astra DB for the collection.
session_id	MessageText	Chat session ID. Uses current session ID if not provided.

Outputs

Name	Type	Description
message_history	BaseChatMessageHistory	An instance of AstraDBChatMessageHistory for the session.

CassandraChatMemory Component

This component creates a CassandraChatMessageHistory instance, enabling storage and retrieval of chat messages using Apache Cassandra or DataStax Astra DB.

Inputs

Name	Type	Description
database_ref	MessageText	Contact points for Cassandra or Astra DB database ID. Required.
username	MessageText	Username for Cassandra (leave empty for Astra DB).
token	SecretString	Password for Cassandra or token for Astra DB. Required.
keyspace	MessageText	Keyspace in Cassandra or namespace in Astra DB. Required.
table_name	MessageText	Name of the table or collection for storing messages. Required.
session_id	MessageText	Unique identifier for the chat session. Optional.
cluster_kwargs	Dictionary	Additional keyword arguments for Cassandra cluster configuration. Optional.

Outputs

Name	Type	Description
message_history	BaseChatMessageHistory	An instance of CassandraChatMessageHistory for the session.

Mem0 Chat Memory

The Mem0 Chat Memory component retrieves and stores chat messages using Mem0 memory storage.

Inputs

Name	Display Name	Info
mem0_config	Mem0 Configuration	Configuration dictionary for initializing Mem0 memory instance.
ingest_message	Message to Ingest	The message content to be ingested into Mem0 memory.
existing_memory	Existing Memory Instance	Optional existing Mem0 memory instance.
user_id	User ID	Identifier for the user associated with the messages.
search_query	Search Query	Input text for searching related memories in Mem0.
mem0_api_key	Mem0 API Key	API key for Mem0 platform (leave empty to use the local version).
metadata	Metadata	Additional metadata to associate with the ingested message.
openai_api_key	OpenAI API Key	API key for OpenAI. This item is required if you use OpenAI embeddings without a provided configuration.

Outputs

Name	Display Name	Info
memory	Mem0 Memory	The resulting Mem0 Memory object after ingesting data.
search_results	Search Results	The search results from querying Mem0 memory.

Redis Chat Memory

This component retrieves and stores chat messages from Redis.

Inputs

Name	Display Name	Info
host	hostname	IP address or hostname.
port	port	Redis Port Number.
database	database	Redis database.
username	Username	The Redis user name.
password	Password	The password for username.
key_prefix	Key prefix	Key prefix.
session_id	Session ID	Session ID for the message.

Outputs

Name	Display Name	Info
memory	Memory	The Redis chat message history object

ZepChatMemory Component

This component creates a ZepChatMessageHistory instance, enabling storage and retrieval of chat messages using Zep, a memory server for Large Language Models (LLMs).

Inputs

Name	Type	Description
url	MessageText	URL of the Zep instance. Required.
api_key	SecretString	API Key for authentication with the Zep instance.
api_base_path	Dropdown	API version to use. Options: "api/v1" or "api/v2".
session_id	MessageText	Unique identifier for the chat session. Optional.

Outputs

Name	Type	Description
message_history	BaseChatMessageHistory	An instance of ZepChatMessageHistory for the session.