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Example

The following agent can maintain persistent memory across conversations: 
from agno.agent import Agent
from agno.tools.memori import MemoriTools

agent = Agent(
    instructions=[
        "You are a memory-enhanced assistant with persistent conversation history",
        "Remember important information about users and their preferences",
        "Use stored memories to provide personalized and contextual responses",
        "Maintain conversation continuity across sessions",
    ],
    tools=[MemoriTools(
        database_url="sqlite:///memori.db",
        user_id="user_123"
    )],
)

agent.print_response("Remember that I prefer vegetarian recipes and I'm learning to cook Italian cuisine", stream=True)

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Toolkit Params

ParameterTypeDefaultDescription
database_urlstrNoneDatabase connection string (SQLite, PostgreSQL, etc.).
user_idOptional[str]NoneUser identifier for memory isolation.
session_idOptional[str]NoneSession identifier for conversation tracking.
enable_store_memoryboolTrueEnable memory storage functionality.
enable_retrieve_memoryboolTrueEnable memory retrieval functionality.
enable_search_memoryboolTrueEnable memory search functionality.
enable_delete_memoryboolTrueEnable memory deletion functionality.
enable_get_conversation_historyboolTrueEnable conversation history retrieval.

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Toolkit Functions

FunctionDescription
store_memoryStore new memories or information.
retrieve_memoryRetrieve specific memories by ID or criteria.
search_memorySearch through stored memories using queries.
delete_memoryDelete specific memories or memory sets.
get_conversation_historyRetrieve conversation history for context.

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Developer Resources