User Memory: Agentic Mode

User Memory captures unstructured observations about users: - Work context and role - Communication style preferences - Patterns and interests - Any memorable facts

"""
User Memory: Agentic Mode
=========================
User Memory captures unstructured observations about users:
- Work context and role
- Communication style preferences
- Patterns and interests
- Any memorable facts

AGENTIC mode gives the agent explicit tools to save and update memories.
The agent decides when to store information - you can see the tool calls.

Compare with: 2a_user_memory_always.py for automatic extraction.
See also: 1b_user_profile_agentic.py for structured profile fields.
"""

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.learn import LearningMachine, LearningMode, UserMemoryConfig
from agno.models.openai import OpenAIResponses

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------

db = PostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai")

# AGENTIC mode: Agent gets memory tools and decides when to use them.
# You'll see tool calls like "update_user_memory" in responses.
agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=db,
    learning=LearningMachine(
        user_memory=UserMemoryConfig(
            mode=LearningMode.AGENTIC,
        ),
    ),
    markdown=True,
)

# ---------------------------------------------------------------------------
# Run Demo
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    user_id = "bob@example.com"

    # Session 1: Agent explicitly saves memories
    print("\n" + "=" * 60)
    print("SESSION 1: Share information (watch for tool calls)")
    print("=" * 60 + "\n")

    agent.print_response(
        "I'm a backend engineer at Stripe. "
        "I specialize in distributed systems and prefer Rust over Go.",
        user_id=user_id,
        session_id="session_1",
        stream=True,
    )
    agent.learning_machine.user_memory_store.print(user_id=user_id)

    # Session 2: Agent uses stored memories
    print("\n" + "=" * 60)
    print("SESSION 2: Memories recalled in new session")
    print("=" * 60 + "\n")

    agent.print_response(
        "What programming language would you recommend for my next project?",
        user_id=user_id,
        session_id="session_2",
        stream=True,
    )
    agent.learning_machine.user_memory_store.print(user_id=user_id)

Run the Example

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/08_learning/01_basics

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

python 2b_user_memory_agentic.py

​Run the Example

Run the Example