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"""
User Memory: Always Mode
========================
User Memory captures unstructured observations about users:
- Work context and role
- Communication style preferences
- Patterns and interests
- Any memorable facts
ALWAYS mode extracts memories automatically in parallel
while the agent responds - no explicit tool calls needed.
Compare with: 2b_user_memory_agentic.py for explicit tool-based updates.
See also: 1a_user_profile_always.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")
# ALWAYS mode: Extraction happens automatically after each response.
# The agent doesn't see or call any memory tools - it's invisible.
# Memories stores unstructured observations that don't fit profile fields.
agent = Agent(
model=OpenAIResponses(id="gpt-5.2"),
db=db,
learning=LearningMachine(
user_memory=UserMemoryConfig(
mode=LearningMode.ALWAYS,
),
),
markdown=True,
)
# ---------------------------------------------------------------------------
# Run Demo
# ---------------------------------------------------------------------------
if __name__ == "__main__":
user_id = "[email protected]"
# Session 1: Share information naturally
print("\n" + "=" * 60)
print("SESSION 1: Share information (extraction happens automatically)")
print("=" * 60 + "\n")
agent.print_response(
"Hi! I work at Anthropic as a research scientist. "
"I prefer concise responses without too much explanation. "
"I'm currently working on a paper about transformer architectures.",
user_id=user_id,
session_id="session_1",
stream=True,
)
agent.learning_machine.user_memory_store.print(user_id=user_id)
# Session 2: New session - memories are recalled automatically
print("\n" + "=" * 60)
print("SESSION 2: Memories recalled in new session")
print("=" * 60 + "\n")
agent.print_response(
"What's a good Python library for async HTTP requests?",
user_id=user_id,
session_id="session_2",
stream=True,
)
agent.learning_machine.user_memory_store.print(user_id=user_id)
Run the Example
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# 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 2a_user_memory_always.py