User Memory

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

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=PostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai"),
    learning=LearningMachine(user_memory=True),
)

# Session 1: Share preferences
agent.print_response(
    "I prefer code examples over explanations. Also, I'm working on a machine learning project.",
    user_id="alice@example.com",
    session_id="session_1",
)

# Session 2: Memory is recalled
agent.print_response(
    "Explain async/await in Python",
    user_id="alice@example.com",
    session_id="session_2",
)

from agno.learn import LearningMachine, LearningMode, UserMemoryConfig

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=db,
    learning=LearningMachine(
        user_memory=UserMemoryConfig(mode=LearningMode.ALWAYS),
    ),
)

from agno.learn import LearningMachine, LearningMode, UserMemoryConfig

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=db,
    learning=LearningMachine(
        user_memory=UserMemoryConfig(mode=LearningMode.AGENTIC),
    ),
)

agent.print_response(
    "Remember that I always want to see error handling in code examples.",
    user_id="alice@example.com",
)

lm = agent.get_learning_machine()

# Get all memories
memories = lm.user_memory_store.get_memories(user_id="alice@example.com")
for memory in memories:
    print(f"- {memory.memory}")

# Debug output
lm.user_memory_store.print(user_id="alice@example.com")

<user_memories>
- Prefers code examples over explanations
- Working on a machine learning project
- Uses Python 3.11
- Prefers concise responses
</user_memories>

lm = agent.get_learning_machine()

# Remove memories older than 90 days
lm.curator.prune(user_id="alice@example.com", max_age_days=90)

# Remove duplicates
lm.curator.deduplicate(user_id="alice@example.com")

from agno.learn import LearningMachine

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=db,
    learning=LearningMachine(
        user_profile=True,  # Structured: name, company
        user_memory=True,   # Unstructured: preferences, context
    ),
)