User Profile

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_profile=True),
)

# Session 1: Share information
agent.print_response(
    "Hi! I'm Alice Chen, but please call me Ali.",
    user_id="alice@example.com",
    session_id="session_1",
)

# Session 2: Profile is recalled automatically
agent.print_response(
    "What's my name?",
    user_id="alice@example.com",
    session_id="session_2",
)

from agno.learn import LearningMachine, LearningMode, UserProfileConfig

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

from agno.learn import LearningMachine, LearningMode, UserProfileConfig

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

agent.print_response(
    "Please remember that my name is Bob Smith.",
    user_id="bob@example.com",
)

from dataclasses import dataclass, field
from typing import Optional
from agno.learn.schemas import UserProfile

@dataclass
class CustomerProfile(UserProfile):
    company: Optional[str] = field(
        default=None,
        metadata={"description": "Company or organization"}
    )
    plan_tier: Optional[str] = field(
        default=None,
        metadata={"description": "Subscription tier: free | pro | enterprise"}
    )
    role: Optional[str] = field(
        default=None,
        metadata={"description": "Job title or role"}
    )
    timezone: Optional[str] = field(
        default=None,
        metadata={"description": "User's timezone"}
    )

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=db,
    learning=LearningMachine(
        user_profile=UserProfileConfig(schema=CustomerProfile),
    ),
)

lm = agent.learning_machine

# Get profile
profile = lm.user_profile_store.get(user_id="alice@example.com")
print(profile.name)
print(profile.preferred_name)

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

<user_profile>
Name: Alice Chen
Preferred Name: Ali
Company: Acme Corp
Role: Data Scientist
</user_profile>