> ## Documentation Index
> Fetch the complete documentation index at: https://phidatainc-agui.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Enable learning in your agents.

## Enable Learning

The simplest way: set `learning=True`.

```python theme={null}
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=SqliteDb(db_file="tmp/agents.db"),
    learning=True,
)
```

This enables user profile and user memory extraction in Always mode. The agent automatically captures information and recalls it in future sessions.

## Test It

```python theme={null}
# Session 1: Share information
agent.print_response(
    "Hi! I'm Sarah, I work at Acme Corp as a data scientist.",
    user_id="sarah@acme.com",
    session_id="session_1",
)

# Session 2: Agent remembers
agent.print_response(
    "What do you know about me?",
    user_id="sarah@acme.com",
    session_id="session_2",
)
```

Session 2 is a new conversation, but the agent remembers Sarah.

## Choose What Gets Learned

For more control, configure stores individually:

```python theme={null}
from agno.learn import LearningMachine

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=db,
    learning=LearningMachine(
        user_profile=True,      # Structured facts (name, role, preferences)
        user_memory=True,       # Unstructured observations
        session_context=True,   # Session summary and goals
        entity_memory=False,    # Facts about external entities
        learned_knowledge=False # Insights across users (requires Knowledge)
    ),
)
```

See [Learning Stores](/learning/stores/intro) for details on each store.

## Choose How Learning Happens

Each store can use a different learning mode:

```python theme={null}
from agno.learn import (
    LearningMachine,
    LearningMode,
    UserProfileConfig,
    UserMemoryConfig,
)

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

| Mode        | How it works                                        |
| ----------- | --------------------------------------------------- |
| **Always**  | Extraction runs automatically after each response   |
| **Agentic** | Agent receives tools and decides what to save       |
| **Propose** | Agent proposes learnings, you approve before saving |

See [Learning Modes](/learning/learning-modes) for details.

## Production Database

For production, use PostgreSQL:

```python theme={null}
from agno.db.postgres import PostgresDb

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

agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
    db=db,
    learning=True,
)
```

## Next Steps

<CardGroup cols={2}>
  <Card title="Learning Stores" icon="database" iconType="duotone" href="/learning/stores/intro">
    Configure each store type
  </Card>

  <Card title="Learning Modes" icon="sliders" iconType="duotone" href="/learning/learning-modes">
    Control how and when agents learn
  </Card>
</CardGroup>