> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2-service-account.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Agentic Memory Management

> Use agentic memory with an Agent.

Use agentic memory with an Agent. During each run, the Agent can create, update, and delete user memories.

```python agentic_memory.py theme={null}
"""
Agentic Memory Management
=========================

This example shows how to use agentic memory with an Agent.
During each run, the Agent can create, update, and delete user memories.
"""

from agno.agent.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.openai import OpenAIChat
from rich.pretty import pprint

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

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent = Agent(
    model=OpenAIChat(id="gpt-4o-mini"),
    db=db,
    enable_agentic_memory=True,
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    john_doe_id = "john_doe@example.com"

    agent.print_response(
        "My name is John Doe and I like to hike in the mountains on weekends.",
        stream=True,
        user_id=john_doe_id,
    )

    agent.print_response("What are my hobbies?", stream=True, user_id=john_doe_id)

    memories = agent.get_user_memories(user_id=john_doe_id)
    print("Memories about John Doe:")
    pprint(memories)

    agent.print_response(
        "Remove all existing memories of me.",
        stream=True,
        user_id=john_doe_id,
    )

    memories = agent.get_user_memories(user_id=john_doe_id)
    print("Memories about John Doe:")
    pprint(memories)

    agent.print_response(
        "My name is John Doe and I like to paint.", stream=True, user_id=john_doe_id
    )

    memories = agent.get_user_memories(user_id=john_doe_id)
    print("Memories about John Doe:")
    pprint(memories)

    agent.print_response(
        "I don't paint anymore, i draw instead.", stream=True, user_id=john_doe_id
    )

    memories = agent.get_user_memories(user_id=john_doe_id)
    print("Memories about John Doe:")
    pprint(memories)
```

## Run the Example

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno openai psycopg-binary sqlalchemy
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export OPENAI_API_KEY="your_openai_api_key_here"
      ```

      ```bash Windows theme={null}
      $Env:OPENAI_API_KEY="your_openai_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Snippet file="run-pgvector-step.mdx" />

  <Step title="Run the example">
    Save the code above as `agentic_memory.py`, then run:

    ```bash theme={null}
    python agentic_memory.py
    ```
  </Step>
</Steps>

Full source: [cookbook/11\_memory/02\_agentic\_memory.py](https://github.com/agno-agi/agno/blob/main/cookbook/11_memory/02_agentic_memory.py)