> ## 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.

# Team with Memory Manager

This example demonstrates how to use persistent memory with a team. After each run, user memories are created and updated, allowing the team to remember information about users across sessions and provide personalized experiences.

## Code

```python team_with_memory_manager.py theme={null}
"""
This example shows you how to use persistent memory with an Agent.

After each run, user memories are created/updated.

To enable this, set `update_memory_on_run=True` in the Agent config.
"""

from uuid import uuid4

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.memory import MemoryManager  # noqa: F401
from agno.models.openai import OpenAIResponses
from agno.team import Team

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

session_id = str(uuid4())
john_doe_id = "john_doe@example.com"

# 1. Create memories by setting `update_memory_on_run=True` in the Agent
agent = Agent(
    model=OpenAIResponses(id="gpt-5.2"),
)
team = Team(
    model=OpenAIResponses(id="gpt-5.2"),
    members=[agent],
    db=db,
    update_memory_on_run=True,
)

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

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

# 2. Set a custom MemoryManager on the agent
# memory_manager = MemoryManager(model=OpenAIResponses(id="gpt-5.2"))

# memory_manager.clear()

# agent = Agent(
#     model=OpenAIResponses(id="gpt-5.2"),
#     memory_manager=memory_manager,
# )

# team = Team(
#     model=OpenAIResponses(id="gpt-5.2"),
#     members=[agent],
#     db=db,
#     update_memory_on_run=True,
# )

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

# # You can also get the user memories from the agent
# memories = agent.get_user_memories(user_id=john_doe_id)
# print("John Doe's memories:")
# pprint(memories)
```

## Usage

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

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

  <Step title="Set up PostgreSQL database">
    Start PostgreSQL with pgvector and update the connection string in the code as needed.
  </Step>

  <Step title="Set environment variables">
    ```bash theme={null}
    export OPENAI_API_KEY=your_openai_api_key_here
    ```
  </Step>

  <Step title="Run the example">
    ```bash theme={null}
    python team_with_memory_manager.py
    ```
  </Step>
</Steps>