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

# Performance with Memory Updates

> Example showing how to evaluate performance when memory updates are involved.

**1. Create a Python file**

```python performance_with_memory.py theme={null}
"""Run `uv pip install openai agno sqlalchemy` to install dependencies."""

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.eval.performance import PerformanceEval
from agno.models.openai import OpenAIResponses

# Memory creation requires a db to be provided
db = SqliteDb(db_file="tmp/memory.db")


def run_agent():
    agent = Agent(
        model=OpenAIResponses(id="gpt-5.2"),
        system_message="Be concise, reply with one sentence.",
        db=db,
        update_memory_on_run=True,
    )

    response = agent.run("My name is Tom! I'm 25 years old and I live in New York.")
    print(f"Agent response: {response.content}")

    return response


response_with_memory_updates_perf = PerformanceEval(
    name="Memory Updates Performance",
    func=run_agent,
    num_iterations=5,
    warmup_runs=0,
)

if __name__ == "__main__":
    response_with_memory_updates_perf.run(print_results=True, print_summary=True)
```

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

**2. Install dependencies**

```bash theme={null}
uv pip install -U openai agno sqlalchemy
```

**3. Export your OpenAI API key**

```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"
```

**4. Run Agent**

```bash theme={null}
python performance_with_memory.py
```


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.