> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2-codex-docs-audit-20260719-0149.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# AutoGen Instantiation Performance Evaluation

> Measure AutoGen AssistantAgent instantiation over 1000 iterations with PerformanceEval, using a gpt-4o OpenAIChatCompletionClient and a weather tool.

Demonstrates agent instantiation benchmarking with AutoGen.

```python autogen_instantiation.py theme={null}
"""
AutoGen Instantiation Performance Evaluation
============================================

Demonstrates agent instantiation benchmarking with AutoGen.
"""

from typing import Literal

from agno.eval.performance import PerformanceEval
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient


# ---------------------------------------------------------------------------
# Create Benchmark Tool
# ---------------------------------------------------------------------------
def get_weather(city: Literal["nyc", "sf"]):
    """Use this to get weather information."""
    if city == "nyc":
        return "It might be cloudy in nyc"
    elif city == "sf":
        return "It's always sunny in sf"
    else:
        raise AssertionError("Unknown city")


tools = [get_weather]


# ---------------------------------------------------------------------------
# Create Benchmark Function
# ---------------------------------------------------------------------------
def instantiate_agent():
    return AssistantAgent(
        name="assistant",
        model_client=OpenAIChatCompletionClient(
            model="gpt-4o",
            model_info={
                "vision": False,
                "function_calling": True,
                "json_output": False,
                "family": "gpt-4o",
                "structured_output": True,
            },
        ),
        tools=tools,
    )


# ---------------------------------------------------------------------------
# Create Evaluation
# ---------------------------------------------------------------------------
autogen_instantiation = PerformanceEval(func=instantiate_agent, num_iterations=1000)

# ---------------------------------------------------------------------------
# Run Evaluation
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    autogen_instantiation.run(print_results=True, print_summary=True)
```

## Run the Example

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

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno "autogen-ext[openai]" autogen-agentchat memory-profiler
    ```
  </Step>

  <Step title="Export your API keys">
    <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>

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

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

Full source: [cookbook/09\_evals/performance/comparison/autogen\_instantiation.py](https://github.com/agno-agi/agno/blob/v2.7.4/cookbook/09_evals/performance/comparison/autogen_instantiation.py)