async_function.py
Run the Example
1
Set up your virtual environment
2
Install dependencies
3
Export your OpenAI API key
4
Run the example
Save the code above as
async_function.py, then run:Documentation Index
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Benchmark an async agent.arun call over 10 iterations with PerformanceEval.arun, printing runtime and memory results.
"""
Async Function Performance Evaluation
=====================================
Demonstrates performance evaluation for an asynchronous function.
"""
import asyncio
from agno.agent import Agent
from agno.eval.performance import PerformanceEval
from agno.models.openai import OpenAIChat
# ---------------------------------------------------------------------------
# Create Benchmark Function
# ---------------------------------------------------------------------------
async def arun_agent():
agent = Agent(
model=OpenAIChat(id="gpt-5.2"),
system_message="Be concise, reply with one sentence.",
)
response = await agent.arun("What is the capital of France?")
return response
# ---------------------------------------------------------------------------
# Create Evaluation
# ---------------------------------------------------------------------------
performance_eval = PerformanceEval(func=arun_agent, num_iterations=10)
# ---------------------------------------------------------------------------
# Run Evaluation
# ---------------------------------------------------------------------------
if __name__ == "__main__":
asyncio.run(performance_eval.arun(print_summary=True, print_results=True))
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
Install dependencies
uv pip install -U agno memory-profiler openai
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
Run the example
async_function.py, then run:python async_function.py
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