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Documentation Index

Fetch the complete documentation index at: https://agno-v2-shaloo-ai-support-link.mintlify.app/llms.txt

Use this file to discover all available pages before exploring further.

1

Create a Python file

accuracy_async.py
"""This example shows how to run an Accuracy evaluation asynchronously."""

import asyncio
from typing import Optional

from agno.agent import Agent
from agno.eval.accuracy import AccuracyEval, AccuracyResult
from agno.models.openai import OpenAIResponses
from agno.tools.calculator import CalculatorTools

evaluation = AccuracyEval(
    model=OpenAIResponses(id="gpt-5.2"),
    agent=Agent(
        model=OpenAIResponses(id="gpt-5.2"),
        tools=[CalculatorTools()],
    ),
    input="What is 10*5 then to the power of 2? do it step by step",
    expected_output="2500",
    additional_guidelines="Agent output should include the steps and the final answer.",
    num_iterations=3,
)

# Run the evaluation calling the arun method.
result: Optional[AccuracyResult] = asyncio.run(evaluation.arun(print_results=True))
assert result is not None and result.avg_score >= 8
2

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate
3

Install dependencies

uv pip install -U openai agno
4

Export your OpenAI API key

  export OPENAI_API_KEY="your_openai_api_key_here"
5

Run Agent

python accuracy_async.py