> ## 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.

# Comparison Accuracy Evaluation

> Example showing how to evaluate agent accuracy on comparison tasks.

**1. Create a Python file**

```python accuracy_comparison.py theme={null}
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(
    name="Comparison Evaluation",
    model=OpenAIResponses(id="gpt-5.2"),
    agent=Agent(
        model=OpenAIResponses(id="gpt-5.2"),
        tools=[CalculatorTools()],
        instructions="You must use the calculator tools for comparisons.",
    ),
    input="9.11 and 9.9 -- which is bigger?",
    expected_output="9.9",
    additional_guidelines="Its ok for the output to include additional text or information relevant to the comparison.",
)

result: Optional[AccuracyResult] = evaluation.run(print_results=True)
assert result is not None and result.avg_score >= 8
```

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

**2. Install dependencies**

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

**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 accuracy_comparison.py
```


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