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This example demonstrates batch evaluation where multiple cases are evaluated together.
1

Add the following code to your Python file

agent_as_judge_batch.py
from agno.db.sqlite import SqliteDb
from agno.eval.agent_as_judge import AgentAsJudgeEval

# Setup database to persist eval results
db = SqliteDb(db_file="tmp/agent_as_judge_batch.db")

evaluation = AgentAsJudgeEval(
    name="Customer Service Quality",
    criteria="Response should be empathetic, professional, and helpful",
    scoring_strategy="binary",  # PASS/FAIL for each case
    db=db,
)

result = evaluation.run(
    cases=[
        {
            "input": "My order is delayed and I'm very upset!",
            "output": "I sincerely apologize for the delay. I understand how frustrating this must be. Let me check your order status right away and see how we can make this right for you.",
        },
        {
            "input": "Can you help me with a refund?",
            "output": "Of course! I'd be happy to help with your refund. Could you please provide your order number so I can process this quickly for you?",
        },
        {
            "input": "Your product is terrible!",
            "output": "I'm sorry to hear you're disappointed. Your feedback is valuable to us. Could you share more details about what went wrong so we can improve?",
        },
    ],
    print_results=True,
)

print(f"Pass rate: {result.pass_rate:.1f}%")
print(f"Passed: {sum(1 for r in result.results if r.passed)}/{len(result.results)}")
2

Create a virtual environment

Open the Terminal and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
3

Install libraries

pip install -U agno openai
4

Export your OpenAI API key

  export OPENAI_API_KEY="your_openai_api_key_here"
5

Run the example

python agent_as_judge_batch.py