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"""
Storage-Backed Response Performance Evaluation
==============================================

Demonstrates measuring performance when storage-backed history is enabled.
"""

from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.eval.performance import PerformanceEval
from agno.models.openai import OpenAIChat

# ---------------------------------------------------------------------------
# Create Database
# ---------------------------------------------------------------------------
db = SqliteDb(db_file="tmp/storage.db")


# ---------------------------------------------------------------------------
# Create Benchmark Function
# ---------------------------------------------------------------------------
def run_agent():
    agent = Agent(
        model=OpenAIChat(id="gpt-5.2"),
        system_message="Be concise, reply with one sentence.",
        db=db,
        add_history_to_context=True,
    )
    response_1 = agent.run("What is the capital of France?")
    print(response_1.content)

    response_2 = agent.run("How many people live there?")
    print(response_2.content)

    return response_2.content


# ---------------------------------------------------------------------------
# Create Evaluation
# ---------------------------------------------------------------------------
response_with_storage_perf = PerformanceEval(
    name="Storage Performance",
    func=run_agent,
    num_iterations=1,
    warmup_runs=0,
)

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

​
Run the Example

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/09_evals/performance

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

python response_with_storage.py