Accuracy Evaluation with Database Logging
Persist AccuracyEval runs to a PostgresDb eval_runs_cookbook table while scoring a calculator agent.
Demonstrates storing accuracy evaluation results in PostgreSQL.
"""
Accuracy Evaluation with Database Logging
=========================================
Demonstrates storing accuracy evaluation results in PostgreSQL.
"""
from typing import Optional
from agno.agent import Agent
from agno.db.postgres.postgres import PostgresDb
from agno.eval.accuracy import AccuracyEval, AccuracyResult
from agno.models.openai import OpenAIChat
from agno.tools.calculator import CalculatorTools
# ---------------------------------------------------------------------------
# Create Database
# ---------------------------------------------------------------------------
db_url = "postgresql+psycopg://ai:ai@localhost:5432/ai"
db = PostgresDb(db_url=db_url, eval_table="eval_runs_cookbook")
# ---------------------------------------------------------------------------
# Create Evaluation
# ---------------------------------------------------------------------------
evaluation = AccuracyEval(
db=db,
name="Calculator Evaluation",
model=OpenAIChat(id="o4-mini"),
agent=Agent(
model=OpenAIChat(id="gpt-5.6-luna"),
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=1,
)
# ---------------------------------------------------------------------------
# Run Evaluation
# ---------------------------------------------------------------------------
if __name__ == "__main__":
result: Optional[AccuracyResult] = evaluation.run(print_results=True)
assert result is not None and result.avg_score >= 8Run the Example
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activateInstall dependencies
uv pip install -U agno "psycopg[binary]" openai sqlalchemyExport your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"Start Postgres
Start Postgres on the port used by this example:
docker run -d --name postgres -e POSTGRES_USER=ai -e POSTGRES_PASSWORD=ai -e POSTGRES_DB=ai -p 5432:5432 postgres:17Run the example
Save the code above as db_logging.py, then run:
python db_logging.pyFull source: cookbook/09_evals/accuracy/db_logging.py