Agent as Judge with Guidelines
Using additional guidelines for more detailed evaluation criteria
Add additional_guidelines to give the judge more specific evaluation criteria.
Add the following code to your Python file
from typing import Optional
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.eval.agent_as_judge import AgentAsJudgeEval, AgentAsJudgeResult
from agno.models.openai import OpenAIResponses
# Setup database to persist eval results
db = SqliteDb(db_file="tmp/agent_as_judge_guidelines.db")
agent = Agent(
model=OpenAIResponses(id="gpt-5.2"),
instructions="You are a Tesla Model 3 product specialist. Provide detailed and helpful specifications.",
db=db,
)
response = agent.run("What is the maximum speed of the Tesla Model 3?")
evaluation = AgentAsJudgeEval(
name="Product Info Quality",
model=OpenAIResponses(id="gpt-5.2"),
criteria="Response should be informative, well-formatted, and accurate for product specifications",
scoring_strategy="numeric",
threshold=8,
additional_guidelines=[
"Must include specific numbers with proper units (mph, km/h, etc.)",
"Should provide context for different model variants if applicable",
"Information should be technically accurate and complete",
],
db=db,
)
result: Optional[AgentAsJudgeResult] = evaluation.run(
input="What is the maximum speed?",
output=str(response.content),
print_results=True,
)
# Query database for stored results
print("Database Results:")
eval_runs = db.get_eval_runs()
print(f"Total evaluations stored: {len(eval_runs)}")
if eval_runs:
latest = eval_runs[0] # get_eval_runs() sorts newest first
print(f"Eval ID: {latest.run_id}")
print(f"Additional guidelines used: {len(evaluation.additional_guidelines)}")
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activateInstall dependencies
uv pip install -U agno openai sqlalchemyExport your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"Run the example
python agent_as_judge_with_guidelines.py