Agent as Judge with Teams
Evaluating team outputs with Agent as Judge
Evaluate team outputs with Agent as Judge, the same way you evaluate agent outputs.
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
from agno.team.team import Team
# Setup database to persist eval results
db = SqliteDb(db_file="tmp/agent_as_judge_team.db")
# Setup a team with researcher and writer
researcher = Agent(
name="Researcher",
role="Research and gather information",
model=OpenAIResponses(id="gpt-5.2"),
)
writer = Agent(
name="Writer",
role="Write clear and concise summaries",
model=OpenAIResponses(id="gpt-5.2"),
)
research_team = Team(
name="Research Team",
model=OpenAIResponses(id="gpt-5.2"),
members=[researcher, writer],
instructions=["First research the topic thoroughly, then write a clear summary."],
db=db,
)
response = research_team.run("Explain quantum computing")
evaluation = AgentAsJudgeEval(
name="Team Response Quality",
model=OpenAIResponses(id="gpt-5.2"),
criteria="Response should be well-researched, clear, and comprehensive with good flow",
scoring_strategy="binary",
db=db,
)
result: Optional[AgentAsJudgeResult] = evaluation.run(
input="Explain quantum computing",
output=str(response.content),
print_results=True,
print_summary=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"Team: {research_team.name}")
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_team.py