agent_as_judge_team.py
"""
Team Agent-as-Judge Evaluation
==============================
Demonstrates response quality evaluation for team outputs.
"""
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 OpenAIChat
from agno.team.team import Team
# ---------------------------------------------------------------------------
# Create Database
# ---------------------------------------------------------------------------
db = SqliteDb(db_file="tmp/agent_as_judge_team.db")
# ---------------------------------------------------------------------------
# Create Team
# ---------------------------------------------------------------------------
researcher = Agent(
name="Researcher",
role="Research and gather information",
model=OpenAIChat(id="gpt-4o"),
)
writer = Agent(
name="Writer",
role="Write clear and concise summaries",
model=OpenAIChat(id="gpt-4o"),
)
research_team = Team(
name="Research Team",
model=OpenAIChat("gpt-4o"),
members=[researcher, writer],
instructions=["First research the topic thoroughly, then write a clear summary."],
db=db,
)
# ---------------------------------------------------------------------------
# Create Evaluation
# ---------------------------------------------------------------------------
evaluation = AgentAsJudgeEval(
name="Team Response Quality",
model=OpenAIChat(id="gpt-5.2"),
criteria="Response should be well-researched, clear, and comprehensive with good flow",
scoring_strategy="binary",
db=db,
)
# ---------------------------------------------------------------------------
# Run Evaluation
# ---------------------------------------------------------------------------
if __name__ == "__main__":
response = research_team.run("Explain quantum computing")
result: Optional[AgentAsJudgeResult] = evaluation.run(
input="Explain quantum computing",
output=str(response.content),
print_results=True,
print_summary=True,
)
assert result is not None, "Evaluation should return a result"
print("Database Results:")
eval_runs = db.get_eval_runs()
print(f"Total evaluations stored: {len(eval_runs)}")
if eval_runs:
latest = eval_runs[-1]
print(f"Eval ID: {latest.run_id}")
print(f"Team: {research_team.name}")
Run the Example
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U agno openai sqlalchemy
3
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Run the example
Save the code above as
agent_as_judge_team.py, then run:python agent_as_judge_team.py