Agent as Judge with Teams

Evaluating team outputs with Agent as Judge

This example demonstrates evaluating team outputs using Agent as Judge evaluation.

1. Add the following code to your Python file

   agent_as_judge_team.py

   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("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[-1]
       print(f"Eval ID: {latest.run_id}")
       print(f"Team: {research_team.name}")
   
   
2. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   
3. Install dependencies

   uv pip install -U agno openai
   
4. Export your OpenAI API key

   Mac/Linux

     export OPENAI_API_KEY="your_openai_api_key_here"
   
5. Run the example

   python agent_as_judge_team.py