Basic Agent as Judge

Basic usage of Agent as Judge evaluation with numeric scoring and failure callbacks

This example demonstrates basic Agent as Judge evaluation with numeric scoring (1-10 scale) and an on_fail callback for handling evaluation failures.

1. Add the following code to your Python file

   agent_as_judge_basic.py

   from agno.agent import Agent
   from agno.db.sqlite import SqliteDb
   from agno.eval.agent_as_judge import AgentAsJudgeEval, AgentAsJudgeEvaluation
   from agno.models.openai import OpenAIResponses
   
   
   def on_evaluation_failure(evaluation: AgentAsJudgeEvaluation):
       """Callback triggered when evaluation fails (score < threshold)."""
       print(f"Evaluation failed - Score: {evaluation.score}/10")
       print(f"Reason: {evaluation.reason[:100]}...")
   
   
   # Setup database to persist eval results
   db = SqliteDb(db_file="tmp/agent_as_judge_basic.db")
   
   agent = Agent(
       model=OpenAIResponses(id="gpt-5.2"),
       instructions="You are a technical writer. Explain concepts clearly and concisely.",
       db=db,
   )
   
   response = agent.run("Explain what an API is")
   
   evaluation = AgentAsJudgeEval(
       name="Explanation Quality",
       criteria="Explanation should be clear, beginner-friendly, and use simple language",
       scoring_strategy="numeric",  # Score 1-10
       threshold=9,  # Pass if score >= 9
       on_fail=on_evaluation_failure,
       db=db,
   )
   
   result = evaluation.run(
       input="Explain what an API is",
       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"Name: {latest.name}")
   
   
2. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   

   uv venv --python 3.12
   .venv\Scripts\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"
   

     $Env:OPENAI_API_KEY="your_openai_api_key_here"
   
5. Run the example

   python agent_as_judge_basic.py