code: def evaluate_agent(
      agent, batch_size=8, verbose=False, return_errors=False
  ):
      """
      Evaluates a new agent on all `EVALUATION_TASKS`.
  
      Example:
  
      ```py
      agent = NewOpenAiAgent(model="text-davinci-003", api_key=your_api_key)
      bads = new_evaluate_agent(agent)
      for bad in bads:
          print(bad)
      ```
      """
      # Sanity check
      agent_tools = set(agent.toolbox.keys())
      if agent_tools != set(TEST_TOOLS):
          missing_tools = set(TEST_TOOLS) - agent_tools
          unexpected_tools = set(agent_tools) - TEST_TOOLS
          raise ValueError(
              f"Fix the test tools in the evaluate_agent module. Tools mising: {missing_tools}. Extra tools: {unexpected_tools}."
          )
  
      eval_tasks = []
      eval_idx = []
      for idx, pb in enumerate(EVALUATION_TASKS):
          if isinstance(pb.task, list):
              eval_tasks.extend(pb.task)
              eval_idx.extend([idx] * len(pb.task))
          else:
              eval_tasks.append(pb.task)
              eval_idx.append(idx)
  
      tool_selection_score = 0
      tool_used_score = 0
      code_score = 0
  
      if return_errors:
          tool_selection_errors = {}
          tool_used_errors = {}
          code_errors = {}
  
      for start_idx in range(0, len(eval_tasks), batch_size):
          end_idx = min(start_idx + batch_size, len(eval_tasks))
          batch_tasks = eval_tasks[start_idx:end_idx]
  
          prompts = [agent.format_prompt(task) for task in batch_tasks]
          results = agent.generate_many(prompts, stop=["Task:"])
  
          for idx, result in enumerate(results):
              problem = EVALUATION_TASKS[eval_idx[start_idx + idx]]
              if verbose:
                  print(
                      f"====Task {start_idx + idx}====\n{batch_tasks[idx]}\n"
                  )
              explanation, code = clean_code_for_run(result)
  
              # Evaluate agent answer and code answer
              agent_answer = evaluate_code(
                  code, problem.inputs, verbose=verbose
              )
              if isinstance(problem.answer, list):
                  theoretical_answer = [
                      evaluate_code(answer, problem.inputs)
                      for answer in problem.answer
                  ]
              else:
                  theoretical_answer = evaluate_code(
                      problem.answer, problem.inputs
                  )
  
              scores, errors = evaluate_one_result(
                  explanation,
                  code,
                  agent_answer,
                  theoretical_answer,
                  problem.answer,
                  verbose=verbose,
              )
  
              tool_selection_score += scores[0]
              tool_used_score += scores[1]
              code_score += scores[2]
  
              if return_errors:
                  if errors[0] is not None:
                      tool_selection_errors[batch_tasks[idx]] = errors[
                          0
                      ]
                  if errors[1] is not None:
                      tool_used_errors[batch_tasks[idx]] = errors[1]
                  if errors[2] is not None:
                      code_errors[batch_tasks[idx]] = errors[2]
  
      scores = {
          "tool selection score": 100
          * (tool_selection_score / len(eval_tasks)),
          "tool used score": 100 * (tool_used_score / len(eval_tasks)),
          "code score": 100 * (code_score / len(eval_tasks)),
      }
  
      if return_errors:
          return (
              scores,
              tool_selection_errors,
              tool_used_errors,
              code_errors,
          )
      else:
          return scores
  
imports: from .agents import BASE_PYTHON_TOOLS, clean_code_for_chat, clean_code_for_run
  from .python_interpreter import InterpretorError, evaluate
label_desc: Use image node_id 19 for calling a global function with example usage: evaluate_agent(agent, batch_size, verbose, return_errors) and returns: scores,  tool_selection_errors,  tool_used_errors,  code_errors, scores