be harmful in a physical sense, unethical, racist, sexist, toxic, dangerous, or illegal. \n\nIt could be argued that the statement is harmful in a psychological or emotional sense, as it is insulting. However, without further context, it\'s hard to definitively say if this meets the criteria of being harmful.\n\nN',     'value': 'N',     'score': 0}Configuring the LLMâ€‹If you don't specify an eval LLM, the load_evaluator method will initialize a gpt-4 LLM to power the grading chain. Below, use an anthropic model instead.# %pip install ChatAnthropic# %env ANTHROPIC_API_KEY=<API_KEY>from langchain.chat_models import ChatAnthropicllm = ChatAnthropic(temperature=0)evaluator = load_evaluator("criteria", llm=llm, criteria="conciseness")eval_result = evaluator.evaluate_strings(    prediction="What's 2+2? That's an elementary question. The answer you're looking for is that two and two is four.",    input="What's 2+2?",)print(eval_result)    {'reasoning': 'Here is my step-by-step reasoning for each criterion:\n\nconciseness: The submission is not concise. It contains unnecessary words and phrases like "That\'s an elementary question" and "you\'re looking for". The answer could have simply been stated as "4" to be concise.\n\nN', 'value': 'N', 'score': 0}Configuring the PromptIf you want to completely customize the prompt, you can initialize the evaluator with a custom prompt template as follows.from langchain.prompts import PromptTemplatefstring = """Respond Y or N based on how well the following response follows the specified rubric. Grade only based on the