class_docstr: Integration with the Anthropic LLM Python Library
class_docstr_tok: ["Integration","with","the","Anthropic","LLM","Python","Library"]
code: def create(
      self,
      target: str,
      df: Optional[pd.DataFrame] = None,
      args: Optional[Dict] = None,
  ) -> None:
      if "using" not in args:
          raise Exception(
              "Anthropic engine requires a USING clause! Refer to its documentation for more details."
          )
  
      if "model" not in args["using"]:
          args["using"]["model"] = self.default_chat_model
      elif args["using"]["model"] not in self.supported_chat_models:
          raise Exception(
              f"Invalid chat model. Please use one of {self.supported_chat_models}"
          )
  
      if "max_tokens" not in args["using"]:
          args["using"]["max_tokens"] = self.default_max_tokens
  
      self.model_storage.json_set("args", args)
  
file_path: mindsdb/mindsdb/integrations/handlers/anthropic_handler/anthropic_handler.py
imports: import os
  from typing import Dict, Optional
  import pandas
  from anthropic import AI_PROMPT, HUMAN_PROMPT, Anthropic
  from mindsdb.integrations.libs.base import BaseMLEngine
  from mindsdb.utilities import log
  from mindsdb.utilities.config import Config
label_desc: Use image node_id 2 for calling the AnthropicHandler obj's underlying member method code with example usage: obj.create(target, df, args) without return types