code: def describe(self, attribute: Optional[str] = None) -> pd.DataFrame:
      args = self.model_storage.json_get("args")
      model_name, target_col = args["model_name"], args["target"]
      prompt_template = args.get(
          "prompt_template",
          "Answer the following question: {{{{text}}}}",
      )
  
      if attribute == "features":
          return pd.DataFrame(
              [[target_col, prompt_template]],
              columns=["target_column", "mindsdb_prompt_template"],
          )
  
      # get model info
      else:
          model_info = requests.post(
              OllamaHandler.SERVE_URL + "/api/show",
              json={"name": model_name},
          ).json()
          return pd.DataFrame(
              [
                  [
                      model_name,
                      model_info["license"],
                      model_info["modelfile"],
                      model_info["parameters"],
                      model_info["template"],
                  ]
              ],
              columns=[
                  "model_type",
                  "license",
                  "modelfile",
                  "parameters",
                  "ollama_base_template",
              ],
          )
  
file_path: mindsdb/mindsdb/integrations/handlers/ollama_handler/ollama_handler.py
imports: import json
  import requests
  from typing import Dict, Optional
  import pandas
  from mindsdb.integrations.libs.base import BaseMLEngine
  from mindsdb.integrations.libs.llm_utils import get_completed_prompts
label_desc: Use image node_id 4 for calling the OllamaHandler obj's underlying member method code with example usage: obj.describe(attribute) and returns: pd, pd