code: def generate_sharegpt():
      # ShareGPT data requires less processing.
      conversation_dataset = []
      dataset = load_dataset(
          "anon8231489123/ShareGPT_Vicuna_unfiltered",
          data_files="ShareGPT_V3_unfiltered_cleaned_split_no_imsorry.json",
          split="train",
      )
  
      conversations = dataset["conversations"]
  
      for idx in range(len(conversations)):
          for conv in conversations[idx]:
              # We don't need markdown and text value.
              del conv["markdown"]
              del conv["text"]
  
          conversation = dict(
              type="conversation",
              language="Multilingual",
              dataset="ShareGPT",
              conversations=conversations[idx],
          )
          conversation_dataset.append(conversation)
  
      return conversation_dataset
  
imports: import argparse
  import json
  from datasets import load_dataset
label_desc: Use image node_id 2 for calling a global function with example usage: generate_sharegpt() and returns: conversation_dataset