code: def parse_args():
      """
      Parse command-line arguments.
      """
      parser = argparse.ArgumentParser()
  
      # Define the command-line arguments
      parser.add_argument(
          "--video_dir",
          help="Directory containing video files.",
          required=True,
      )
      parser.add_argument(
          "--gt_file",
          help="Path to the ground truth file containing question.",
          required=True,
      )
      parser.add_argument(
          "--output_dir",
          help="Directory to save the model results JSON.",
          required=True,
      )
      parser.add_argument(
          "--output_name",
          help="Name of the file for storing results JSON.",
          required=True,
      )
      parser.add_argument(
          "--model-path", type=str, default="facebook/opt-350m"
      )
      parser.add_argument("--model-base", type=str, default=None)
      parser.add_argument("--conv-mode", type=str, default=None)
      parser.add_argument("--num-chunks", type=int, default=1)
      parser.add_argument("--chunk-idx", type=int, default=0)
      parser.add_argument("--model-max-length", type=int, default=None)
  
      return parser.parse_args()
  
file_path: llama-vid/llamavid/eval/model_msvd_qa.py
imports: import argparse
  import torch
  from llamavid.constants import IMAGE_TOKEN_INDEX, DEFAULT_IMAGE_TOKEN, DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN
  from llamavid.conversation import conv_templates, SeparatorStyle
  from llamavid.model.builder import load_pretrained_model
  from llava.utils import disable_torch_init
  from llava.mm_utils import tokenizer_image_token, get_model_name_from_path, KeywordsStoppingCriteria
  import json
  import os
  import math
  from tqdm import tqdm
  from decord import VideoReader, cpu
label_desc: Use image node_id 3 for calling a global function with example usage: parse_args() and returns: parser