code: def insert_in_background_multiple(
      video_path: str,
      output_path: str,
      background_path: str,
      src_ids: List[str],
      additional_video_paths: List[str],
      seed: Optional[int] = None,
      min_source_segment_duration: float = 5.0,
      max_source_segment_duration: float = 20.0,
      min_background_segment_duration: float = 2.0,
      min_result_video_duration: float = 30.0,
      max_result_video_duration: float = 60.0,
      transition: Optional[af.TransitionConfig] = None,
      metadata: Optional[List[Dict[str, Any]]] = None,
  ) -> str:
      """
      Places the video (and the additional videos) in the middle of the background video.
  
      @param video_path: the path of the main video to be augmented.
  
      @param output_path: the path in which the output video will be stored.
  
      @param background_path: the path of the video in which to insert the main
          (and additional) video.
  
      @param src_ids: the list of identifiers for the main video and additional videos.
  
      @param additional_video_paths: list of additional video paths to be
          inserted alongside the main video; one clip from each of the input
          videos will be inserted in order.
  
      @param seed: if provided, this will set the random seed to ensure consistency
          between runs.
  
      @param min_source_segment_duration: minimum duration in seconds of the source
          segments that will be inserted in the background video.
  
      @param max_source_segment_duration: maximum duration in seconds of the source
          segments that will be inserted in the background video.
  
      @param min_background_segment_duration: minimum duration in seconds of a background segment.
  
      @param min_result_video_duration: minimum duration in seconds of the output video.
  
      @param max_result_video_duration: maximum duration in seconds of the output video.
  
      @param transition: optional transition configuration to apply between the clips.
  
      @param metadata: if set to be a list, metadata about the function execution including
          its name, the source & dest duration, fps, etc. will be appended to the inputted
          list. If set to None, no metadata will be appended or returned
  
      @returns: the path to the augmented video
      """
      if additional_video_paths:
          assert len(additional_video_paths) + 1 == len(
              src_ids
          ), "src_ids need to be specified for the main video and all additional videos."
      func_kwargs = helpers.get_func_kwargs(
          metadata, locals(), video_path
      )
      rng = (
          np.random.RandomState(seed) if seed is not None else np.random
      )
  
      local_path = utils.pathmgr.get_local_path(video_path)
      additional_local_paths = (
          [
              utils.pathmgr.get_local_path(p)
              for p in additional_video_paths
          ]
          if additional_video_paths
          else []
      )
      bkg_local_path = utils.pathmgr.get_local_path(background_path)
      src_paths = [
          local_path,
      ] + additional_local_paths
  
      src_video_durations = np.array(
          [
              float(helpers.get_video_info(v)["duration"])
              for v in src_paths
          ]
      )
      bkg_duration = float(
          helpers.get_video_info(bkg_local_path)["duration"]
      )
  
      src_segment_durations = (
          rng.random_sample(len(src_video_durations))
          * (max_source_segment_duration - min_source_segment_duration)
          + min_source_segment_duration
      )
      src_segment_durations = np.minimum(
          src_segment_durations, src_video_durations
      )
      src_segment_starts = rng.random(len(src_video_durations)) * (
          src_video_durations - src_segment_durations
      )
      src_segment_ends = src_segment_starts + src_segment_durations
  
      sum_src_duration = np.sum(src_segment_durations)
      required_result_duration = (
          len(src_segment_durations) + 1
      ) * min_background_segment_duration + sum_src_duration
      if required_result_duration > max_result_video_duration:
          raise ValueError(
              "Failed to generate config for source segments in insert_in_background_multiple."
          )
  
      duration_budget = (
          max_result_video_duration - required_result_duration
      )
      bkg_budget = rng.random() * duration_budget
      overall_bkg_needed_duration = (
          len(src_segment_durations) + 1
      ) * min_background_segment_duration + bkg_budget
  
      num_loops_needed = 0
      if overall_bkg_needed_duration > bkg_duration:
          num_loops_needed = math.ceil(
              overall_bkg_needed_duration / bkg_duration
          )
  
      # Now sample insertion points by picking len(src_segment_durations) points in the interval [0, bkg_budget)
      # Then sort the segments and add spacing for the minimum background segment duration.
      bkg_insertion_points = (
          np.sort(rng.random(len(src_segment_durations)) * bkg_budget)
          + np.arange(len(src_segment_durations))
          * min_background_segment_duration
      )
      last_bkg_point = overall_bkg_needed_duration
      dst_starts = bkg_insertion_points + np.concatenate(
          (
              [
                  0.0,
              ],
              np.cumsum(src_segment_durations)[:-1],
          )
      )
  
      # Start applying transforms.
      with tempfile.TemporaryDirectory() as tmpdir:
          # First, loop through background video if needed.
          if num_loops_needed > 0:
              buf = os.path.join(tmpdir, "bkg_loop.mp4")
              loop(bkg_local_path, buf, num_loops=num_loops_needed)
              bkg_path = buf
          else:
              bkg_path = bkg_local_path
  
          bkg_videos = []
          # Sample background segments.
          prev = 0.0
          for i, pt in enumerate(bkg_insertion_points):
              out_path = os.path.join(tmpdir, f"bkg_{i}.mp4")
              trim(bkg_path, out_path, start=prev, end=pt)
              prev = pt
              bkg_videos.append(out_path)
  
          # last background segment
          last_bkg_path = os.path.join(tmpdir, "bkg_last.mp4")
          trim(bkg_path, last_bkg_path, start=prev, end=last_bkg_point)
  
          src_videos = []
          # Sample source segments.
          for i, seg in enumerate(
              zip(src_segment_starts, src_segment_ends)
          ):
              out_path = os.path.join(tmpdir, f"src_{i}.mp4")
              trim(src_paths[i], out_path, start=seg[0], end=seg[1])
              src_videos.append(out_path)
  
          all_videos = [
              v for pair in zip(bkg_videos, src_videos) for v in pair
          ] + [
              last_bkg_path,
          ]
          concat(all_videos, output_path, 1, transition=transition)
  
      if metadata is not None:
          helpers.get_metadata(
              metadata=metadata,
              function_name="insert_in_background_multiple",
              src_segment_starts=src_segment_starts,
              src_segment_ends=src_segment_ends,
              bkg_insertion_points=bkg_insertion_points,
              **func_kwargs,
          )
  
      return output_path
  
imports: import functools
  import math
  import os
  import shutil
  import tempfile
  from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  import numpy
  from augly import audio, image, utils
  from augly.audio import utils
  from augly.video import helpers, utils
  from augly.video.augmenters import cv2, ffmpeg
label_desc: Use image node_id 20 for calling a global function with example usage: insert_in_background_multiple(video_path, output_path, background_path, src_ids, additional_video_paths, seed, min_source_segment_duration, max_source_segment_duration, min_background_segment_duration, min_result_video_duration, max_result_video_duration, transition, metadata) and returns: output_path