code: def read_json_chunk(
      chunk,
      encoding,
      errors,
      engine,
      column_name,
      path,
      path_dtype,
      kwargs,
      meta=None,
  ):
      s = io.StringIO(chunk.decode(encoding, errors))
      s.seek(0)
      df = engine(s, orient="records", lines=True, **kwargs)
      if meta is not None and df.empty:
          return meta
  
      if column_name:
          df = add_path_column(df, column_name, path, path_dtype)
  
      return df
  
imports: from __future__ import annotations
  import io
  import os
  from functools import partial
  from itertools import zip_longest
  import pandas
  from fsspec.core import open_files
  from dask.base import compute
  from dask.bytes import read_bytes
  from dask.core import flatten
  from dask.dataframe._compat import PANDAS_GE_200, PANDAS_VERSION
  from dask.dataframe.backends import dataframe_creation_dispatch
  from dask.dataframe.io.io import from_delayed
  from dask.dataframe.utils import insert_meta_param_description, make_meta
  from dask.delayed import delayed
label_desc: Use image node_id 4 for calling a global function with example usage: read_json_chunk(chunk, encoding, errors, engine, column_name, path, path_dtype, kwargs, meta) and returns: df, meta