code: def get_meta(
      model_path: Union[str, Path], existing_meta: Dict[str, Any]
  ) -> Dict[str, Any]:
      meta: Dict[str, Any] = {
          "lang": "en",
          "name": "pipeline",
          "version": "0.0.0",
          "description": "",
          "author": "",
          "email": "",
          "url": "",
          "license": "MIT",
      }
      nlp = util.load_model_from_path(Path(model_path))
      meta.update(nlp.meta)
      meta["spacy_version"] = util.get_minor_version_range(
          about.__version__
      )
      meta.update(existing_meta)
      meta["vectors"] = {
          "width": nlp.vocab.vectors_length,
          "vectors": len(nlp.vocab.vectors),
          "keys": nlp.vocab.vectors.n_keys,
          "name": nlp.vocab.vectors.name,
      }
      if about.__title__ != "spacy":
          meta["parent_package"] = about.__title__
      meta.setdefault("requirements", [])
      # Update the requirements with all third-party packages in the config
      existing_reqs = [
          util.split_requirement(req)[0] for req in meta["requirements"]
      ]
      reqs = get_third_party_dependencies(
          nlp.config, exclude=existing_reqs
      )
      meta["requirements"].extend(reqs)
      return meta
  
imports: import os
  import re
  import shutil
  import subprocess
  import sys
  from collections import defaultdict
  from pathlib import Path
  from typing import Any, Dict, List, Optional, Tuple, Union, cast
  import srsly
  from catalogue import RegistryError
  from thinc.api import Config
  from wasabi import MarkdownRenderer, Printer, get_raw_input
  from ..None import about, util
  from ..compat import importlib_metadata
  from ..schemas import ModelMetaSchema, validate
  from ._util import SDIST_SUFFIX, WHEEL_SUFFIX, Arg, Opt, app, string_to_list
label_desc: Use image node_id 8 for calling a global function with example usage: get_meta(model_path, existing_meta) and returns: meta