code: def main(argv: Sequence[str]) -> Optional[dev_server.LitServerType]:
      if len(argv) > 1:
          raise app.UsageError("Too many command-line arguments.")
  
      models = {
          "species classifier": penguin_model.PenguinModel(
              _MODEL_PATH.value
          )
      }
      datasets = {"penguins": penguin_data.PenguinDataset()}
      # Truncate datasets if --max_examples is set.
      if _MAX_EXAMPLES.value is not None:
          for name in datasets:
              logging.info(
                  "Dataset: '%s' with %d examples",
                  name,
                  len(datasets[name]),
              )
              datasets[name] = datasets[name].slice[
                  : _MAX_EXAMPLES.value
              ]
              logging.info(
                  "  truncated to %d examples", len(datasets[name])
              )
  
      generators = {
          "Minimal Targeted Counterfactuals": minimal_targeted_counterfactuals.TabularMTC()
      }
      lit_demo = dev_server.Server(
          models,
          datasets,
          generators=generators,
          layouts=CUSTOM_LAYOUTS,
          **server_flags.get_flags(),
      )
      return lit_demo.serve()
  
file_path: lit/lit_nlp/examples/penguin_demo.py
imports: from collections.abc import Sequence
  import sys
  from typing import Optional
  from absl import app
  from absl import flags
  from absl import logging
  from lit_nlp import dev_server
  from lit_nlp import server_flags
  from lit_nlp.api import layout
  from lit_nlp.components import minimal_targeted_counterfactuals
  from lit_nlp.examples.datasets import penguin_data
  from lit_nlp.examples.models import penguin_model
label_desc: Use image node_id 2 for calling a global function with example usage: main(argv) and returns: lit_demo