code: def log_everything():
      exp_id = mlflow.create_experiment(
          uuid.uuid4().hex, tags={"tag": "experiment"}
      )
      mlflow.set_experiment(experiment_id=exp_id)
      with mlflow.start_run() as run:
          mlflow.log_params({"param": "value"})
          mlflow.log_metrics({"metric": 0.1})
          mlflow.set_tags({"tag": "run"})
          model_info = mlflow.pyfunc.log_model(
              python_model=Model(), artifact_path="model"
          )
  
      client = mlflow.MlflowClient()
      registered_model_name = uuid.uuid4().hex
      client.create_registered_model(
          registered_model_name,
          tags={"tag": "registered_model"},
          description="description",
      )
      client.create_model_version(
          registered_model_name,
          model_info.model_uri,
          run_id=run.info.run_id,
          tags={"tag": "model_version"},
          run_link="run_link",
          description="description",
      )
  
file_path: mlflow/tests/db/check_migration.py
imports: import os
  import uuid
  from pathlib import Path
  import click
  import pandas
  import sqlalchemy
  import mlflow
  from mlflow.store.model_registry.dbmodels.models import SqlModelVersion, SqlModelVersionTag, SqlRegisteredModel, SqlRegisteredModelTag
  from mlflow.store.tracking.dbmodels.models import SqlExperiment, SqlExperimentTag, SqlLatestMetric, SqlMetric, SqlParam, SqlRun, SqlTag
label_desc: Use image node_id 1 for calling a global function with example usage: log_everything() without return types