code: def predict(self, model_name: str, data, version=None, params=None):
      model_metadata = self.project.get_model(model_name)
      if model_metadata is None:
          raise Exception(f"Can't find model '{model_name}'")
      model_metadata = model_metadata["metadata"]
      if model_metadata["update_status"] == "available":
          raise Exception(
              f"model '{model_name}' is obsolete and needs to be updated. Run 'RETRAIN {model_name};'"
          )
      handler = self.integration_controller.get_handler(
          model_metadata["engine_name"]
      )
      return handler.predict(
          model_name,
          data,
          project_name=self.project.name,
          version=version,
          params=params,
      )
  
file_path: mindsdb/mindsdb/api/executor/datahub/datanodes/project_datanode.py
imports: from copy import deepcopy
  import pandas
  from mindsdb_sql import parse_sql
  from mindsdb_sql.parser.ast import BinaryOperation, Identifier, Constant, Update, Select, Delete
  from mindsdb.utilities.exception import EntityNotExistsError
  from mindsdb.api.executor.datahub.datanodes.datanode import DataNode
  from mindsdb.api.executor.datahub.classes.tables_row import TablesRow
  from mindsdb.api.executor import SQLQuery
  from mindsdb.api.executor.utilities.sql import query_df
  from mindsdb.interfaces.query_context.context_controller import query_context_controller
label_desc: Use image node_id 6 for calling the ProjectDataNode obj's underlying member method code with example usage: obj.predict(model_name, data, version, params) and returns: handler