text: """
  Transformers Pipeline Implementation
  """
  from relevanceai.operations_new.base import OperationBase
  from typing import Optional
  
  
  class TransformersPipelineBase(OperationBase):
      def __init__(self, text_fields: list, pipeline, output_field: Optional[str] = None):
          self.text_fields = text_fields
          self.pipeline = pipeline
          self.task: str = pipeline.task
          self._name: str = pipeline.tokenizer.name_or_path
          self.output_field = (
              self._generate_output_field() if output_field is None else output_field
          )
  
      @property
      def name(self):
          if self._name is not None:
              return self._name
          else:
              return "transformers-pipeline"
  
      def transform(self, documents):
          for text_field in self.text_fields:
              texts = self.get_field_across_documents(text_field, documents)
              values = self.pipeline(texts)
              self.set_field_across_documents(self.output_field, values, documents)
          return documents
  
      def _generate_output_field(self):
          return f"_{self.task}_." + self.name + "." + ".".join(self.text_fields)
  