code: def build_schema(self, fields, language):
          
          content_field_name = ''
          mapping = {
              DJANGO_CT: {'type': 'string', 'index': 'not_analyzed', 'include_in_all': False},
              DJANGO_ID: {'type': 'string', 'index': 'not_analyzed', 'include_in_all': False},
          }
  
          for field_name, field_class in fields.items():
              field_mapping = FIELD_MAPPINGS.get(
                  field_class.field_type, DEFAULT_FIELD_MAPPING).copy()
              if field_class.boost != 1.0:
                  field_mapping['boost'] = field_class.boost
  
              if field_class.document is True:
                  content_field_name = field_class.index_fieldname
  
              # Do this last to override `text` fields.
              if field_mapping['type'] == 'string':
                  # Use the language analyzer for text fields.
                  if field_mapping['analyzer'] == DEFAULT_FIELD_MAPPING['analyzer']:
                      field_mapping['analyzer'] = get_analyzer_for(language)
                  if field_class.indexed is False or hasattr(field_class, 'facet_for'):
                      field_mapping['index'] = 'not_analyzed'
                      del field_mapping['analyzer']
  
              mapping[field_class.index_fieldname] = field_mapping
  
          return content_field_name, mapping
docs: Build the index schema for the given field. New argument language.
          :param fields:
          :param language: the language code
          :return: a dictionary wit the field name (string) and the
                   mapping configuration (dictionary)