feat: dataset support i18n

Author: wxg0103

apps/dataset/serializers/common_serializers.py

@@ -27,6 +27,7 @@
 from dataset.models import Paragraph, Problem, ProblemParagraphMapping, DataSet, File, Image
 from setting.models_provider import get_model
 from smartdoc.conf import PROJECT_DIR
+from django.utils.translation import gettext_lazy as _
 
 
 def zip_dir(zip_path, output=None):
@@ -83,16 +84,16 @@ def list_paragraph(paragraph_list: List[str]):
 
 class MetaSerializer(serializers.Serializer):
     class WebMeta(serializers.Serializer):
-        source_url = serializers.CharField(required=True, error_messages=ErrMessage.char("文档地址"))
+        source_url = serializers.CharField(required=True, error_messages=ErrMessage.char(_('source url')))
         selector = serializers.CharField(required=False, allow_null=True, allow_blank=True,
-                                         error_messages=ErrMessage.char("选择器"))
+                                         error_messages=ErrMessage.char(_('selector')))
 
         def is_valid(self, *, raise_exception=False):
             super().is_valid(raise_exception=True)
             source_url = self.data.get('source_url')
             response = Fork(source_url, []).fork()
             if response.status == 500:
-                raise AppApiException(500, f"url错误,无法解析【{source_url}】")
+                raise AppApiException(500, _('URL error, cannot parse [{source_url}]').format(source_url=source_url))
 
     class BaseMeta(serializers.Serializer):
         def is_valid(self, *, raise_exception=False):
@@ -101,7 +102,7 @@ def is_valid(self, *, raise_exception=False):
 
 class BatchSerializer(ApiMixin, serializers.Serializer):
     id_list = serializers.ListField(required=True, child=serializers.UUIDField(required=True),
-                                    error_messages=ErrMessage.char("id列表"))
+                                    error_messages=ErrMessage.char(_('id list')))
 
     def is_valid(self, *, model=None, raise_exception=False):
         super().is_valid(raise_exception=True)
@@ -111,16 +112,17 @@ def is_valid(self, *, model=None, raise_exception=False):
             if len(model_list) != len(id_list):
                 model_id_list = [str(m.id) for m in model_list]
                 error_id_list = list(filter(lambda row_id: not model_id_list.__contains__(row_id), id_list))
-                raise AppApiException(500, f"id不正确:{error_id_list}")
+                raise AppApiException(500, _('The following id does not exist: {error_id_list}').format(
+                    error_id_list=error_id_list))
 
     @staticmethod
     def get_request_body_api():
         return openapi.Schema(
             type=openapi.TYPE_OBJECT,
             properties={
                 'id_list': openapi.Schema(type=openapi.TYPE_ARRAY, items=openapi.Schema(type=openapi.TYPE_STRING),
-                                          title="主键id列表",
-                                          description="主键id列表")
+                                          title=_('id list'),
+                                          description=_('id list'))
             }
         )
 
@@ -178,9 +180,9 @@ def to_problem_model_list(self):
 def get_embedding_model_by_dataset_id_list(dataset_id_list: List):
     dataset_list = QuerySet(DataSet).filter(id__in=dataset_id_list)
     if len(set([dataset.embedding_mode_id for dataset in dataset_list])) > 1:
-        raise Exception("知识库未向量模型不一致")
+        raise Exception(_('The knowledge base is inconsistent with the vector model'))
     if len(dataset_list) == 0:
-        raise Exception("知识库设置错误,请重新设置知识库")
+        raise Exception(_('Knowledge base setting error, please reset the knowledge base'))
     return ModelManage.get_model(str(dataset_list[0].embedding_mode_id),
                                  lambda _id: get_model(dataset_list[0].embedding_mode))
 
@@ -202,7 +204,7 @@ def get_embedding_model_id_by_dataset_id(dataset_id):
 def get_embedding_model_id_by_dataset_id_list(dataset_id_list: List):
     dataset_list = QuerySet(DataSet).filter(id__in=dataset_id_list)
     if len(set([dataset.embedding_mode_id for dataset in dataset_list])) > 1:
-        raise Exception("知识库未向量模型不一致")
+        raise Exception(_('The knowledge base is inconsistent with the vector model'))
     if len(dataset_list) == 0:
-        raise Exception("知识库设置错误,请重新设置知识库")
+        raise Exception(_('Knowledge base setting error, please reset the knowledge base'))
     return str(dataset_list[0].embedding_mode_id)