fix update dataset failed when embedding model is not exist (#6920)

langgenius · Aug 2, 2024 · 048bc4c · 048bc4c
1 parent 4d0a6cc
commit 048bc4c
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Showing 2 changed files with 29 additions and 2 deletions.
diff --git a/api/controllers/console/datasets/datasets.py b/api/controllers/console/datasets/datasets.py
@@ -189,8 +189,6 @@ def patch(self, dataset_id):
         dataset = DatasetService.get_dataset(dataset_id_str)
         if dataset is None:
             raise NotFound("Dataset not found.")
-        # check user's model setting
-        DatasetService.check_dataset_model_setting(dataset)
 
         parser = reqparse.RequestParser()
         parser.add_argument('name', nullable=False,
@@ -215,6 +213,13 @@ def patch(self, dataset_id):
         args = parser.parse_args()
         data = request.get_json()
 
+        # check embedding model setting
+        if data.get('indexing_technique') == 'high_quality':
+            DatasetService.check_embedding_model_setting(dataset.tenant_id,
+                                                         data.get('embedding_model_provider'),
+                                                         data.get('embedding_model')
+                                                         )
+
         # The role of the current user in the ta table must be admin, owner, editor, or dataset_operator
         DatasetPermissionService.check_permission(
             current_user, dataset, data.get('permission'), data.get('partial_member_list')

diff --git a/api/services/dataset_service.py b/api/services/dataset_service.py
@@ -197,6 +197,28 @@ def check_dataset_model_setting(dataset):
                     f"{ex.description}"
                 )
 
+    @staticmethod
+    def check_embedding_model_setting(tenant_id: str, embedding_model_provider: str, embedding_model:str):
+        try:
+            model_manager = ModelManager()
+            model_manager.get_model_instance(
+                tenant_id=tenant_id,
+                provider=embedding_model_provider,
+                model_type=ModelType.TEXT_EMBEDDING,
+                model=embedding_model
+            )
+        except LLMBadRequestError:
+            raise ValueError(
+                "No Embedding Model available. Please configure a valid provider "
+                "in the Settings -> Model Provider."
+            )
+        except ProviderTokenNotInitError as ex:
+            raise ValueError(
+                f"The dataset in unavailable, due to: "
+                f"{ex.description}"
+            )
+
+
     @staticmethod
     def update_dataset(dataset_id, data, user):
         data.pop('partial_member_list', None)