Feat/api validate model provider (#21582)

Co-authored-by: crazywoola <427733928@qq.com>

api/controllers/service_api/dataset/dataset.py

         parser.add_argument("embedding_model_provider", type=str, required=False, nullable=True, location="json")
 
         args = parser.parse_args()
+
+        if args.get("embedding_model_provider"):
+            DatasetService.check_embedding_model_setting(
+                tenant_id, args.get("embedding_model_provider"), args.get("embedding_model")
+            )
+        if (
+            args.get("retrieval_model")
+            and args.get("retrieval_model").get("reranking_model")
+            and args.get("retrieval_model").get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                tenant_id,
+                args.get("retrieval_model").get("reranking_model").get("reranking_provider_name"),
+                args.get("retrieval_model").get("reranking_model").get("reranking_model_name"),
+            )
+
         try:
             dataset = DatasetService.create_empty_dataset(
                 tenant_id=tenant_id,
         data = request.get_json()
 
         # check embedding model setting
-        if data.get("indexing_technique") == "high_quality":
+        if data.get("indexing_technique") == "high_quality" or data.get("embedding_model_provider"):
             DatasetService.check_embedding_model_setting(
                 dataset.tenant_id, data.get("embedding_model_provider"), data.get("embedding_model")
             )
+        if (
+            data.get("retrieval_model")
+            and data.get("retrieval_model").get("reranking_model")
+            and data.get("retrieval_model").get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                dataset.tenant_id,
+                data.get("retrieval_model").get("reranking_model").get("reranking_provider_name"),
+                data.get("retrieval_model").get("reranking_model").get("reranking_model_name"),
+            )
 
         # The role of the current user in the ta table must be admin, owner, editor, or dataset_operator
         DatasetPermissionService.check_permission(

api/controllers/service_api/dataset/document.py

 from fields.document_fields import document_fields, document_status_fields
 from libs.login import current_user
 from models.dataset import Dataset, Document, DocumentSegment
-from services.dataset_service import DocumentService
+from services.dataset_service import DatasetService, DocumentService
 from services.entities.knowledge_entities.knowledge_entities import KnowledgeConfig
 from services.file_service import FileService
 
         parser.add_argument("embedding_model_provider", type=str, required=False, nullable=True, location="json")
 
         args = parser.parse_args()
+
         dataset_id = str(dataset_id)
         tenant_id = str(tenant_id)
         dataset = db.session.query(Dataset).filter(Dataset.tenant_id == tenant_id, Dataset.id == dataset_id).first()
         if text is None or name is None:
             raise ValueError("Both 'text' and 'name' must be non-null values.")
 
+        if args.get("embedding_model_provider"):
+            DatasetService.check_embedding_model_setting(
+                tenant_id, args.get("embedding_model_provider"), args.get("embedding_model")
+            )
+        if (
+            args.get("retrieval_model")
+            and args.get("retrieval_model").get("reranking_model")
+            and args.get("retrieval_model").get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                tenant_id,
+                args.get("retrieval_model").get("reranking_model").get("reranking_provider_name"),
+                args.get("retrieval_model").get("reranking_model").get("reranking_model_name"),
+            )
+
         upload_file = FileService.upload_text(text=str(text), text_name=str(name))
         data_source = {
             "type": "upload_file",
         if not dataset:
             raise ValueError("Dataset does not exist.")
 
+        if (
+            args.get("retrieval_model")
+            and args.get("retrieval_model").get("reranking_model")
+            and args.get("retrieval_model").get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                tenant_id,
+                args.get("retrieval_model").get("reranking_model").get("reranking_provider_name"),
+                args.get("retrieval_model").get("reranking_model").get("reranking_model_name"),
+            )
+
         # indexing_technique is already set in dataset since this is an update
         args["indexing_technique"] = dataset.indexing_technique
 
             raise ValueError("indexing_technique is required.")
         args["indexing_technique"] = indexing_technique
 
+        if "embedding_model_provider" in args:
+            DatasetService.check_embedding_model_setting(
+                tenant_id, args["embedding_model_provider"], args["embedding_model"]
+            )
+        if (
+            "retrieval_model" in args
+            and args["retrieval_model"].get("reranking_model")
+            and args["retrieval_model"].get("reranking_model").get("reranking_provider_name")
+        ):
+            DatasetService.check_reranking_model_setting(
+                tenant_id,
+                args["retrieval_model"].get("reranking_model").get("reranking_provider_name"),
+                args["retrieval_model"].get("reranking_model").get("reranking_model_name"),
+            )
+
         # save file info
         file = request.files["file"]
         # check file

api/services/dataset_service.py

         except ProviderTokenNotInitError as ex:
             raise ValueError(ex.description)
 
+    @staticmethod
+    def check_reranking_model_setting(tenant_id: str, reranking_model_provider: str, reranking_model: str):
+        try:
+            model_manager = ModelManager()
+            model_manager.get_model_instance(
+                tenant_id=tenant_id,
+                provider=reranking_model_provider,
+                model_type=ModelType.RERANK,
+                model=reranking_model,
+            )
+        except LLMBadRequestError:
+            raise ValueError(
+                "No Rerank Model available. Please configure a valid provider in the Settings -> Model Provider."
+            )
+        except ProviderTokenNotInitError as ex:
+            raise ValueError(ex.description)
+
     @staticmethod
     def update_dataset(dataset_id, data, user):
         """