Merge branch 'fix/refresh-token' into deploy/dev

api/controllers/inner_api/workspace/workspace.py

@@ -21,7 +21,7 @@ class EnterpriseWorkspace(Resource):
         if account is None:
             return {"message": "owner account not found."}, 404
 
-        tenant = TenantService.create_tenant(args["name"])
+        tenant = TenantService.create_tenant(args["name"], is_from_dashboard=True)
         TenantService.create_tenant_member(tenant, account, role="owner")
 
         tenant_was_created.send(tenant)

api/core/model_runtime/model_providers/azure_openai/azure_openai.yaml

@@ -53,6 +53,9 @@ model_credential_schema:
       type: select
       required: true
       options:
+        - label:
+            en_US: 2024-10-01-preview
+          value: 2024-10-01-preview
         - label:
             en_US: 2024-09-01-preview
           value: 2024-09-01-preview

api/core/model_runtime/model_providers/azure_openai/llm/llm.py

@@ -45,9 +45,7 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
         stream: bool = True,
         user: Optional[str] = None,
     ) -> Union[LLMResult, Generator]:
-        base_model_name = credentials.get("base_model_name")
+        base_model_name = self._get_base_model_name(credentials)
-        if not base_model_name:
-            raise ValueError("Base Model Name is required")
         ai_model_entity = self._get_ai_model_entity(base_model_name=base_model_name, model=model)
 
         if ai_model_entity and ai_model_entity.entity.model_properties.get(ModelPropertyKey.MODE) == LLMMode.CHAT.value:
@@ -81,9 +79,7 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
         prompt_messages: list[PromptMessage],
         tools: Optional[list[PromptMessageTool]] = None,
     ) -> int:
-        base_model_name = credentials.get("base_model_name")
+        base_model_name = self._get_base_model_name(credentials)
-        if not base_model_name:
-            raise ValueError("Base Model Name is required")
         model_entity = self._get_ai_model_entity(base_model_name=base_model_name, model=model)
         if not model_entity:
             raise ValueError(f"Base Model Name {base_model_name} is invalid")
@@ -108,9 +104,7 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
         if "base_model_name" not in credentials:
             raise CredentialsValidateFailedError("Base Model Name is required")
 
-        base_model_name = credentials.get("base_model_name")
+        base_model_name = self._get_base_model_name(credentials)
-        if not base_model_name:
-            raise CredentialsValidateFailedError("Base Model Name is required")
         ai_model_entity = self._get_ai_model_entity(base_model_name=base_model_name, model=model)
 
         if not ai_model_entity:
@@ -149,9 +143,7 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
             raise CredentialsValidateFailedError(str(ex))
 
     def get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]:
-        base_model_name = credentials.get("base_model_name")
+        base_model_name = self._get_base_model_name(credentials)
-        if not base_model_name:
-            raise ValueError("Base Model Name is required")
         ai_model_entity = self._get_ai_model_entity(base_model_name=base_model_name, model=model)
         return ai_model_entity.entity if ai_model_entity else None
 
@@ -308,11 +300,6 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
 
         if tools:
             extra_model_kwargs["tools"] = [helper.dump_model(PromptMessageFunction(function=tool)) for tool in tools]
-            # extra_model_kwargs['functions'] = [{
-            #     "name": tool.name,
-            #     "description": tool.description,
-            #     "parameters": tool.parameters
-            # } for tool in tools]
 
         if stop:
             extra_model_kwargs["stop"] = stop
@@ -769,3 +756,9 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
                 ai_model_entity_copy.entity.label.en_US = model
                 ai_model_entity_copy.entity.label.zh_Hans = model
                 return ai_model_entity_copy
+
+    def _get_base_model_name(self, credentials: dict) -> str:
+        base_model_name = credentials.get("base_model_name")
+        if not base_model_name:
+            raise ValueError("Base Model Name is required")
+        return base_model_name

api/core/tools/entities/tool_entities.py

@@ -204,7 +204,7 @@ class ToolParameter(BaseModel):
                         return str(value)
 
             except Exception:
-                raise ValueError(f"The tool parameter value {value} is not in correct type of {parameter_type}.")
+                raise ValueError(f"The tool parameter value {value} is not in correct type.")
 
     class ToolParameterForm(Enum):
         SCHEMA = "schema"  # should be set while adding tool

api/core/tools/provider/builtin/siliconflow/tools/stable_diffusion.py

@@ -5,9 +5,12 @@ import requests
 from core.tools.entities.tool_entities import ToolInvokeMessage
 from core.tools.tool.builtin_tool import BuiltinTool
 
-SDURL = {
+SILICONFLOW_API_URL = "https://api.siliconflow.cn/v1/image/generations"
-    "sd_3": "https://api.siliconflow.cn/v1/stabilityai/stable-diffusion-3-medium/text-to-image",
+
-    "sd_xl": "https://api.siliconflow.cn/v1/stabilityai/stable-diffusion-xl-base-1.0/text-to-image",
+SD_MODELS = {
+    "sd_3": "stabilityai/stable-diffusion-3-medium",
+    "sd_xl": "stabilityai/stable-diffusion-xl-base-1.0",
+    "sd_3.5_large": "stabilityai/stable-diffusion-3-5-large",
 }
 
 
@@ -22,9 +25,10 @@ class StableDiffusionTool(BuiltinTool):
         }
 
         model = tool_parameters.get("model", "sd_3")
-        url = SDURL.get(model)
+        sd_model = SD_MODELS.get(model)
 
         payload = {
+            "model": sd_model,
             "prompt": tool_parameters.get("prompt"),
             "negative_prompt": tool_parameters.get("negative_prompt", ""),
             "image_size": tool_parameters.get("image_size", "1024x1024"),
@@ -34,7 +38,7 @@ class StableDiffusionTool(BuiltinTool):
             "num_inference_steps": tool_parameters.get("num_inference_steps", 20),
         }
 
-        response = requests.post(url, json=payload, headers=headers)
+        response = requests.post(SILICONFLOW_API_URL, json=payload, headers=headers)
         if response.status_code != 200:
             return self.create_text_message(f"Got Error Response:{response.text}")
 

api/core/tools/provider/builtin/siliconflow/tools/stable_diffusion.yaml

@@ -40,6 +40,9 @@ parameters:
       - value: sd_xl
         label:
           en_US: Stable Diffusion XL
+      - value: sd_3.5_large
+        label:
+          en_US: Stable Diffusion 3.5 Large
     default: sd_3
     label:
       en_US: Choose Image Model

api/services/account_service.py

@@ -486,9 +486,13 @@ def _get_login_cache_key(*, account_id: str, token: str):
 
 class TenantService:
     @staticmethod
-    def create_tenant(name: str, is_setup: Optional[bool] = False) -> Tenant:
+    def create_tenant(name: str, is_setup: Optional[bool] = False, is_from_dashboard: Optional[bool] = False) -> Tenant:
         """Create tenant"""
-        if not FeatureService.get_system_features().is_allow_create_workspace and not is_setup:
+        if (
+            not FeatureService.get_system_features().is_allow_create_workspace
+            and not is_setup
+            and not is_from_dashboard
+        ):
             from controllers.console.error import NotAllowedCreateWorkspace
 
             raise NotAllowedCreateWorkspace()

web/hooks/use-refresh-token.ts

@@ -41,6 +41,7 @@ const useRefreshToken = () => {
       return new Error('No access token or refresh token found')
     }
     if (localStorage?.getItem('is_refreshing') === '1') {
+      clearTimeout(timer.current)
       timer.current = setTimeout(() => {
         getNewAccessToken()
       }, 1000)
@@ -61,12 +62,14 @@ const useRefreshToken = () => {
       localStorage?.setItem('console_token', access_token)
       localStorage?.setItem('refresh_token', refresh_token)
       const newTokenExpireTime = getExpireTime(access_token)
+      clearTimeout(timer.current)
       timer.current = setTimeout(() => {
         getNewAccessToken()
       }, newTokenExpireTime - advanceTime.current - getCurrentTimeStamp())
     }
     else {
       const newTokenExpireTime = getExpireTime(currentAccessToken)
+      clearTimeout(timer.current)
       timer.current = setTimeout(() => {
         getNewAccessToken()
       }, newTokenExpireTime - advanceTime.current - getCurrentTimeStamp())
@@ -74,8 +77,15 @@ const useRefreshToken = () => {
     return null
   }, [getExpireTime, getCurrentTimeStamp, handleError])
 
+  const handleVisibilityChange = useCallback(() => {
+    if (document.visibilityState === 'visible')
+      getNewAccessToken()
+  }, [])
+
   useEffect(() => {
+    window.addEventListener('visibilitychange', handleVisibilityChange)
     return () => {
+      window.removeEventListener('visibilitychange', handleVisibilityChange)
       clearTimeout(timer.current)
       localStorage?.removeItem('is_refreshing')
     }