Merge branch 'main' into feat/plugins

api/.env.example

@@ -433,3 +433,5 @@ RESET_PASSWORD_TOKEN_EXPIRY_MINUTES=5
 
 CREATE_TIDB_SERVICE_JOB_ENABLED=false
 
+# Maximum number of submitted thread count in a ThreadPool for parallel node execution
+MAX_SUBMIT_COUNT=100

api/configs/feature/__init__.py

@@ -439,6 +439,17 @@ class WorkflowConfig(BaseSettings):
     )
 
 
+class WorkflowNodeExecutionConfig(BaseSettings):
+    """
+    Configuration for workflow node execution
+    """
+
+    MAX_SUBMIT_COUNT: PositiveInt = Field(
+        description="Maximum number of submitted thread count in a ThreadPool for parallel node execution",
+        default=100,
+    )
+
+
 class AuthConfig(BaseSettings):
     """
     Configuration for authentication and OAuth
@@ -775,6 +786,7 @@ class FeatureConfig(
     ToolConfig,
     UpdateConfig,
     WorkflowConfig,
+    WorkflowNodeExecutionConfig,
     WorkspaceConfig,
     LoginConfig,
     # hosted services config

api/configs/packaging/__init__.py

@@ -9,7 +9,7 @@ class PackagingInfo(BaseSettings):
 
     CURRENT_VERSION: str = Field(
         description="Dify version",
-        default="0.13.2",
+        default="0.14.0",
     )
 
     COMMIT_SHA: str = Field(

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

@@ -10,6 +10,7 @@ from core.model_runtime.entities.llm_entities import (
 from core.model_runtime.entities.message_entities import (
     AssistantPromptMessage,
     PromptMessage,
+    PromptMessageContentType,
     PromptMessageTool,
     SystemPromptMessage,
     ToolPromptMessage,
@@ -105,7 +106,11 @@ class BaichuanLanguageModel(LargeLanguageModel):
             if isinstance(message.content, str):
                 message_dict = {"role": "user", "content": message.content}
             else:
-                raise ValueError("User message content must be str")
+                for message_content in message.content:
+                    if message_content.type == PromptMessageContentType.TEXT:
+                        message_dict = {"role": "user", "content": message_content.data}
+                    elif message_content.type == PromptMessageContentType.IMAGE:
+                        raise ValueError("Content object type not support image_url")
         elif isinstance(message, AssistantPromptMessage):
             message = cast(AssistantPromptMessage, message)
             message_dict = {"role": "assistant", "content": message.content}

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

@@ -24,6 +24,9 @@ class DeepseekLargeLanguageModel(OAIAPICompatLargeLanguageModel):
         user: Optional[str] = None,
     ) -> Union[LLMResult, Generator]:
         self._add_custom_parameters(credentials)
+        # {"response_format": "xx"} need convert to {"response_format": {"type": "xx"}}
+        if "response_format" in model_parameters:
+            model_parameters["response_format"] = {"type": model_parameters.get("response_format")}
         return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream)
 
     def validate_credentials(self, model: str, credentials: dict) -> None:

api/core/model_runtime/model_providers/volcengine_maas/legacy/client.py

@@ -68,7 +68,12 @@ class MaaSClient(MaasService):
                 content = []
                 for message_content in message.content:
                     if message_content.type == PromptMessageContentType.TEXT:
-                        raise ValueError("Content object type only support image_url")
+                        content.append(
+                            {
+                                "type": "text",
+                                "text": message_content.data,
+                            }
+                        )
                     elif message_content.type == PromptMessageContentType.IMAGE:
                         message_content = cast(ImagePromptMessageContent, message_content)
                         image_data = re.sub(r"^data:image\/[a-zA-Z]+;base64,", "", message_content.data)

api/core/workflow/graph_engine/graph_engine.py

@@ -9,6 +9,7 @@ from typing import Any, Optional, cast
 
 from flask import Flask, current_app
 
+from configs import dify_config
 from core.app.apps.base_app_queue_manager import GenerateTaskStoppedError
 from core.app.entities.app_invoke_entities import InvokeFrom
 from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult
@@ -52,7 +53,12 @@ logger = logging.getLogger(__name__)
 
 class GraphEngineThreadPool(ThreadPoolExecutor):
     def __init__(
-        self, max_workers=None, thread_name_prefix="", initializer=None, initargs=(), max_submit_count=100
+        self,
+        max_workers=None,
+        thread_name_prefix="",
+        initializer=None,
+        initargs=(),
+        max_submit_count=dify_config.MAX_SUBMIT_COUNT,
     ) -> None:
         super().__init__(max_workers, thread_name_prefix, initializer, initargs)
         self.max_submit_count = max_submit_count
@@ -92,7 +98,7 @@ class GraphEngine:
         max_execution_time: int,
         thread_pool_id: Optional[str] = None,
     ) -> None:
-        thread_pool_max_submit_count = 100
+        thread_pool_max_submit_count = dify_config.MAX_SUBMIT_COUNT
         thread_pool_max_workers = 10
 
         # init thread pool

api/core/workflow/nodes/iteration/iteration_node.py

@@ -163,7 +163,9 @@ class IterationNode(BaseNode[IterationNodeData]):
             if self.node_data.is_parallel:
                 futures: list[Future] = []
                 q: Queue = Queue()
-                thread_pool = GraphEngineThreadPool(max_workers=self.node_data.parallel_nums, max_submit_count=100)
+                thread_pool = GraphEngineThreadPool(
+                    max_workers=self.node_data.parallel_nums, max_submit_count=dify_config.MAX_SUBMIT_COUNT
+                )
                 for index, item in enumerate(iterator_list_value):
                     future: Future = thread_pool.submit(
                         self._run_single_iter_parallel,

api/models/workflow.py

@@ -225,8 +225,10 @@ class Workflow(db.Model):
         from models.tools import WorkflowToolProvider
 
         return (
-            db.session.query(WorkflowToolProvider).filter(WorkflowToolProvider.app_id == self.app_id).first()
-            is not None
+            db.session.query(WorkflowToolProvider)
+            .filter(WorkflowToolProvider.tenant_id == self.tenant_id, WorkflowToolProvider.app_id == self.app_id)
+            .count()
+            > 0
         )
 
     @property