feat: add mention node executor

api/core/workflow/graph_engine/event_management/event_handlers.py

@@ -125,6 +125,11 @@ class EventHandler:
         Args:
             event: The node started event
         """
+        # Check if this is a virtual node (extraction node)
+        if self._is_virtual_node(event.node_id):
+            self._handle_virtual_node_started(event)
+            return
+
         # Track execution in domain model
         node_execution = self._graph_execution.get_or_create_node_execution(event.node_id)
         is_initial_attempt = node_execution.retry_count == 0
@@ -164,6 +169,11 @@ class EventHandler:
         Args:
             event: The node succeeded event
         """
+        # Check if this is a virtual node (extraction node)
+        if self._is_virtual_node(event.node_id):
+            self._handle_virtual_node_success(event)
+            return
+
         # Update domain model
         node_execution = self._graph_execution.get_or_create_node_execution(event.node_id)
         node_execution.mark_taken()
@@ -226,6 +236,11 @@ class EventHandler:
         Args:
             event: The node failed event
         """
+        # Check if this is a virtual node (extraction node)
+        if self._is_virtual_node(event.node_id):
+            self._handle_virtual_node_failed(event)
+            return
+
         # Update domain model
         node_execution = self._graph_execution.get_or_create_node_execution(event.node_id)
         node_execution.mark_failed(event.error)
@@ -345,3 +360,57 @@ class EventHandler:
                     self._graph_runtime_state.set_output("answer", value)
             else:
                 self._graph_runtime_state.set_output(key, value)
+
+    def _is_virtual_node(self, node_id: str) -> bool:
+        """
+        Check if node_id represents a virtual sub-node.
+
+        Virtual nodes have IDs in the format: {parent_node_id}.{local_id}
+        We check if the part before '.' exists in graph nodes.
+        """
+        if "." in node_id:
+            parent_id = node_id.rsplit(".", 1)[0]
+            return parent_id in self._graph.nodes
+        return False
+
+    def _handle_virtual_node_started(self, event: NodeRunStartedEvent) -> None:
+        """
+        Handle virtual node started event.
+
+        Virtual nodes don't need full execution tracking, just collect the event.
+        """
+        # Track in response coordinator for stream ordering
+        self._response_coordinator.track_node_execution(event.node_id, event.id)
+
+        # Collect the event
+        self._event_collector.collect(event)
+
+    def _handle_virtual_node_success(self, event: NodeRunSucceededEvent) -> None:
+        """
+        Handle virtual node success event.
+
+        Virtual nodes (extraction nodes) need special handling:
+        - Store outputs in variable pool (for reference by other nodes)
+        - Accumulate token usage
+        - Collect the event for logging
+        - Do NOT process edges or enqueue next nodes (parent node handles that)
+        """
+        self._accumulate_node_usage(event.node_run_result.llm_usage)
+
+        # Store outputs in variable pool
+        self._store_node_outputs(event.node_id, event.node_run_result.outputs)
+
+        # Collect the event
+        self._event_collector.collect(event)
+
+    def _handle_virtual_node_failed(self, event: NodeRunFailedEvent) -> None:
+        """
+        Handle virtual node failed event.
+
+        Virtual nodes (extraction nodes) failures are collected for logging,
+        but the parent node is responsible for handling the error.
+        """
+        self._accumulate_node_usage(event.node_run_result.llm_usage)
+
+        # Collect the event for logging
+        self._event_collector.collect(event)

api/core/workflow/graph_events/node.py

@@ -20,6 +20,12 @@ class NodeRunStartedEvent(GraphNodeEventBase):
     provider_type: str = ""
     provider_id: str = ""
 
+    # Virtual node fields for extraction
+    is_virtual: bool = False
+    parent_node_id: str | None = None
+    extraction_source: str | None = None  # e.g., "llm1.context"
+    extraction_prompt: str | None = None
+
 
 class NodeRunStreamChunkEvent(GraphNodeEventBase):
     # Spec-compliant fields

api/core/workflow/nodes/base/__init__.py

@@ -1,5 +1,13 @@
-from .entities import BaseIterationNodeData, BaseIterationState, BaseLoopNodeData, BaseLoopState, BaseNodeData
+from .entities import (
+    BaseIterationNodeData,
+    BaseIterationState,
+    BaseLoopNodeData,
+    BaseLoopState,
+    BaseNodeData,
+    VirtualNodeConfig,
+)
 from .usage_tracking_mixin import LLMUsageTrackingMixin
+from .virtual_node_executor import VirtualNodeExecutionError, VirtualNodeExecutor
 
 __all__ = [
     "BaseIterationNodeData",
@@ -8,4 +16,7 @@ __all__ = [
     "BaseLoopState",
     "BaseNodeData",
     "LLMUsageTrackingMixin",
+    "VirtualNodeConfig",
+    "VirtualNodeExecutionError",
+    "VirtualNodeExecutor",
 ]

api/core/workflow/nodes/base/entities.py

@@ -167,6 +167,24 @@ class DefaultValue(BaseModel):
         return self
 
 
+class VirtualNodeConfig(BaseModel):
+    """Configuration for a virtual sub-node embedded within a parent node."""
+
+    # Local ID within parent node (e.g., "ext_1")
+    # Will be converted to global ID: "{parent_id}.{id}"
+    id: str
+
+    # Node type (e.g., "llm", "code", "tool")
+    type: str
+
+    # Full node data configuration
+    data: dict[str, Any] = {}
+
+    def get_global_id(self, parent_node_id: str) -> str:
+        """Get the global node ID by combining parent ID and local ID."""
+        return f"{parent_node_id}.{self.id}"
+
+
 class BaseNodeData(ABC, BaseModel):
     title: str
     desc: str | None = None
@@ -175,6 +193,9 @@ class BaseNodeData(ABC, BaseModel):
     default_value: list[DefaultValue] | None = None
     retry_config: RetryConfig = RetryConfig()
 
+    # Virtual sub-nodes that execute before the main node
+    virtual_nodes: list[VirtualNodeConfig] = []
+
     @property
     def default_value_dict(self) -> dict[str, Any]:
         if self.default_value:

api/core/workflow/nodes/base/node.py

@@ -229,6 +229,7 @@ class Node(Generic[NodeDataT]):
         self._node_id = node_id
         self._node_execution_id: str = ""
         self._start_at = naive_utc_now()
+        self._virtual_node_outputs: dict[str, Any] = {}  # Outputs from virtual sub-nodes
 
         raw_node_data = config.get("data") or {}
         if not isinstance(raw_node_data, Mapping):
@@ -270,10 +271,52 @@ class Node(Generic[NodeDataT]):
         """Check if execution should be stopped."""
         return self.graph_runtime_state.stop_event.is_set()
 
+    def _execute_virtual_nodes(self) -> Generator[GraphNodeEventBase, None, dict[str, Any]]:
+        """
+        Execute all virtual sub-nodes defined in node configuration.
+
+        Virtual nodes are complete node definitions that execute before the main node.
+        Each virtual node:
+        - Has its own global ID: "{parent_id}.{local_id}"
+        - Generates standard node events
+        - Stores outputs in the variable pool (via event handling)
+        - Supports retry via parent node's retry config
+
+        Returns:
+            dict mapping local_id -> outputs dict
+        """
+        from .virtual_node_executor import VirtualNodeExecutor
+
+        virtual_nodes = self.node_data.virtual_nodes
+        if not virtual_nodes:
+            return {}
+
+        executor = VirtualNodeExecutor(
+            graph_init_params=self._graph_init_params,
+            graph_runtime_state=self.graph_runtime_state,
+            parent_node_id=self._node_id,
+            parent_retry_config=self.retry_config,
+        )
+
+        return (yield from executor.execute_virtual_nodes(virtual_nodes))
+
+    @property
+    def virtual_node_outputs(self) -> dict[str, Any]:
+        """
+        Get the outputs from virtual sub-nodes.
+
+        Returns:
+            dict mapping local_id -> outputs dict
+        """
+        return self._virtual_node_outputs
+
     def run(self) -> Generator[GraphNodeEventBase, None, None]:
         execution_id = self.ensure_execution_id()
         self._start_at = naive_utc_now()
 
+        # Step 1: Execute virtual sub-nodes before main node execution
+        self._virtual_node_outputs = yield from self._execute_virtual_nodes()
+
         # Create and push start event with required fields
         start_event = NodeRunStartedEvent(
             id=execution_id,

api/core/workflow/nodes/base/virtual_node_executor.py

@@ -0,0 +1,213 @@
+"""
+Virtual Node Executor for running embedded sub-nodes within a parent node.
+
+This module handles the execution of virtual nodes defined in a parent node's
+`virtual_nodes` configuration. Virtual nodes are complete node definitions
+that execute before the parent node.
+
+Example configuration:
+    virtual_nodes:
+      - id: ext_1
+        type: llm
+        data:
+          model: {...}
+          prompt_template: [...]
+"""
+
+import time
+from collections.abc import Generator
+from typing import TYPE_CHECKING, Any
+from uuid import uuid4
+
+from core.workflow.enums import NodeType
+from core.workflow.graph_events import (
+    GraphNodeEventBase,
+    NodeRunFailedEvent,
+    NodeRunRetryEvent,
+    NodeRunStartedEvent,
+    NodeRunSucceededEvent,
+)
+from libs.datetime_utils import naive_utc_now
+
+from .entities import RetryConfig, VirtualNodeConfig
+
+if TYPE_CHECKING:
+    from core.workflow.entities import GraphInitParams
+    from core.workflow.runtime import GraphRuntimeState
+
+
+class VirtualNodeExecutionError(Exception):
+    """Error during virtual node execution"""
+
+    def __init__(self, node_id: str, original_error: Exception):
+        self.node_id = node_id
+        self.original_error = original_error
+        super().__init__(f"Virtual node {node_id} execution failed: {original_error}")
+
+
+class VirtualNodeExecutor:
+    """
+    Executes virtual sub-nodes embedded within a parent node.
+
+    Virtual nodes are complete node definitions that execute before the parent node.
+    Each virtual node:
+    - Has its own global ID: "{parent_id}.{local_id}"
+    - Generates standard node events
+    - Stores outputs in the variable pool
+    - Supports retry via parent node's retry config
+    """
+
+    def __init__(
+        self,
+        *,
+        graph_init_params: "GraphInitParams",
+        graph_runtime_state: "GraphRuntimeState",
+        parent_node_id: str,
+        parent_retry_config: RetryConfig | None = None,
+    ):
+        self._graph_init_params = graph_init_params
+        self._graph_runtime_state = graph_runtime_state
+        self._parent_node_id = parent_node_id
+        self._parent_retry_config = parent_retry_config or RetryConfig()
+
+    def execute_virtual_nodes(
+        self,
+        virtual_nodes: list[VirtualNodeConfig],
+    ) -> Generator[GraphNodeEventBase, None, dict[str, Any]]:
+        """
+        Execute all virtual nodes in order.
+
+        Args:
+            virtual_nodes: List of virtual node configurations
+
+        Yields:
+            Node events from each virtual node execution
+
+        Returns:
+            dict mapping local_id -> outputs dict
+        """
+        results: dict[str, Any] = {}
+
+        for vnode_config in virtual_nodes:
+            global_id = vnode_config.get_global_id(self._parent_node_id)
+
+            # Execute with retry
+            outputs = yield from self._execute_with_retry(vnode_config, global_id)
+            results[vnode_config.id] = outputs
+
+        return results
+
+    def _execute_with_retry(
+        self,
+        vnode_config: VirtualNodeConfig,
+        global_id: str,
+    ) -> Generator[GraphNodeEventBase, None, dict[str, Any]]:
+        """
+        Execute virtual node with retry support.
+        """
+        retry_config = self._parent_retry_config
+        last_error: Exception | None = None
+
+        for attempt in range(retry_config.max_retries + 1):
+            try:
+                return (yield from self._execute_single_node(vnode_config, global_id))
+            except Exception as e:
+                last_error = e
+
+                if attempt < retry_config.max_retries:
+                    # Yield retry event
+                    yield NodeRunRetryEvent(
+                        id=str(uuid4()),
+                        node_id=global_id,
+                        node_type=self._get_node_type(vnode_config.type),
+                        node_title=vnode_config.data.get("title", f"Virtual: {vnode_config.id}"),
+                        start_at=naive_utc_now(),
+                        error=str(e),
+                        retry_index=attempt + 1,
+                    )
+
+                    time.sleep(retry_config.retry_interval_seconds)
+                    continue
+
+                raise VirtualNodeExecutionError(global_id, e) from e
+
+        raise last_error or VirtualNodeExecutionError(global_id, Exception("Unknown error"))
+
+    def _execute_single_node(
+        self,
+        vnode_config: VirtualNodeConfig,
+        global_id: str,
+    ) -> Generator[GraphNodeEventBase, None, dict[str, Any]]:
+        """
+        Execute a single virtual node by instantiating and running it.
+        """
+        from core.workflow.nodes.node_mapping import LATEST_VERSION, NODE_TYPE_CLASSES_MAPPING
+
+        # Build node config
+        node_config: dict[str, Any] = {
+            "id": global_id,
+            "data": {
+                **vnode_config.data,
+                "title": vnode_config.data.get("title", f"Virtual: {vnode_config.id}"),
+            },
+        }
+
+        # Get the node class for this type
+        node_type = self._get_node_type(vnode_config.type)
+        node_mapping = NODE_TYPE_CLASSES_MAPPING.get(node_type)
+        if not node_mapping:
+            raise ValueError(f"No class mapping found for node type: {node_type}")
+
+        node_version = str(vnode_config.data.get("version", "1"))
+        node_cls = node_mapping.get(node_version) or node_mapping.get(LATEST_VERSION)
+        if not node_cls:
+            raise ValueError(f"No class found for node type: {node_type}")
+
+        # Instantiate the node
+        node = node_cls(
+            id=global_id,
+            config=node_config,
+            graph_init_params=self._graph_init_params,
+            graph_runtime_state=self._graph_runtime_state,
+        )
+
+        # Run and collect events
+        outputs: dict[str, Any] = {}
+
+        for event in node.run():
+            # Mark event as coming from virtual node
+            self._mark_event_as_virtual(event, vnode_config)
+            yield event
+
+            if isinstance(event, NodeRunSucceededEvent):
+                outputs = event.node_run_result.outputs or {}
+            elif isinstance(event, NodeRunFailedEvent):
+                raise Exception(event.error or "Virtual node execution failed")
+
+        return outputs
+
+    def _mark_event_as_virtual(
+        self,
+        event: GraphNodeEventBase,
+        vnode_config: VirtualNodeConfig,
+    ) -> None:
+        """Mark event as coming from a virtual node."""
+        if isinstance(event, NodeRunStartedEvent):
+            event.is_virtual = True
+            event.parent_node_id = self._parent_node_id
+
+    def _get_node_type(self, type_str: str) -> NodeType:
+        """Convert type string to NodeType enum."""
+        type_mapping = {
+            "llm": NodeType.LLM,
+            "code": NodeType.CODE,
+            "tool": NodeType.TOOL,
+            "if-else": NodeType.IF_ELSE,
+            "question-classifier": NodeType.QUESTION_CLASSIFIER,
+            "parameter-extractor": NodeType.PARAMETER_EXTRACTOR,
+            "template-transform": NodeType.TEMPLATE_TRANSFORM,
+            "variable-assigner": NodeType.VARIABLE_ASSIGNER,
+            "http-request": NodeType.HTTP_REQUEST,
+            "knowledge-retrieval": NodeType.KNOWLEDGE_RETRIEVAL,
+        }
+        return type_mapping.get(type_str, NodeType.LLM)

api/core/workflow/nodes/tool/tool_node.py

@@ -89,18 +89,20 @@ class ToolNode(Node[ToolNodeData]):
             )
             return
 
-        # get parameters
+        # get parameters (use virtual_node_outputs from base class)
         tool_parameters = tool_runtime.get_merged_runtime_parameters() or []
         parameters = self._generate_parameters(
             tool_parameters=tool_parameters,
             variable_pool=self.graph_runtime_state.variable_pool,
             node_data=self.node_data,
+            virtual_node_outputs=self.virtual_node_outputs,
         )
         parameters_for_log = self._generate_parameters(
             tool_parameters=tool_parameters,
             variable_pool=self.graph_runtime_state.variable_pool,
             node_data=self.node_data,
             for_log=True,
+            virtual_node_outputs=self.virtual_node_outputs,
         )
         # get conversation id
         conversation_id = self.graph_runtime_state.variable_pool.get(["sys", SystemVariableKey.CONVERSATION_ID])
@@ -176,6 +178,7 @@ class ToolNode(Node[ToolNodeData]):
         variable_pool: "VariablePool",
         node_data: ToolNodeData,
         for_log: bool = False,
+        virtual_node_outputs: dict[str, Any] | None = None,
     ) -> dict[str, Any]:
         """
         Generate parameters based on the given tool parameters, variable pool, and node data.
@@ -184,12 +187,17 @@ class ToolNode(Node[ToolNodeData]):
             tool_parameters (Sequence[ToolParameter]): The list of tool parameters.
             variable_pool (VariablePool): The variable pool containing the variables.
             node_data (ToolNodeData): The data associated with the tool node.
+            for_log (bool): Whether to generate parameters for logging.
+            virtual_node_outputs (dict[str, Any] | None): Outputs from virtual sub-nodes.
+                Maps local_id -> outputs dict. Virtual node outputs are also in variable_pool
+                with global IDs like "{parent_id}.{local_id}".
 
         Returns:
             Mapping[str, Any]: A dictionary containing the generated parameters.
 
         """
         tool_parameters_dictionary = {parameter.name: parameter for parameter in tool_parameters}
+        virtual_node_outputs = virtual_node_outputs or {}
 
         result: dict[str, Any] = {}
         for parameter_name in node_data.tool_parameters:
@@ -199,14 +207,25 @@ class ToolNode(Node[ToolNodeData]):
                 continue
             tool_input = node_data.tool_parameters[parameter_name]
             if tool_input.type == "variable":
-                variable = variable_pool.get(tool_input.value)
-                if variable is None:
-                    if parameter.required:
-                        raise ToolParameterError(f"Variable {tool_input.value} does not exist")
-                    continue
-                parameter_value = variable.value
+                # Check if this references a virtual node output (local ID like [ext_1, text])
+                selector = tool_input.value
+                if len(selector) >= 2 and selector[0] in virtual_node_outputs:
+                    # Reference to virtual node output
+                    local_id = selector[0]
+                    var_name = selector[1]
+                    outputs = virtual_node_outputs.get(local_id, {})
+                    parameter_value = outputs.get(var_name)
+                else:
+                    # Normal variable reference
+                    variable = variable_pool.get(selector)
+                    if variable is None:
+                        if parameter.required:
+                            raise ToolParameterError(f"Variable {selector} does not exist")
+                        continue
+                    parameter_value = variable.value
             elif tool_input.type in {"mixed", "constant"}:
-                segment_group = variable_pool.convert_template(str(tool_input.value))
+                template = str(tool_input.value)
+                segment_group = variable_pool.convert_template(template)
                 parameter_value = segment_group.log if for_log else segment_group.text
             else:
                 raise ToolParameterError(f"Unknown tool input type '{tool_input.type}'")

api/tests/fixtures/pav-test-extraction.yml

@@ -0,0 +1,266 @@
+app:
+  description: Test for variable extraction feature
+  icon: 🤖
+  icon_background: '#FFEAD5'
+  mode: advanced-chat
+  name: pav-test-extraction
+  use_icon_as_answer_icon: false
+dependencies:
+- current_identifier: null
+  type: marketplace
+  value:
+    marketplace_plugin_unique_identifier: langgenius/google:0.0.8@3efcf55ffeef9d0f77715e0afb23534952ae0cb385c051d0637e86d71199d1a6
+    version: null
+- current_identifier: null
+  type: marketplace
+  value:
+    marketplace_plugin_unique_identifier: langgenius/tongyi:0.1.16@d8bffbe45418f0c117fb3393e5e40e61faee98f9a2183f062e5a280e74b15d21
+    version: null
+kind: app
+version: 0.5.0
+workflow:
+  conversation_variables: []
+  environment_variables: []
+  features:
+    file_upload:
+      allowed_file_extensions:
+      - .JPG
+      - .JPEG
+      - .PNG
+      - .GIF
+      - .WEBP
+      - .SVG
+      allowed_file_types:
+      - image
+      allowed_file_upload_methods:
+      - local_file
+      - remote_url
+      enabled: false
+      image:
+        enabled: false
+        number_limits: 3
+        transfer_methods:
+        - local_file
+        - remote_url
+      number_limits: 3
+    opening_statement: 你好！我是一个搜索助手，请告诉我你想搜索什么内容。
+    retriever_resource:
+      enabled: true
+    sensitive_word_avoidance:
+      enabled: false
+    speech_to_text:
+      enabled: false
+    suggested_questions: []
+    suggested_questions_after_answer:
+      enabled: false
+    text_to_speech:
+      enabled: false
+      language: ''
+      voice: ''
+  graph:
+    edges:
+    - data:
+        sourceType: start
+        targetType: llm
+      id: 1767773675796-llm
+      source: '1767773675796'
+      sourceHandle: source
+      target: llm
+      targetHandle: target
+      type: custom
+    - data:
+        isInIteration: false
+        isInLoop: false
+        sourceType: llm
+        targetType: tool
+      id: llm-source-1767773709491-target
+      source: llm
+      sourceHandle: source
+      target: '1767773709491'
+      targetHandle: target
+      type: custom
+      zIndex: 0
+    - data:
+        isInIteration: false
+        isInLoop: false
+        sourceType: tool
+        targetType: answer
+      id: tool-source-answer-target
+      source: '1767773709491'
+      sourceHandle: source
+      target: answer
+      targetHandle: target
+      type: custom
+      zIndex: 0
+    nodes:
+    - data:
+        selected: false
+        title: User Input
+        type: start
+        variables: []
+      height: 73
+      id: '1767773675796'
+      position:
+        x: 80
+        y: 282
+      positionAbsolute:
+        x: 80
+        y: 282
+      sourcePosition: right
+      targetPosition: left
+      type: custom
+      width: 242
+    - data:
+        context:
+          enabled: false
+          variable_selector: []
+        memory:
+          query_prompt_template: ''
+          role_prefix:
+            assistant: ''
+            user: ''
+          window:
+            enabled: true
+            size: 10
+        model:
+          completion_params:
+            temperature: 0.7
+          mode: chat
+          name: qwen-max
+          provider: langgenius/tongyi/tongyi
+        prompt_template:
+        - id: 11d06d15-914a-4915-a5b1-0e35ab4fba51
+          role: system
+          text: '你是一个智能搜索助手。用户会告诉你他们想搜索的内容。
+
+            请与用户进行对话，了解他们的搜索需求。
+
+            当用户明确表达了想要搜索的内容后，你可以回复"好的，我来帮你搜索"。
+
+            '
+        selected: false
+        title: LLM
+        type: llm
+        vision:
+          enabled: false
+      height: 88
+      id: llm
+      position:
+        x: 380
+        y: 282
+      positionAbsolute:
+        x: 380
+        y: 282
+      selected: false
+      sourcePosition: right
+      targetPosition: left
+      type: custom
+      width: 242
+    - data:
+        is_team_authorization: true
+        paramSchemas:
+        - auto_generate: null
+          default: null
+          form: llm
+          human_description:
+            en_US: used for searching
+            ja_JP: used for searching
+            pt_BR: used for searching
+            zh_Hans: 用于搜索网页内容
+          label:
+            en_US: Query string
+            ja_JP: Query string
+            pt_BR: Query string
+            zh_Hans: 查询语句
+          llm_description: key words for searching
+          max: null
+          min: null
+          name: query
+          options: []
+          placeholder: null
+          precision: null
+          required: true
+          scope: null
+          template: null
+          type: string
+        params:
+          query: ''
+        plugin_id: langgenius/google
+        plugin_unique_identifier: langgenius/google:0.0.8@3efcf55ffeef9d0f77715e0afb23534952ae0cb385c051d0637e86d71199d1a6
+        provider_icon: http://localhost:5001/console/api/workspaces/current/plugin/icon?tenant_id=7217e801-f6f5-49ec-8103-d7de97a4b98f&filename=1c5871163478957bac64c3fe33d72d003f767497d921c74b742aad27a8344a74.svg
+        provider_id: langgenius/google/google
+        provider_name: langgenius/google/google
+        provider_type: builtin
+        selected: false
+        title: GoogleSearch
+        tool_configurations: {}
+        tool_description: A tool for performing a Google SERP search and extracting
+          snippets and webpages.Input should be a search query.
+        tool_label: GoogleSearch
+        tool_name: google_search
+        tool_node_version: '2'
+        tool_parameters:
+          query:
+            type: variable
+            value:
+            - ext_1
+            - text
+        type: tool
+        virtual_nodes:
+        - data:
+            model:
+              completion_params:
+                temperature: 0.7
+              mode: chat
+              name: qwen-max
+              provider: langgenius/tongyi/tongyi
+            context:
+              enabled: false
+            prompt_template:
+            - role: user
+              text: '{{#llm.context#}}'
+            - role: user
+              text: 请从对话历史中提取用户想要搜索的关键词，只返回关键词本身，不要返回其他内容
+            title: 提取搜索关键词
+          id: ext_1
+          type: llm
+      height: 52
+      id: '1767773709491'
+      position:
+        x: 682
+        y: 282
+      positionAbsolute:
+        x: 682
+        y: 282
+      selected: false
+      sourcePosition: right
+      targetPosition: left
+      type: custom
+      width: 242
+    - data:
+        answer: '搜索结果：
+
+          {{#1767773709491.text#}}
+
+          '
+        selected: false
+        title: Answer
+        type: answer
+      height: 103
+      id: answer
+      position:
+        x: 984
+        y: 282
+      positionAbsolute:
+        x: 984
+        y: 282
+      selected: true
+      sourcePosition: right
+      targetPosition: left
+      type: custom
+      width: 242
+    viewport:
+      x: 151
+      y: 141.5
+      zoom: 1
+  rag_pipeline_variables: []

api/tests/unit_tests/core/workflow/entities/test_virtual_node.py

@@ -0,0 +1,77 @@
+"""
+Unit tests for virtual node configuration.
+"""
+
+from core.workflow.nodes.base.entities import VirtualNodeConfig
+
+
+class TestVirtualNodeConfig:
+    """Tests for VirtualNodeConfig entity."""
+
+    def test_create_basic_config(self):
+        """Test creating a basic virtual node config."""
+        config = VirtualNodeConfig(
+            id="ext_1",
+            type="llm",
+            data={
+                "title": "Extract keywords",
+                "model": {"provider": "openai", "name": "gpt-4o-mini"},
+            },
+        )
+
+        assert config.id == "ext_1"
+        assert config.type == "llm"
+        assert config.data["title"] == "Extract keywords"
+
+    def test_get_global_id(self):
+        """Test generating global ID from parent ID."""
+        config = VirtualNodeConfig(
+            id="ext_1",
+            type="llm",
+            data={},
+        )
+
+        global_id = config.get_global_id("tool1")
+        assert global_id == "tool1.ext_1"
+
+    def test_get_global_id_with_different_parents(self):
+        """Test global ID generation with different parent IDs."""
+        config = VirtualNodeConfig(id="sub_node", type="code", data={})
+
+        assert config.get_global_id("parent1") == "parent1.sub_node"
+        assert config.get_global_id("node_123") == "node_123.sub_node"
+
+    def test_empty_data(self):
+        """Test virtual node config with empty data."""
+        config = VirtualNodeConfig(
+            id="test",
+            type="tool",
+        )
+
+        assert config.id == "test"
+        assert config.type == "tool"
+        assert config.data == {}
+
+    def test_complex_data(self):
+        """Test virtual node config with complex data."""
+        config = VirtualNodeConfig(
+            id="llm_1",
+            type="llm",
+            data={
+                "title": "Generate summary",
+                "model": {
+                    "provider": "openai",
+                    "name": "gpt-4",
+                    "mode": "chat",
+                    "completion_params": {"temperature": 0.7, "max_tokens": 500},
+                },
+                "prompt_template": [
+                    {"role": "user", "text": "{{#llm1.context#}}"},
+                    {"role": "user", "text": "Please summarize the conversation"},
+                ],
+            },
+        )
+
+        assert config.data["model"]["provider"] == "openai"
+        assert len(config.data["prompt_template"]) == 2
+

web/app/components/workflow/hooks/use-workflow-run-event/use-workflow-node-finished.ts

@@ -37,7 +37,10 @@ export const useWorkflowNodeFinished = () => {
     }))
 
     const newNodes = produce(nodes, (draft) => {
-      const currentNode = draft.find(node => node.id === data.node_id)!
+      const currentNode = draft.find(node => node.id === data.node_id)
+      // Skip if node not found (e.g., virtual extraction nodes)
+      if (!currentNode)
+        return
       currentNode.data._runningStatus = data.status
       if (data.status === NodeRunningStatus.Exception) {
         if (data.execution_metadata?.error_strategy === ErrorHandleTypeEnum.failBranch)

web/app/components/workflow/hooks/use-workflow-run-event/use-workflow-node-started.ts

@@ -45,6 +45,11 @@ export const useWorkflowNodeStarted = () => {
     } = reactflow
     const currentNodeIndex = nodes.findIndex(node => node.id === data.node_id)
     const currentNode = nodes[currentNodeIndex]
+
+    // Skip if node not found (e.g., virtual extraction nodes)
+    if (!currentNode)
+      return
+
     const position = currentNode.position
     const zoom = transform[2]