fix: iteration and loop node single step run

api/core/app/apps/advanced_chat/app_runner.py

@@ -89,6 +89,7 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
                 user_inputs=dict(self.application_generate_entity.single_iteration_run.inputs),
                 graph_runtime_state=graph_runtime_state,
             )
+            graph_runtime_state.variable_pool = variable_pool
         elif self.application_generate_entity.single_loop_run:
             # if only single loop run is requested
             graph_runtime_state = GraphRuntimeState(
@@ -101,6 +102,7 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
                 user_inputs=dict(self.application_generate_entity.single_loop_run.inputs),
                 graph_runtime_state=graph_runtime_state,
             )
+            graph_runtime_state.variable_pool = variable_pool
         else:
             inputs = self.application_generate_entity.inputs
             query = self.application_generate_entity.query

api/core/app/apps/workflow_app_runner.py

@@ -149,7 +149,9 @@ class WorkflowBasedAppRunner:
         node_configs = [
             node
             for node in graph_config.get("nodes", [])
-            if node.get("id") == node_id or node.get("data", {}).get("iteration_id", "") == node_id
+            if node.get("id") == node_id
+            or node.get("data", {}).get("iteration_id", "") == node_id
+            or node.get("id") == f"{node_id}start"
         ]
 
         graph_config["nodes"] = node_configs
@@ -264,7 +266,9 @@ class WorkflowBasedAppRunner:
         node_configs = [
             node
             for node in graph_config.get("nodes", [])
-            if node.get("id") == node_id or node.get("data", {}).get("loop_id", "") == node_id
+            if node.get("id") == node_id
+            or node.get("data", {}).get("loop_id", "") == node_id
+            or node.get("id") == f"{node_id}start"
         ]
 
         graph_config["nodes"] = node_configs

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

@@ -208,43 +208,16 @@ class IterationNode(Node):
         variable_mapping: dict[str, Sequence[str]] = {
             f"{node_id}.input_selector": typed_node_data.iterator_selector,
         }
+        iteration_node_ids = set()
 
-        # init graph
-        from core.workflow.entities import GraphInitParams, GraphRuntimeState
-        from core.workflow.graph import Graph
-        from core.workflow.nodes.node_factory import DifyNodeFactory
-
-        # Create minimal GraphInitParams for static analysis
-        graph_init_params = GraphInitParams(
-            tenant_id="",
-            app_id="",
-            workflow_id="",
-            graph_config=graph_config,
-            user_id="",
-            user_from="",
-            invoke_from="",
-            call_depth=0,
-        )
-
-        # Create minimal GraphRuntimeState for static analysis
-        from core.workflow.entities import VariablePool
-
-        graph_runtime_state = GraphRuntimeState(
-            variable_pool=VariablePool(),
-            start_at=0,
-        )
-
-        # Create node factory for static analysis
-        node_factory = DifyNodeFactory(graph_init_params=graph_init_params, graph_runtime_state=graph_runtime_state)
-
-        iteration_graph = Graph.init(
-            graph_config=graph_config,
-            node_factory=node_factory,
-            root_node_id=typed_node_data.start_node_id,
-        )
-
-        if not iteration_graph:
-            raise IterationGraphNotFoundError("iteration graph not found")
+        # Find all nodes that belong to this loop
+        nodes = graph_config.get("nodes", [])
+        for node in nodes:
+            node_data = node.get("data", {})
+            if node_data.get("iteration_id") == node_id:
+                in_iteration_node_id = node.get("id")
+                if in_iteration_node_id:
+                    iteration_node_ids.add(in_iteration_node_id)
 
         # Get node configs from graph_config instead of non-existent node_id_config_mapping
         node_configs = {node["id"]: node for node in graph_config.get("nodes", []) if "id" in node}
@@ -280,9 +253,7 @@ class IterationNode(Node):
             variable_mapping.update(sub_node_variable_mapping)
 
         # remove variable out from iteration
-        variable_mapping = {
-            key: value for key, value in variable_mapping.items() if value[0] not in iteration_graph.node_ids
-        }
+        variable_mapping = {key: value for key, value in variable_mapping.items() if value[0] not in iteration_node_ids}
 
         return variable_mapping
 

api/core/workflow/nodes/loop/loop_node.py

@@ -1,3 +1,4 @@
+import contextlib
 import json
 import logging
 from collections.abc import Callable, Generator, Mapping, Sequence
@@ -126,11 +127,13 @@ class LoopNode(Node):
         try:
             reach_break_condition = False
             if break_conditions:
-                _, _, reach_break_condition = condition_processor.process_conditions(
-                    variable_pool=self.graph_runtime_state.variable_pool,
-                    conditions=break_conditions,
-                    operator=logical_operator,
-                )
+                with contextlib.suppress(ValueError):
+                    _, _, reach_break_condition = condition_processor.process_conditions(
+                        variable_pool=self.graph_runtime_state.variable_pool,
+                        conditions=break_conditions,
+                        operator=logical_operator,
+                    )
+
             if reach_break_condition:
                 loop_count = 0
             cost_tokens = 0
@@ -294,42 +297,11 @@ class LoopNode(Node):
 
         variable_mapping = {}
 
-        # init graph
-        from core.workflow.entities import GraphInitParams, GraphRuntimeState, VariablePool
-        from core.workflow.graph import Graph
-        from core.workflow.nodes.node_factory import DifyNodeFactory
+        # Extract loop node IDs statically from graph_config
 
-        # Create minimal GraphInitParams for static analysis
-        graph_init_params = GraphInitParams(
-            tenant_id="",
-            app_id="",
-            workflow_id="",
-            graph_config=graph_config,
-            user_id="",
-            user_from="",
-            invoke_from="",
-            call_depth=0,
-        )
+        loop_node_ids = cls._extract_loop_node_ids_from_config(graph_config, node_id)
 
-        # Create minimal GraphRuntimeState for static analysis
-        graph_runtime_state = GraphRuntimeState(
-            variable_pool=VariablePool(),
-            start_at=0,
-        )
-
-        # Create node factory for static analysis
-        node_factory = DifyNodeFactory(graph_init_params=graph_init_params, graph_runtime_state=graph_runtime_state)
-
-        loop_graph = Graph.init(
-            graph_config=graph_config,
-            node_factory=node_factory,
-            root_node_id=typed_node_data.start_node_id,
-        )
-
-        if not loop_graph:
-            raise ValueError("loop graph not found")
-
-        # Get node configs from graph_config instead of non-existent node_id_config_mapping
+        # Get node configs from graph_config
         node_configs = {node["id"]: node for node in graph_config.get("nodes", []) if "id" in node}
         for sub_node_id, sub_node_config in node_configs.items():
             if sub_node_config.get("data", {}).get("loop_id") != node_id:
@@ -370,12 +342,35 @@ class LoopNode(Node):
                 variable_mapping[f"{node_id}.{loop_variable.label}"] = selector
 
         # remove variable out from loop
-        variable_mapping = {
-            key: value for key, value in variable_mapping.items() if value[0] not in loop_graph.node_ids
-        }
+        variable_mapping = {key: value for key, value in variable_mapping.items() if value[0] not in loop_node_ids}
 
         return variable_mapping
 
+    @classmethod
+    def _extract_loop_node_ids_from_config(cls, graph_config: Mapping[str, Any], loop_node_id: str) -> set[str]:
+        """
+        Extract node IDs that belong to a specific loop from graph configuration.
+
+        This method statically analyzes the graph configuration to find all nodes
+        that are part of the specified loop, without creating actual node instances.
+
+        :param graph_config: the complete graph configuration
+        :param loop_node_id: the ID of the loop node
+        :return: set of node IDs that belong to the loop
+        """
+        loop_node_ids = set()
+
+        # Find all nodes that belong to this loop
+        nodes = graph_config.get("nodes", [])
+        for node in nodes:
+            node_data = node.get("data", {})
+            if node_data.get("loop_id") == loop_node_id:
+                node_id = node.get("id")
+                if node_id:
+                    loop_node_ids.add(node_id)
+
+        return loop_node_ids
+
     @staticmethod
     def _get_segment_for_constant(var_type: SegmentType, original_value: Any) -> Segment:
         """Get the appropriate segment type for a constant value."""