Feat/loop node (#17273)

api/core/workflow/entities/node_entities.py

@@ -30,6 +30,7 @@ class NodeRunMetadataKey(StrEnum):
     ITERATION_DURATION_MAP = "iteration_duration_map"  # single iteration duration if iteration node runs
     LOOP_DURATION_MAP = "loop_duration_map"  # single loop duration if loop node runs
     ERROR_STRATEGY = "error_strategy"  # node in continue on error mode return the field
+    LOOP_VARIABLE_MAP = "loop_variable_map"  # single loop variable output
 
 
 class NodeRunResult(BaseModel):

api/core/workflow/nodes/enums.py

@@ -17,6 +17,7 @@ class NodeType(StrEnum):
     LEGACY_VARIABLE_AGGREGATOR = "variable-assigner"  # TODO: Merge this into VARIABLE_AGGREGATOR in the database.
     LOOP = "loop"
     LOOP_START = "loop-start"
+    LOOP_END = "loop-end"
     ITERATION = "iteration"
     ITERATION_START = "iteration-start"  # Fake start node for iteration.
     PARAMETER_EXTRACTOR = "parameter-extractor"

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

@@ -1,5 +1,6 @@
 from .entities import LoopNodeData
+from .loop_end_node import LoopEndNode
 from .loop_node import LoopNode
 from .loop_start_node import LoopStartNode
 
-__all__ = ["LoopNode", "LoopNodeData", "LoopStartNode"]
+__all__ = ["LoopEndNode", "LoopNode", "LoopNodeData", "LoopStartNode"]

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

@@ -1,11 +1,23 @@
+from collections.abc import Mapping
 from typing import Any, Literal, Optional
 
-from pydantic import Field
+from pydantic import BaseModel, Field
 
 from core.workflow.nodes.base import BaseLoopNodeData, BaseLoopState, BaseNodeData
 from core.workflow.utils.condition.entities import Condition
 
 
+class LoopVariableData(BaseModel):
+    """
+    Loop Variable Data.
+    """
+
+    label: str
+    var_type: Literal["string", "number", "object", "array[string]", "array[number]", "array[object]"]
+    value_type: Literal["variable", "constant"]
+    value: Optional[Any | list[str]] = None
+
+
 class LoopNodeData(BaseLoopNodeData):
     """
     Loop Node Data.
@@ -14,6 +26,8 @@ class LoopNodeData(BaseLoopNodeData):
     loop_count: int  # Maximum number of loops
     break_conditions: list[Condition]  # Conditions to break the loop
     logical_operator: Literal["and", "or"]
+    loop_variables: Optional[list[LoopVariableData]] = Field(default_factory=list)
+    outputs: Optional[Mapping[str, Any]] = None
 
 
 class LoopStartNodeData(BaseNodeData):
@@ -24,6 +38,14 @@ class LoopStartNodeData(BaseNodeData):
     pass
 
 
+class LoopEndNodeData(BaseNodeData):
+    """
+    Loop End Node Data.
+    """
+
+    pass
+
+
 class LoopState(BaseLoopState):
     """
     Loop State.

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

@@ -0,0 +1,20 @@
+from core.workflow.entities.node_entities import NodeRunResult
+from core.workflow.nodes.base import BaseNode
+from core.workflow.nodes.enums import NodeType
+from core.workflow.nodes.loop.entities import LoopEndNodeData
+from models.workflow import WorkflowNodeExecutionStatus
+
+
+class LoopEndNode(BaseNode[LoopEndNodeData]):
+    """
+    Loop End Node.
+    """
+
+    _node_data_cls = LoopEndNodeData
+    _node_type = NodeType.LOOP_END
+
+    def _run(self) -> NodeRunResult:
+        """
+        Run the node.
+        """
+        return NodeRunResult(status=WorkflowNodeExecutionStatus.SUCCEEDED)

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

@@ -1,10 +1,20 @@
+import json
 import logging
 from collections.abc import Generator, Mapping, Sequence
 from datetime import UTC, datetime
-from typing import Any, cast
+from typing import TYPE_CHECKING, Any, Literal, cast
 
 from configs import dify_config
-from core.variables import IntegerSegment
+from core.variables import (
+    ArrayNumberSegment,
+    ArrayObjectSegment,
+    ArrayStringSegment,
+    IntegerSegment,
+    ObjectSegment,
+    Segment,
+    SegmentType,
+    StringSegment,
+)
 from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult
 from core.workflow.graph_engine.entities.event import (
     BaseGraphEvent,
@@ -29,6 +39,10 @@ from core.workflow.nodes.loop.entities import LoopNodeData
 from core.workflow.utils.condition.processor import ConditionProcessor
 from models.workflow import WorkflowNodeExecutionStatus
 
+if TYPE_CHECKING:
+    from core.workflow.entities.variable_pool import VariablePool
+    from core.workflow.graph_engine.graph_engine import GraphEngine
+
 logger = logging.getLogger(__name__)
 
 
@@ -61,6 +75,28 @@ class LoopNode(BaseNode[LoopNodeData]):
         variable_pool = self.graph_runtime_state.variable_pool
         variable_pool.add([self.node_id, "index"], 0)
 
+        # Initialize loop variables
+        loop_variable_selectors = {}
+        if self.node_data.loop_variables:
+            for loop_variable in self.node_data.loop_variables:
+                value_processor = {
+                    "constant": lambda var=loop_variable: self._get_segment_for_constant(var.var_type, var.value),
+                    "variable": lambda var=loop_variable: variable_pool.get(var.value),
+                }
+
+                if loop_variable.value_type not in value_processor:
+                    raise ValueError(
+                        f"Invalid value type '{loop_variable.value_type}' for loop variable {loop_variable.label}"
+                    )
+
+                processed_segment = value_processor[loop_variable.value_type]()
+                if not processed_segment:
+                    raise ValueError(f"Invalid value for loop variable {loop_variable.label}")
+                variable_selector = [self.node_id, loop_variable.label]
+                variable_pool.add(variable_selector, processed_segment.value)
+                loop_variable_selectors[loop_variable.label] = variable_selector
+                inputs[loop_variable.label] = processed_segment.value
+
         from core.workflow.graph_engine.graph_engine import GraphEngine
 
         graph_engine = GraphEngine(
@@ -95,135 +131,51 @@ class LoopNode(BaseNode[LoopNodeData]):
             predecessor_node_id=self.previous_node_id,
         )
 
-        yield LoopRunNextEvent(
-            loop_id=self.id,
-            loop_node_id=self.node_id,
-            loop_node_type=self.node_type,
-            loop_node_data=self.node_data,
-            index=0,
-            pre_loop_output=None,
-        )
-
+        # yield LoopRunNextEvent(
+        #     loop_id=self.id,
+        #     loop_node_id=self.node_id,
+        #     loop_node_type=self.node_type,
+        #     loop_node_data=self.node_data,
+        #     index=0,
+        #     pre_loop_output=None,
+        # )
+        loop_duration_map = {}
+        single_loop_variable_map = {}  # single loop variable output
         try:
             check_break_result = False
             for i in range(loop_count):
-                # Run workflow
-                rst = graph_engine.run()
-                current_index_variable = variable_pool.get([self.node_id, "index"])
-                if not isinstance(current_index_variable, IntegerSegment):
-                    raise ValueError(f"loop {self.node_id} current index not found")
-                current_index = current_index_variable.value
-
-                check_break_result = False
-
-                for event in rst:
-                    if isinstance(event, (BaseNodeEvent | BaseParallelBranchEvent)) and not event.in_loop_id:
-                        event.in_loop_id = self.node_id
-
-                    if (
-                        isinstance(event, BaseNodeEvent)
-                        and event.node_type == NodeType.LOOP_START
-                        and not isinstance(event, NodeRunStreamChunkEvent)
-                    ):
-                        continue
-
-                    if isinstance(event, NodeRunSucceededEvent):
-                        yield self._handle_event_metadata(event=event, iter_run_index=current_index)
-
-                        # Check if all variables in break conditions exist
-                        exists_variable = False
-                        for condition in break_conditions:
-                            if not self.graph_runtime_state.variable_pool.get(condition.variable_selector):
-                                exists_variable = False
-                                break
-                            else:
-                                exists_variable = True
-                        if exists_variable:
-                            input_conditions, group_result, check_break_result = condition_processor.process_conditions(
-                                variable_pool=self.graph_runtime_state.variable_pool,
-                                conditions=break_conditions,
-                                operator=logical_operator,
-                            )
-                            if check_break_result:
-                                break
-
-                    elif isinstance(event, BaseGraphEvent):
-                        if isinstance(event, GraphRunFailedEvent):
-                            # Loop run failed
-                            yield LoopRunFailedEvent(
-                                loop_id=self.id,
-                                loop_node_id=self.node_id,
-                                loop_node_type=self.node_type,
-                                loop_node_data=self.node_data,
-                                start_at=start_at,
-                                inputs=inputs,
-                                steps=i,
-                                metadata={
-                                    NodeRunMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens,
-                                    "completed_reason": "error",
-                                },
-                                error=event.error,
-                            )
-                            yield RunCompletedEvent(
-                                run_result=NodeRunResult(
-                                    status=WorkflowNodeExecutionStatus.FAILED,
-                                    error=event.error,
-                                    metadata={
-                                        NodeRunMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens
-                                    },
-                                )
-                            )
-                            return
-                    elif isinstance(event, NodeRunFailedEvent):
-                        # Loop run failed
-                        yield event
-                        yield LoopRunFailedEvent(
-                            loop_id=self.id,
-                            loop_node_id=self.node_id,
-                            loop_node_type=self.node_type,
-                            loop_node_data=self.node_data,
-                            start_at=start_at,
-                            inputs=inputs,
-                            steps=i,
-                            metadata={
-                                NodeRunMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens,
-                                "completed_reason": "error",
-                            },
-                            error=event.error,
-                        )
-                        yield RunCompletedEvent(
-                            run_result=NodeRunResult(
-                                status=WorkflowNodeExecutionStatus.FAILED,
-                                error=event.error,
-                                metadata={
-                                    NodeRunMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens
-                                },
-                            )
-                        )
-                        return
+                loop_start_time = datetime.now(UTC).replace(tzinfo=None)
+                # run single loop
+                loop_result = yield from self._run_single_loop(
+                    graph_engine=graph_engine,
+                    loop_graph=loop_graph,
+                    variable_pool=variable_pool,
+                    loop_variable_selectors=loop_variable_selectors,
+                    break_conditions=break_conditions,
+                    logical_operator=logical_operator,
+                    condition_processor=condition_processor,
+                    current_index=i,
+                    start_at=start_at,
+                    inputs=inputs,
+                )
+                loop_end_time = datetime.now(UTC).replace(tzinfo=None)
+
+                single_loop_variable = {}
+                for key, selector in loop_variable_selectors.items():
+                    item = variable_pool.get(selector)
+                    if item:
+                        single_loop_variable[key] = item.value
                     else:
-                        yield self._handle_event_metadata(event=cast(InNodeEvent, event), iter_run_index=current_index)
+                        single_loop_variable[key] = None
 
-                # Remove all nodes outputs from variable pool
-                for node_id in loop_graph.node_ids:
-                    variable_pool.remove([node_id])
+                loop_duration_map[str(i)] = (loop_end_time - loop_start_time).total_seconds()
+                single_loop_variable_map[str(i)] = single_loop_variable
+
+                check_break_result = loop_result.get("check_break_result", False)
 
                 if check_break_result:
                     break
 
-                # Move to next loop
-                next_index = current_index + 1
-                variable_pool.add([self.node_id, "index"], next_index)
-
-                yield LoopRunNextEvent(
-                    loop_id=self.id,
-                    loop_node_id=self.node_id,
-                    loop_node_type=self.node_type,
-                    loop_node_data=self.node_data,
-                    index=next_index,
-                    pre_loop_output=None,
-                )
-
             # Loop completed successfully
             yield LoopRunSucceededEvent(
                 loop_id=self.id,
@@ -232,17 +184,26 @@ class LoopNode(BaseNode[LoopNodeData]):
                 loop_node_data=self.node_data,
                 start_at=start_at,
                 inputs=inputs,
+                outputs=self.node_data.outputs,
                 steps=loop_count,
                 metadata={
                     NodeRunMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens,
                     "completed_reason": "loop_break" if check_break_result else "loop_completed",
+                    NodeRunMetadataKey.LOOP_DURATION_MAP: loop_duration_map,
+                    NodeRunMetadataKey.LOOP_VARIABLE_MAP: single_loop_variable_map,
                 },
             )
 
             yield RunCompletedEvent(
                 run_result=NodeRunResult(
                     status=WorkflowNodeExecutionStatus.SUCCEEDED,
-                    metadata={NodeRunMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens},
+                    metadata={
+                        NodeRunMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens,
+                        NodeRunMetadataKey.LOOP_DURATION_MAP: loop_duration_map,
+                        NodeRunMetadataKey.LOOP_VARIABLE_MAP: single_loop_variable_map,
+                    },
+                    outputs=self.node_data.outputs,
+                    inputs=inputs,
                 )
             )
 
@@ -260,6 +221,8 @@ class LoopNode(BaseNode[LoopNodeData]):
                 metadata={
                     "total_tokens": graph_engine.graph_runtime_state.total_tokens,
                     "completed_reason": "error",
+                    NodeRunMetadataKey.LOOP_DURATION_MAP: loop_duration_map,
+                    NodeRunMetadataKey.LOOP_VARIABLE_MAP: single_loop_variable_map,
                 },
                 error=str(e),
             )
@@ -268,7 +231,11 @@ class LoopNode(BaseNode[LoopNodeData]):
                 run_result=NodeRunResult(
                     status=WorkflowNodeExecutionStatus.FAILED,
                     error=str(e),
-                    metadata={NodeRunMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens},
+                    metadata={
+                        NodeRunMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens,
+                        NodeRunMetadataKey.LOOP_DURATION_MAP: loop_duration_map,
+                        NodeRunMetadataKey.LOOP_VARIABLE_MAP: single_loop_variable_map,
+                    },
                 )
             )
 
@@ -276,6 +243,159 @@ class LoopNode(BaseNode[LoopNodeData]):
             # Clean up
             variable_pool.remove([self.node_id, "index"])
 
+    def _run_single_loop(
+        self,
+        *,
+        graph_engine: "GraphEngine",
+        loop_graph: Graph,
+        variable_pool: "VariablePool",
+        loop_variable_selectors: dict,
+        break_conditions: list,
+        logical_operator: Literal["and", "or"],
+        condition_processor: ConditionProcessor,
+        current_index: int,
+        start_at: datetime,
+        inputs: dict,
+    ) -> Generator[NodeEvent | InNodeEvent, None, dict]:
+        """Run a single loop iteration.
+        Returns:
+            dict:  {'check_break_result': bool}
+        """
+        # Run workflow
+        rst = graph_engine.run()
+        current_index_variable = variable_pool.get([self.node_id, "index"])
+        if not isinstance(current_index_variable, IntegerSegment):
+            raise ValueError(f"loop {self.node_id} current index not found")
+        current_index = current_index_variable.value
+
+        check_break_result = False
+
+        for event in rst:
+            if isinstance(event, (BaseNodeEvent | BaseParallelBranchEvent)) and not event.in_loop_id:
+                event.in_loop_id = self.node_id
+
+            if (
+                isinstance(event, BaseNodeEvent)
+                and event.node_type == NodeType.LOOP_START
+                and not isinstance(event, NodeRunStreamChunkEvent)
+            ):
+                continue
+
+            if (
+                isinstance(event, NodeRunSucceededEvent)
+                and event.node_type == NodeType.LOOP_END
+                and not isinstance(event, NodeRunStreamChunkEvent)
+            ):
+                check_break_result = True
+                yield self._handle_event_metadata(event=event, iter_run_index=current_index)
+                break
+
+            if isinstance(event, NodeRunSucceededEvent):
+                yield self._handle_event_metadata(event=event, iter_run_index=current_index)
+
+                # Check if all variables in break conditions exist
+                exists_variable = False
+                for condition in break_conditions:
+                    if not self.graph_runtime_state.variable_pool.get(condition.variable_selector):
+                        exists_variable = False
+                        break
+                    else:
+                        exists_variable = True
+                if exists_variable:
+                    input_conditions, group_result, check_break_result = condition_processor.process_conditions(
+                        variable_pool=self.graph_runtime_state.variable_pool,
+                        conditions=break_conditions,
+                        operator=logical_operator,
+                    )
+                    if check_break_result:
+                        break
+
+            elif isinstance(event, BaseGraphEvent):
+                if isinstance(event, GraphRunFailedEvent):
+                    # Loop run failed
+                    yield LoopRunFailedEvent(
+                        loop_id=self.id,
+                        loop_node_id=self.node_id,
+                        loop_node_type=self.node_type,
+                        loop_node_data=self.node_data,
+                        start_at=start_at,
+                        inputs=inputs,
+                        steps=current_index,
+                        metadata={
+                            NodeRunMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens,
+                            "completed_reason": "error",
+                        },
+                        error=event.error,
+                    )
+                    yield RunCompletedEvent(
+                        run_result=NodeRunResult(
+                            status=WorkflowNodeExecutionStatus.FAILED,
+                            error=event.error,
+                            metadata={NodeRunMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens},
+                        )
+                    )
+                    return {"check_break_result": True}
+            elif isinstance(event, NodeRunFailedEvent):
+                # Loop run failed
+                yield event
+                yield LoopRunFailedEvent(
+                    loop_id=self.id,
+                    loop_node_id=self.node_id,
+                    loop_node_type=self.node_type,
+                    loop_node_data=self.node_data,
+                    start_at=start_at,
+                    inputs=inputs,
+                    steps=current_index,
+                    metadata={
+                        NodeRunMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens,
+                        "completed_reason": "error",
+                    },
+                    error=event.error,
+                )
+                yield RunCompletedEvent(
+                    run_result=NodeRunResult(
+                        status=WorkflowNodeExecutionStatus.FAILED,
+                        error=event.error,
+                        metadata={NodeRunMetadataKey.TOTAL_TOKENS: graph_engine.graph_runtime_state.total_tokens},
+                    )
+                )
+                return {"check_break_result": True}
+            else:
+                yield self._handle_event_metadata(event=cast(InNodeEvent, event), iter_run_index=current_index)
+
+        # Remove all nodes outputs from variable pool
+        for node_id in loop_graph.node_ids:
+            variable_pool.remove([node_id])
+
+        _outputs = {}
+        for loop_variable_key, loop_variable_selector in loop_variable_selectors.items():
+            _loop_variable_segment = variable_pool.get(loop_variable_selector)
+            if _loop_variable_segment:
+                _outputs[loop_variable_key] = _loop_variable_segment.value
+            else:
+                _outputs[loop_variable_key] = None
+
+        _outputs["loop_round"] = current_index + 1
+        self.node_data.outputs = _outputs
+
+        if check_break_result:
+            return {"check_break_result": True}
+
+        # Move to next loop
+        next_index = current_index + 1
+        variable_pool.add([self.node_id, "index"], next_index)
+
+        yield LoopRunNextEvent(
+            loop_id=self.id,
+            loop_node_id=self.node_id,
+            loop_node_type=self.node_type,
+            loop_node_data=self.node_data,
+            index=next_index,
+            pre_loop_output=self.node_data.outputs,
+        )
+
+        return {"check_break_result": False}
+
     def _handle_event_metadata(
         self,
         *,
@@ -360,3 +480,25 @@ class LoopNode(BaseNode[LoopNodeData]):
         }
 
         return variable_mapping
+
+    @staticmethod
+    def _get_segment_for_constant(var_type: str, value: Any) -> Segment:
+        """Get the appropriate segment type for a constant value."""
+        segment_mapping: dict[str, tuple[type[Segment], SegmentType]] = {
+            "string": (StringSegment, SegmentType.STRING),
+            "number": (IntegerSegment, SegmentType.NUMBER),
+            "object": (ObjectSegment, SegmentType.OBJECT),
+            "array[string]": (ArrayStringSegment, SegmentType.ARRAY_STRING),
+            "array[number]": (ArrayNumberSegment, SegmentType.ARRAY_NUMBER),
+            "array[object]": (ArrayObjectSegment, SegmentType.ARRAY_OBJECT),
+        }
+        if var_type in ["array[string]", "array[number]", "array[object]"]:
+            if value:
+                value = json.loads(value)
+            else:
+                value = []
+        segment_info = segment_mapping.get(var_type)
+        if not segment_info:
+            raise ValueError(f"Invalid variable type: {var_type}")
+        segment_class, value_type = segment_info
+        return segment_class(value=value, value_type=value_type)

api/core/workflow/nodes/node_mapping.py

@@ -13,7 +13,7 @@ from core.workflow.nodes.iteration import IterationNode, IterationStartNode
 from core.workflow.nodes.knowledge_retrieval import KnowledgeRetrievalNode
 from core.workflow.nodes.list_operator import ListOperatorNode
 from core.workflow.nodes.llm import LLMNode
-from core.workflow.nodes.loop import LoopNode, LoopStartNode
+from core.workflow.nodes.loop import LoopEndNode, LoopNode, LoopStartNode
 from core.workflow.nodes.parameter_extractor import ParameterExtractorNode
 from core.workflow.nodes.question_classifier import QuestionClassifierNode
 from core.workflow.nodes.start import StartNode
@@ -94,6 +94,10 @@ NODE_TYPE_CLASSES_MAPPING: Mapping[NodeType, Mapping[str, type[BaseNode]]] = {
         LATEST_VERSION: LoopStartNode,
         "1": LoopStartNode,
     },
+    NodeType.LOOP_END: {
+        LATEST_VERSION: LoopEndNode,
+        "1": LoopEndNode,
+    },
     NodeType.PARAMETER_EXTRACTOR: {
         LATEST_VERSION: ParameterExtractorNode,
         "1": ParameterExtractorNode,

api/core/workflow/nodes/variable_assigner/v2/node.py

@@ -2,6 +2,7 @@ import json
 from collections.abc import Sequence
 from typing import Any, cast
 
+from core.app.entities.app_invoke_entities import InvokeFrom
 from core.variables import SegmentType, Variable
 from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID
 from core.workflow.entities.node_entities import NodeRunResult
@@ -123,13 +124,14 @@ class VariableAssignerNode(BaseNode[VariableAssignerNodeData]):
             if variable.selector[0] == CONVERSATION_VARIABLE_NODE_ID:
                 conversation_id = self.graph_runtime_state.variable_pool.get(["sys", "conversation_id"])
                 if not conversation_id:
-                    raise ConversationIDNotFoundError
+                    if self.invoke_from != InvokeFrom.DEBUGGER:
+                        raise ConversationIDNotFoundError
                 else:
                     conversation_id = conversation_id.value
-                common_helpers.update_conversation_variable(
-                    conversation_id=cast(str, conversation_id),
-                    variable=variable,
-                )
+                    common_helpers.update_conversation_variable(
+                        conversation_id=cast(str, conversation_id),
+                        variable=variable,
+                    )
 
         return NodeRunResult(
             status=WorkflowNodeExecutionStatus.SUCCEEDED,