Merge #80 into develop from feature/20251219_myh

feat(workflow): support cycle nodes in workflow config validation and enhance node logging

* feature/20251219_myh: (11 commits squashed)

  - feat(workflow): update reranker model configuration for knowledge base retrieval

  - fix(workflow): fix output issue in parameter extraction node

  - fix(workflow): fix output issue in parameter extraction node

  - feat(workflow): add user prompt to parameter extraction node

  - perf(workflow): change grouped variable input to key-value format in variable aggregator

  - feat(workflow): Add new cycle node for iterative workflow execution
    
    - Introduce a new Loop/Iteration node in the workflow engine.
    - Supports both conditional loops and iteration over lists.
    - Allows parallel execution and flattening of iteration outputs.
    - Maintains runtime state, node outputs, and loop variables for downstream nodes.
    - Enhances workflow flexibility for complex, repeated operations.

  - Merge branch 'develop' into feature/20251219_myh
    
    # Conflicts:
    #	api/app/core/workflow/nodes/configs.py
    #	api/app/core/workflow/nodes/node_factory.py

  - feat(workflow): Add new cycle node for iterative workflow execution
    
    - Introduce a new Loop/Iteration node in the workflow engine.
    - Supports both conditional loops and iteration over lists.
    - Allows parallel execution and flattening of iteration outputs.
    - Maintains runtime state, node outputs, and loop variables for downstream nodes.
    - Enhances workflow flexibility for complex, repeated operations.

  - feat(workflow): support cycle nodes in workflow config validation and enhance node logging

  - feat(workflow): support cycle nodes in workflow config validation and enhance node logging

  - fix(workflow): fix compatibility with some legacy node configurations

Signed-off-by: Eternity <1533512157@qq.com>
Reviewed-by: zhuwenhui5566@163.com <zhuwenhui5566@163.com>
Reviewed-by: aliyun6762716068 <accounts_68cb7c6b61f5dcc4200d6251@mail.teambition.com>
Merged-by: aliyun6762716068 <accounts_68cb7c6b61f5dcc4200d6251@mail.teambition.com>

CR-link: https://codeup.aliyun.com/redbearai/python/redbear-mem-open/change/80

api/app/core/workflow/nodes/assigner/node.py

@@ -83,3 +83,5 @@ class AssignerNode(BaseNode):
                     operator.remove_last()
                 case _:
                     raise ValueError(f"Invalid Operator: {assignment.operation}")
+            logger.info(f"Node {self.node_id}: execution completed")
+

api/app/core/workflow/nodes/base_node.py

@@ -78,6 +78,7 @@ class BaseNode(ABC):
         self.workflow_config = workflow_config
         self.node_id = node_config["id"]
         self.node_type = node_config["type"]
+        self.cycle = node_config.get("cycle")
         self.node_name = node_config.get("name", self.node_id)
         # 使用 or 运算符处理 None 值
         self.config = node_config.get("config") or {}

api/app/core/workflow/nodes/breaker/node.py

@@ -29,4 +29,5 @@ class BreakNode(BaseNode):
             Optional dictionary indicating the loop has been stopped.
         """
         state["looping"] = False
-        logger.info(f"run break node, looping={state['looping']}")
+        logger.info(f"Setting cycle node exit flag, cycle={self.cycle}, looping={state['looping']}")
+

api/app/core/workflow/nodes/cycle_graph/iteration.py

@@ -1,5 +1,6 @@
 import asyncio
 import copy
+import logging
 import re
 from typing import Any
 
@@ -9,6 +10,8 @@ from app.core.workflow.nodes import WorkflowState
 from app.core.workflow.nodes.cycle_graph import IterationNodeConfig
 from app.core.workflow.variable_pool import VariablePool
 
+logger = logging.getLogger(__name__)
+
 
 class IterationRuntime:
     """
@@ -127,12 +130,15 @@ class IterationRuntime:
             # Execute iterations in parallel batches
             while idx < len(array_obj) and self.looping:
                 tasks = self._create_iteration_tasks(array_obj, idx)
+                logger.info(f"Iteration node {self.node_id}: running, concurrency {len(tasks)}")
                 idx += self.typed_config.parallel_count
                 await asyncio.gather(*tasks)
+            logger.info(f"Iteration node {self.node_id}: execution completed")
             return self.result
         else:
             # Execute iterations sequentially
             while idx < len(array_obj) and self.looping:
+                logger.info(f"Iteration node {self.node_id}: running")
                 item = array_obj[idx]
                 result = await self.graph.ainvoke(self._init_iteration_state(item, idx))
                 output = VariablePool(result).get(self.output_value)
@@ -143,4 +149,6 @@ class IterationRuntime:
                 if not result["looping"]:
                     self.looping = False
                 idx += 1
+
+            logger.info(f"Iteration node {self.node_id}: execution completed")
             return self.result

api/app/core/workflow/nodes/cycle_graph/loop.py

@@ -1,3 +1,4 @@
+import logging
 from typing import Any
 
 from langgraph.graph.state import CompiledStateGraph
@@ -8,6 +9,8 @@ from app.core.workflow.nodes.cycle_graph import LoopNodeConfig
 from app.core.workflow.nodes.operators import ConditionExpressionBuilder
 from app.core.workflow.variable_pool import VariablePool
 
+logger = logging.getLogger(__name__)
+
 
 class LoopRuntime:
     """
@@ -119,6 +122,9 @@ class LoopRuntime:
                 node_outputs=loop_variable_pool.get_all_node_outputs(),
                 system_vars=loop_variable_pool.get_all_system_vars(),
         ) and loopstate["looping"] and loop_time > 0:
+            logger.info(f"loop node {self.node_id}: running")
             await self.graph.ainvoke(loopstate)
             loop_time -= 1
+
+        logger.info(f"loop node {self.node_id}: execution completed")
         return loopstate["runtime_vars"][self.node_id]

api/app/core/workflow/nodes/cycle_graph/node.py

@@ -65,7 +65,10 @@ class CycleGraphNode(BaseNode):
 
             # Raise error if cycle nodes are connected with external nodes
             if source_in ^ target_in:
-                raise ValueError(f"循环节点与外部节点存在连接,soruce: {edge.get("source")}, target:{edge.get("target")}")
+                raise ValueError(
+                    f"Cycle node is connected to external node, "
+                    f"source: {edge.get('source')}, target: {edge.get('target')}"
+                )
 
             if source_in and target_in:
                 cycle_edges.append(edge)
@@ -220,4 +223,4 @@ class CycleGraphNode(BaseNode):
                 config=self.config,
                 state=state,
             ).run()
-        raise RuntimeError("未知循环节点类型")
+        raise RuntimeError("Unknown cycle node type")

api/app/core/workflow/nodes/http_request/node.py

@@ -215,6 +215,7 @@ class HttpRequestNode(BaseNode):
                         **self._build_content(state)
                     )
                     resp.raise_for_status()
+                    logger.info(f"Node {self.node_id}: HTTP request succeeded")
                     return HttpRequestNodeOutput(
                         body=resp.text,
                         status_code=resp.status_code,
@@ -228,12 +229,21 @@ class HttpRequestNode(BaseNode):
             else:
                 match self.typed_config.error_handle.method:
                     case HttpErrorHandle.NONE:
+                        logger.warning(
+                            f"Node {self.node_id}: HTTP request failed, returning error response"
+                        )
                         return HttpRequestNodeOutput(
                             body="",
                             status_code=resp.status_code,
                             headers=resp.headers,
                         ).model_dump()
                     case HttpErrorHandle.DEFAULT:
+                        logger.warning(
+                            f"Node {self.node_id}: HTTP request failed, returning default result"
+                        )
                         return self.typed_config.error_handle.default.model_dump()
                     case HttpErrorHandle.BRANCH:
+                        logger.warning(
+                            f"Node {self.node_id}: HTTP request failed, switching to error handling branch"
+                        )
                         return "ERROR"

api/app/core/workflow/nodes/if_else/node.py

@@ -94,5 +94,6 @@ class IfElseNode(BaseNode):
         for i in range(len(expressions)):
             logger.info(expressions[i])
             if self._evaluate_condition(expressions[i], state):
+                logger.info(f"Node {self.node_id}: switched to branch CASE {i + 1}")
                 return f'CASE{i + 1}'
         return f'CASE{len(expressions)}'

api/app/core/workflow/nodes/jinja_render/node.py

@@ -1,3 +1,4 @@
+import logging
 from typing import Any
 
 from app.core.workflow.nodes import WorkflowState
@@ -5,6 +6,7 @@ from app.core.workflow.nodes.base_node import BaseNode
 from app.core.workflow.nodes.jinja_render.config import JinjaRenderNodeConfig
 from app.core.workflow.template_renderer import TemplateRenderer
 
+logger = logging.getLogger(__name__)
 
 class JinjaRenderNode(BaseNode):
     def __init__(self, node_config: dict[str, Any], workflow_config: dict[str, Any]):
@@ -41,5 +43,5 @@ class JinjaRenderNode(BaseNode):
             res = render.env.from_string(self.typed_config.template).render(**context)
         except Exception as e:
             raise RuntimeError(f"JinjaRender Node {self.node_name} render failed: {e}") from e
-
+        logger.info(f"Node {self.node_id}: Jinja template rendering completed")
         return res

api/app/core/workflow/nodes/knowledge/node.py

@@ -190,12 +190,12 @@ class KnowledgeRetrievalNode(BaseNode):
                 match kb_config.retrieve_type:
                     case RetrieveType.PARTICIPLE:
                         rs.extend(vector_service.search_by_full_text(query=query, top_k=kb_config.top_k,
-                                                                indices=indices,
+                                                                     indices=indices,
-                                                                score_threshold=kb_config.similarity_threshold))
+                                                                     score_threshold=kb_config.similarity_threshold))
                     case RetrieveType.SEMANTIC:
                         rs.extend(vector_service.search_by_vector(query=query, top_k=kb_config.top_k,
-                                                             indices=indices,
+                                                                  indices=indices,
-                                                             score_threshold=kb_config.vector_similarity_weight))
+                                                                  score_threshold=kb_config.vector_similarity_weight))
                     case RetrieveType.HYBRID:
                         rs1 = vector_service.search_by_vector(query=query, top_k=kb_config.top_k,
                                                               indices=indices,
@@ -209,5 +209,9 @@ class KnowledgeRetrievalNode(BaseNode):
                         rs.extend(vector_service.rerank(query=query, docs=unique_rs, top_k=kb_config.top_k))
                     case _:
                         raise RuntimeError("Unknown retrieval type")
-            final_rs = vector_service.rerank(query=query, docs=rs, top_k=kb_config.top_k)
+            vector_service.reranker = self.get_reranker_model()
+            final_rs = vector_service.rerank(query=query, docs=rs, top_k=self.typed_config.reranker_top_k)
+            logger.info(
+                f"Node {self.node_id}: knowledge base retrieval completed, results count: {len(final_rs)}"
+            )
             return [chunk.model_dump() for chunk in final_rs]

api/app/core/workflow/nodes/parameter_extractor/node.py

@@ -163,6 +163,6 @@ class ParameterExtractorNode(BaseNode):
 
         model_resp = await llm.ainvoke(messages)
         result = json_repair.repair_json(model_resp.content, return_objects=True)
-        logger.info(f"get prarms:{result}")
+        logger.info(f"node: {self.node_id} get params:{result}")
 
         return result

api/app/core/workflow/nodes/variable_aggregator/node.py

@@ -50,6 +50,7 @@ class VariableAggregatorNode(BaseNode):
                     continue
 
                 if value is not None:
+                    logger.info(f"Node: {self.node_id} variable aggregation result: {value}")
                     return value
 
             logger.info("No variable found in non-group mode; returning empty string.")
@@ -74,5 +75,5 @@ class VariableAggregatorNode(BaseNode):
             else:
                 result[group_name] = ""
                 logger.info(f"No variable found for group '{group_name}'; set empty string.")
-
+        logger.info(f"Node: {self.node_id} variable aggregation result: {result}")
         return result

api/app/core/workflow/validator.py

@@ -7,14 +7,87 @@
 import logging
 from typing import Any, Union
 
+from app.core.workflow.nodes.enums import NodeType
+
 logger = logging.getLogger(__name__)
 
 
 class WorkflowValidator:
     """工作流配置验证器"""
 
-    @staticmethod
+    @classmethod
-    def validate(workflow_config: Union[dict[str, Any], Any]) -> tuple[bool, list[str]]:
+    def pure_cycle_graph(cls, workflow_config: Union[dict[str, Any], Any], node_id) -> tuple[list, list]:
+        """
+        Extract cycle nodes and internal edges from the workflow configuration,
+        removing them from the global workflow.
+
+        Raises:
+            ValueError: If cycle nodes are connected to external nodes improperly.
+
+        Returns:
+            Tuple containing:
+            - cycle_nodes: List of removed nodes
+            - cycle_edges: List of removed edges
+        """
+        nodes = workflow_config.get("nodes", [])
+        edges = workflow_config.get("edges", [])
+
+        # Select all nodes that belong to the current cycle
+        cycle_nodes = [node for node in nodes if node.get("cycle") == node_id]
+        cycle_node_ids = {node.get("id") for node in cycle_nodes}
+
+        cycle_edges = []
+        remain_edges = []
+
+        for edge in edges:
+            source_in = edge.get("source") in cycle_node_ids
+            target_in = edge.get("target") in cycle_node_ids
+
+            # Raise error if cycle nodes are connected with external nodes
+            if source_in ^ target_in:
+                raise ValueError(
+                    f"Cycle node is connected to external node, "
+                    f"source: {edge.get('source')}, target: {edge.get('target')}"
+                )
+
+            if source_in and target_in:
+                cycle_edges.append(edge)
+            else:
+                remain_edges.append(edge)
+
+        # Update workflow_config by removing cycle nodes and internal edges
+        workflow_config["nodes"] = [
+            node for node in nodes if node.get("cycle") != node_id
+        ]
+        workflow_config["edges"] = remain_edges
+
+        return cycle_nodes, cycle_edges
+
+    @classmethod
+    def get_subgraph(cls, workflow_config: Union[dict[str, Any], Any]) -> list:
+        if not isinstance(workflow_config, dict):
+            workflow_config = {
+                "nodes": workflow_config.nodes,
+                "edges": workflow_config.edges,
+                "variables": workflow_config.variables,
+            }
+        cycle_nodes = [
+            node.get("id")
+            for node in workflow_config.get("nodes", [])
+            if node.get("type") in [NodeType.LOOP, NodeType.ITERATION]
+        ]
+        graphs = []
+        for cycle_node in cycle_nodes:
+            nodes, edges = cls.pure_cycle_graph(workflow_config, cycle_node)
+            graphs.append({
+                "nodes": nodes,
+                "edges": edges,
+            })
+        graphs.append(workflow_config)
+        return graphs
+
+    @classmethod
+    def validate(cls, workflow_config: Union[dict[str, Any], Any]) -> tuple[bool, list[str]]:
         """验证工作流配置
         
         Args:
@@ -39,80 +112,75 @@ class WorkflowValidator:
         """
         errors = []
 
-        # 支持字典和 Pydantic 模型
+        graphs = cls.get_subgraph(workflow_config)
-        if isinstance(workflow_config, dict):
+        logger.info(graphs)
-            nodes = workflow_config.get("nodes", [])
+        for graph in graphs:
-            edges = workflow_config.get("edges", [])
+            nodes = graph.get("nodes", [])
-            variables = workflow_config.get("variables", [])
+            edges = graph.get("edges", [])
-        else:
+            variables = graph.get("variables", [])
-            # Pydantic 模型
+            # 1. 验证 start 节点（有且只有一个）
-            nodes = getattr(workflow_config, "nodes", [])
+            start_nodes = [n for n in nodes if n.get("type") in [NodeType.START, NodeType.CYCLE_START]]
-            edges = getattr(workflow_config, "edges", [])
+            if len(start_nodes) == 0:
-            variables = getattr(workflow_config, "variables", [])
+                errors.append("工作流必须有一个 start 节点")
+            elif len(start_nodes) > 1:
+                errors.append(f"工作流只能有一个 start 节点，当前有 {len(start_nodes)} 个")
 
-        # 1. 验证 start 节点（有且只有一个）
+            # 2. 验证 end 节点（至少一个）
-        start_nodes = [n for n in nodes if n.get("type") == "start"]
+            end_nodes = [n for n in nodes if n.get("type") == NodeType.END]
-        if len(start_nodes) == 0:
+            if len(end_nodes) == 0:
-            errors.append("工作流必须有一个 start 节点")
+                errors.append("工作流必须至少有一个 end 节点")
-        elif len(start_nodes) > 1:
-            errors.append(f"工作流只能有一个 start 节点，当前有 {len(start_nodes)} 个")
 
-        # 2. 验证 end 节点（至少一个）
+            # 3. 验证节点 ID 唯一性
-        end_nodes = [n for n in nodes if n.get("type") == "end"]
+            node_ids = [n.get("id") for n in nodes]
-        if len(end_nodes) == 0:
+            if len(node_ids) != len(set(node_ids)):
-            errors.append("工作流必须至少有一个 end 节点")
+                duplicates = [nid for nid in node_ids if node_ids.count(nid) > 1]
+                errors.append(f"节点 ID 必须唯一，重复的 ID: {set(duplicates)}")
 
-        # 3. 验证节点 ID 唯一性
+            # 4. 验证节点必须有 id 和 type
-        node_ids = [n.get("id") for n in nodes]
+            for i, node in enumerate(nodes):
-        if len(node_ids) != len(set(node_ids)):
+                if not node.get("id"):
-            duplicates = [nid for nid in node_ids if node_ids.count(nid) > 1]
+                    errors.append(f"节点 #{i} 缺少 id 字段")
-            errors.append(f"节点 ID 必须唯一，重复的 ID: {set(duplicates)}")
+                if not node.get("type"):
+                    errors.append(f"节点 #{i} (id={node.get('id', 'unknown')}) 缺少 type 字段")
 
-        # 4. 验证节点必须有 id 和 type
+            # 5. 验证边的有效性
-        for i, node in enumerate(nodes):
+            node_id_set = set(node_ids)
-            if not node.get("id"):
+            for i, edge in enumerate(edges):
-                errors.append(f"节点 #{i} 缺少 id 字段")
+                source = edge.get("source")
-            if not node.get("type"):
+                target = edge.get("target")
-                errors.append(f"节点 #{i} (id={node.get('id', 'unknown')}) 缺少 type 字段")
 
-        # 5. 验证边的有效性
+                if not source:
-        node_id_set = set(node_ids)
+                    errors.append(f"边 #{i} 缺少 source 字段")
-        for i, edge in enumerate(edges):
+                elif source not in node_id_set:
-            source = edge.get("source")
+                    errors.append(f"边 #{i} 的 source 节点不存在: {source}")
-            target = edge.get("target")
 
-            if not source:
+                if not target:
-                errors.append(f"边 #{i} 缺少 source 字段")
+                    errors.append(f"边 #{i} 缺少 target 字段")
-            elif source not in node_id_set:
+                elif target not in node_id_set:
-                errors.append(f"边 #{i} 的 source 节点不存在: {source}")
+                    errors.append(f"边 #{i} 的 target 节点不存在: {target}")
 
-            if not target:
+            # 6. 验证所有节点可达（从 start 节点出发）
-                errors.append(f"边 #{i} 缺少 target 字段")
+            if start_nodes and not errors:  # 只有在前面验证通过时才检查可达性
-            elif target not in node_id_set:
+                reachable = WorkflowValidator._get_reachable_nodes(
-                errors.append(f"边 #{i} 的 target 节点不存在: {target}")
+                    start_nodes[0]["id"],
-        
+                    edges
-        # 6. 验证所有节点可达（从 start 节点出发）
-        if start_nodes and not errors:  # 只有在前面验证通过时才检查可达性
-            reachable = WorkflowValidator._get_reachable_nodes(
-                start_nodes[0]["id"], 
-                edges
-            )
-            unreachable = node_id_set - reachable
-            if unreachable:
-                errors.append(f"以下节点无法从 start 节点到达: {unreachable}")
-        
-        # 7. 检测循环依赖（非 loop 节点）
-        if not errors:  # 只有在前面验证通过时才检查循环
-            has_cycle, cycle_path = WorkflowValidator._has_cycle(nodes, edges)
-            if has_cycle:
-                errors.append(
-                    f"工作流存在循环依赖（请使用 loop 节点实现循环）: {' -> '.join(cycle_path)}"
                 )
+                unreachable = node_id_set - reachable
+                if unreachable:
+                    errors.append(f"以下节点无法从 start 节点到达: {unreachable}")
 
-        # 8. 验证变量名
+            # 7. 检测循环依赖（非 loop 节点）
-        from app.core.workflow.expression_evaluator import ExpressionEvaluator
+            if not errors:  # 只有在前面验证通过时才检查循环
-        var_errors = ExpressionEvaluator.validate_variable_names(variables)
+                has_cycle, cycle_path = WorkflowValidator._has_cycle(nodes, edges)
-        errors.extend(var_errors)
+                if has_cycle:
+                    errors.append(
+                        f"工作流存在循环依赖（请使用 loop 节点实现循环）: {' -> '.join(cycle_path)}"
+                    )
+
+            # 8. 验证变量名
+            from app.core.workflow.expression_evaluator import ExpressionEvaluator
+            var_errors = ExpressionEvaluator.validate_variable_names(variables)
+            errors.extend(var_errors)
 
         return len(errors) == 0, errors
 
@@ -230,7 +298,7 @@ class WorkflowValidator:
 
         # 1. 验证所有节点都有名称
         for node in nodes:
-            if node.get("type") not in ["start", "end"] and not node.get("name"):
+            if node.get("type") not in [NodeType.START, NodeType.CYCLE_START, NodeType.END] and not node.get("name"):
                 errors.append(
                     f"节点 {node.get('id')} 缺少名称（发布时必须提供）"
                 )
@@ -238,7 +306,7 @@ class WorkflowValidator:
         # 2. 验证所有非 start/end 节点都有配置
         for node in nodes:
             node_type = node.get("type")
-            if node_type not in ["start", "end"]:
+            if node_type not in [NodeType.START, NodeType.CYCLE_START, NodeType.END, NodeType.BREAK]:
                 config = node.get("config")
                 if not config or not isinstance(config, dict):
                     errors.append(
@@ -259,8 +327,8 @@ class WorkflowValidator:
 
 
 def validate_workflow_config(
-    workflow_config: dict[str, Any],
+        workflow_config: dict[str, Any],
-    for_publish: bool = False
+        for_publish: bool = False
 ) -> tuple[bool, list[str]]:
     """验证工作流配置（便捷函数）