Refactor workflow routing and greeting management in Brain classes

- Update WorkflowBrain to handle greeting playback more effectively, ensuring that the initial greeting completes before transitioning to the first node.
- Introduce new methods for managing greeting states and conditions, enhancing the interaction flow for user turns.
- Refactor WorkflowLLMRouter to improve routing logic and ensure proper handling of conditional paths.
- Enhance tests to verify the correct behavior of greeting management and routing under various scenarios, including waiting for audio playback to finish.
- Update frontend components to reflect changes in edge handling and improve user experience in workflow configurations.

backend/services/node_specs.py

@@ -116,7 +116,7 @@ def node_types_response() -> dict[str, Any]:
     return {"specVersion": SPEC_VERSION, "nodeTypes": NODE_SPECS}
 
 
-def _edge_data_v3(edge: dict, source_type: str) -> dict:
+def _edge_data_v3(edge: dict) -> dict:
     data = deepcopy(edge.get("data") or {})
     if data.get("mode") in EDGE_MODES:
         data.setdefault("priority", 10)
@@ -125,7 +125,7 @@ def _edge_data_v3(edge: dict, source_type: str) -> dict:
     transition = data.pop("transition_speech", data.get("transitionSpeech", ""))
     data.update(
         {
-            "mode": "llm" if condition and source_type == "agent" else "always",
+            "mode": "llm" if condition else "always",
             "priority": 10,
             "condition": condition,
             "transitionSpeech": transition,
@@ -185,7 +185,6 @@ def normalize_graph(graph: dict[str, Any] | None) -> dict[str, Any]:
     edges = source.get("edges") or []
     global_prompt = ""
     mapped_nodes: list[dict] = []
-    type_by_id: dict[str, str] = {}
     start_prompt_nodes: dict[str, str] = {}
 
     type_map = {
@@ -220,15 +219,11 @@ def normalize_graph(graph: dict[str, Any] | None) -> dict[str, Any]:
                 data.pop(key, None)
         migrated["data"] = data
         mapped_nodes.append(migrated)
-        if migrated.get("id"):
-            type_by_id[str(migrated["id"])] = new_type
 
     mapped_edges: list[dict] = []
     for edge in edges:
         migrated = deepcopy(edge)
-        migrated["data"] = _edge_data_v3(
-            migrated, type_by_id.get(str(migrated.get("source")), "")
-        )
+        migrated["data"] = _edge_data_v3(migrated)
         mapped_edges.append(migrated)
 
     # A v2 Start was conversational. Insert a synthetic Agent so its prompt remains active.
@@ -254,7 +249,7 @@ def normalize_graph(graph: dict[str, Any] | None) -> dict[str, Any]:
         for edge in mapped_edges:
             if edge.get("source") == start_id:
                 edge["source"] = synthetic_id
-                edge["data"] = _edge_data_v3(edge, "agent")
+                edge["data"] = _edge_data_v3(edge)
                 if str(edge["data"].get("condition") or "").strip():
                     edge["data"]["mode"] = "llm"
         mapped_edges.append(
@@ -352,10 +347,8 @@ def validate_graph(graph: dict[str, Any]) -> list[str]:
         mode = data.get("mode")
         if mode not in EDGE_MODES:
             errors.append(f"边 {edge_id} 的判断模式无效:{mode}")
-        if mode == "llm" and node_by_id[source_id].get("type") != "agent":
-            errors.append(f"LLM 判断边只能从 Agent 发出:{edge_id}")
         if mode == "llm" and not str(data.get("condition") or "").strip():
-            errors.append(f"LLM 判断边缺少自然语言条件:{edge_id}")
+            errors.append(f"大模型判断边缺少自然语言条件:{edge_id}")
         if mode == "expression":
             expression_errors = _validate_expression(data.get("expression"))
             errors.extend(f"边 {edge_id}:{item}" for item in expression_errors)
@@ -370,7 +363,7 @@ def validate_graph(graph: dict[str, Any]) -> list[str]:
         if mode == "always":
             always_counts[source_id] += 1
             if always_counts[source_id] > 1:
-                errors.append(f"节点 {source_id} 最多只能有一条默认边")
+                errors.append(f"节点 {source_id} 最多只能有一条默认路径")
         incoming[target_id] += 1
         outgoing[source_id] += 1
         adj[source_id].append(target_id)
@@ -394,14 +387,6 @@ def validate_graph(graph: dict[str, Any]) -> list[str]:
                 errors.append(f"节点 {node_id} 的{label}不能少于 {lo}")
             if hi is not None and actual > hi:
                 errors.append(f"节点 {node_id} 的{label}不能多于 {hi}")
-        node_type = node.get("type")
-        if (
-            node_type in AUTOMATIC_NODE_TYPES
-            and outgoing[node_id] > 0
-            and always_counts[node_id] != 1
-        ):
-            errors.append(f"自动节点 {node_id} 存在出边时必须有且仅有一条默认边")
-
     start_id = next(
         (node_id for node_id, node in node_by_id.items() if node.get("type") == "start"),
         None,