Refactor workflow agent and routing components for improved functionality
- Introduce WorkflowAgentStage to manage agent stage configurations and enhance interaction with the workflow engine. - Implement WorkflowEdgeEvaluator for priority-aware edge evaluation, improving routing decisions based on conditions and user turns. - Update WorkflowBrain to handle user turns and routing more effectively, ensuring agents cannot have only one default path. - Enhance CallEndCoordinator to track speech events and manage call termination based on queued speech. - Add new models and output handling for workflow interactions, improving clarity and maintainability. - Update tests to validate the new routing logic and agent behavior under various scenarios.
This commit is contained in:
Xin Wang
@@ -28,7 +28,7 @@ from services.brains.dify_llm import (
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)
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from services.brains.workflow_brain import WorkflowBrain
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from services.runtime_variables import prepare_dynamic_config
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from services.workflow_router import STAY_ON_CURRENT_NODE
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from services.workflow.models import LLMRouteResult, RouteStatus
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class FakeLLM:
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@@ -47,6 +47,7 @@ class FakeCallEnd:
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self.finished = False
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self.response_started = False
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self.waited_for_text: bool | None = None
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self.tracked_speeches = 0
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def begin(self, reason: str) -> None:
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self.ending = True
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@@ -58,6 +59,14 @@ class FakeCallEnd:
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def arm_after_speech(self) -> None:
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self.armed = True
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def track_speech(self) -> None:
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self.tracked_speeches += 1
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async def arm_after_tracked_speech(self) -> None:
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self.armed = True
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if self.tracked_speeches == 0:
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await self.finish()
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async def finish_after_current_speech(self, *, has_text: bool) -> None:
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self.waited_for_text = has_text
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if has_text:
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@@ -824,7 +833,10 @@ class WorkflowBrainTests(unittest.IsolatedAsyncioTestCase):
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async def select_edge(self, **_kwargs):
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self.calls += 1
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return "goto_eat"
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return LLMRouteResult(
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status=RouteStatus.MATCHED,
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function_name="goto_eat",
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)
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manager = FakeManager()
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router = FakeRouter()
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@@ -847,6 +859,45 @@ class WorkflowBrainTests(unittest.IsolatedAsyncioTestCase):
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self.assertTrue(any(isinstance(frame, LLMRunFrame) for frame in queued))
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self.assertIn("我想吃饭", brain._store.values["system__conversation_history"])
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async def test_start_expression_condition_also_waits_for_user_turn(self):
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brain = WorkflowBrain(
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{
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"specVersion": 3,
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"settings": {},
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"nodes": [
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{"id": "start", "type": "start", "data": {}},
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{"id": "agent", "type": "agent", "data": {}},
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],
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"edges": [
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{
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"id": "route",
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"source": "start",
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"target": "agent",
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"data": {
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"mode": "expression",
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"priority": 10,
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"expression": {
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"combinator": "and",
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"rules": [
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{
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"variable": "route",
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"operator": "eq",
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"value": "agent",
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}
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],
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},
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},
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}
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],
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}
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)
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brain._store.values["route"] = "agent"
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config = await brain._initial_node_config()
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self.assertEqual(config["name"], "start")
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self.assertEqual(brain._state.status.value, "waiting_user")
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async def test_automatic_node_can_follow_llm_condition(self):
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brain = WorkflowBrain(
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{
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@@ -896,7 +947,10 @@ class WorkflowBrainTests(unittest.IsolatedAsyncioTestCase):
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class FakeRouter:
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async def select_edge(self, **kwargs):
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self.node_name = kwargs["node_name"]
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return "goto_to_agent"
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return LLMRouteResult(
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status=RouteStatus.MATCHED,
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function_name="goto_to_agent",
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)
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router = FakeRouter()
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brain._router = router
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@@ -961,7 +1015,7 @@ class WorkflowBrainTests(unittest.IsolatedAsyncioTestCase):
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class FakeRouter:
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def __init__(self):
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self.result = STAY_ON_CURRENT_NODE
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self.result = LLMRouteResult(status=RouteStatus.NO_MATCH)
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self.edge_ids = []
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async def select_edge(self, **kwargs):
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@@ -975,7 +1029,10 @@ class WorkflowBrainTests(unittest.IsolatedAsyncioTestCase):
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self.assertEqual(router.edge_ids, ["llm"])
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self.assertEqual(selected["id"], "expression")
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router.result = "goto_llm"
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router.result = LLMRouteResult(
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status=RouteStatus.MATCHED,
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function_name="goto_llm",
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)
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selected = await brain._select_edge("agent")
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self.assertEqual(selected["id"], "llm")
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@@ -1183,21 +1240,19 @@ class WorkflowBrainTests(unittest.IsolatedAsyncioTestCase):
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brain._engine.data("agent")["entryMode"] = "generate"
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generate_config = brain._agent_config("agent")
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self.assertTrue(generate_config["respond_immediately"])
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self.assertFalse(generate_config["respond_immediately"])
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worker.frames.clear()
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await brain._manager.set_node_from_config(generate_config)
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self.assertTrue(any(isinstance(frame, LLMRunFrame) for frame in worker.frames))
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self.assertFalse(any(isinstance(frame, LLMRunFrame) for frame in worker.frames))
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await brain._after_node_activated(generate_config)
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self.assertTrue(any(isinstance(frame, LLMRunFrame) for frame in queued))
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brain._engine.data("agent").update(
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{"entryMode": "fixed_speech", "entrySpeech": "您好，{{user_name}}"}
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)
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fixed_config = brain._agent_config("agent")
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self.assertFalse(fixed_config["respond_immediately"])
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self.assertEqual(
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fixed_config["pre_actions"][0]["type"],
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"workflow_fixed_speech",
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)
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self.assertEqual(fixed_config["pre_actions"][0]["text"], "您好，王先生")
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self.assertNotIn("pre_actions", fixed_config)
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self.assertEqual(
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fixed_config["task_messages"],
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[
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@@ -1216,10 +1271,10 @@ class WorkflowBrainTests(unittest.IsolatedAsyncioTestCase):
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{"role": "assistant", "content": "您好，王先生"},
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],
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)
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self.assertEqual(fixed_config["pre_actions"][0]["node_id"], "agent")
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worker.frames.clear()
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queued.clear()
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await brain._manager.set_node_from_config(fixed_config)
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await brain._after_node_activated(fixed_config)
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self.assertTrue(any(isinstance(frame, TTSSpeakFrame) for frame in queued))
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self.assertFalse(any(isinstance(frame, LLMRunFrame) for frame in worker.frames))
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context_updates = [
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@@ -1263,7 +1318,10 @@ class WorkflowBrainTests(unittest.IsolatedAsyncioTestCase):
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class FakeRouter:
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async def select_edge(self, **_kwargs):
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return "goto_finish"
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return LLMRouteResult(
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status=RouteStatus.MATCHED,
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function_name="goto_finish",
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)
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brain._router = FakeRouter()
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handled = await brain.on_user_turn_end("我的需求已经说完了")
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