Enhance greeting context management in Brain classes
- Introduce greeting context handling in BaseBrain and WorkflowBrain to manage assistant greetings effectively. - Implement prepare_greeting_context method to add greeting messages to the local context while preserving playback order. - Update pipeline event handling to ensure greeting timestamps are maintained until the client is ready. - Enhance tests to verify the correct behavior of greeting context management in various scenarios.
This commit is contained in:
Xin Wang
@@ -9,6 +9,7 @@ from pipecat.frames.frames import (
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LLMContextFrame,
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LLMFullResponseEndFrame,
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LLMFullResponseStartFrame,
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LLMMessagesAppendFrame,
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LLMMessagesUpdateFrame,
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LLMRunFrame,
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LLMTextFrame,
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@@ -19,6 +20,7 @@ from pipecat.processors.aggregators.llm_context import LLMContext
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from pipecat.processors.frame_processor import FrameDirection
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from schemas import AssistantUpsert, REALTIME_CAPABLE_TYPES
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from services.brains import BrainRuntime, SPECS, build_brain
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from services.brains.base import GREETING_CONTEXT_MARKER
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from services.brains.dify_llm import (
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DifyLLMService,
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last_user_text,
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@@ -227,6 +229,19 @@ class PromptBrainTests(unittest.IsolatedAsyncioTestCase):
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brain = build_brain(cfg)
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self.assertEqual(brain.system_prompt(cfg), "服务用户 王先生")
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self.assertEqual(await brain.greeting(cfg), "您好，王先生")
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context = LLMContext(
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messages=[{"role": "system", "content": brain.system_prompt(cfg)}]
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)
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brain.prepare_greeting_context("您好，王先生", context)
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self.assertEqual(
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[message["role"] for message in context.get_messages()],
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["system", "system"],
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)
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self.assertNotEqual(context.get_messages()[0]["role"], "assistant")
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self.assertEqual(
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context.get_messages()[1]["content"],
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f"{GREETING_CONTEXT_MARKER}\n您好，王先生",
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)
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async def test_end_call_tool_is_owned_by_prompt_brain(self):
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brain = build_brain(
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@@ -604,7 +619,10 @@ class WorkflowBrainTests(unittest.IsolatedAsyncioTestCase):
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{
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"id": "start",
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"type": "start",
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"data": {"name": "Start"},
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"data": {
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"name": "Start",
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"greeting": "欢迎，{{user_name}}",
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},
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},
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{
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"id": "agent",
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@@ -710,6 +728,14 @@ class WorkflowBrainTests(unittest.IsolatedAsyncioTestCase):
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apply_turn_config=apply_turn_config,
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)
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await brain.setup(cfg, runtime)
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greeting = await brain.greeting(cfg)
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self.assertEqual(greeting, "欢迎，王先生")
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greeting_message = {
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"role": "system",
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"content": f"{GREETING_CONTEXT_MARKER}\n欢迎，王先生",
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}
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brain.prepare_greeting_context(greeting, context)
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self.assertEqual(context.get_messages(), [greeting_message])
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await brain.on_connected()
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self.assertEqual(brain._manager.current_node, "agent")
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variable_events = [
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@@ -758,7 +784,7 @@ class WorkflowBrainTests(unittest.IsolatedAsyncioTestCase):
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agent_config = brain._agent_config("agent")
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self.assertIn("王先生", agent_config["role_message"])
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self.assertIn("工作流路由已在用户一轮输入结束时完成", agent_config["role_message"])
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self.assertEqual(agent_config["task_messages"], [])
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self.assertEqual(agent_config["task_messages"], [greeting_message])
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self.assertFalse(agent_config["respond_immediately"])
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self.assertFalse(any(isinstance(frame, LLMRunFrame) for frame in worker.frames))
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self.assertEqual(
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@@ -785,7 +811,21 @@ class WorkflowBrainTests(unittest.IsolatedAsyncioTestCase):
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self.assertEqual(fixed_config["pre_actions"][0]["text"], "您好，王先生")
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self.assertEqual(
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fixed_config["task_messages"],
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[{"role": "assistant", "content": "您好，王先生"}],
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[
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greeting_message,
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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(
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brain._agent_config(
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"agent",
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[{"role": "assistant", "content": "正在进入下一阶段"}],
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)["task_messages"],
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[
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greeting_message,
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{"role": "assistant", "content": "正在进入下一阶段"},
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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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@@ -800,8 +840,19 @@ class WorkflowBrainTests(unittest.IsolatedAsyncioTestCase):
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]
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self.assertEqual(
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context_updates[-1].messages,
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[{"role": "assistant", "content": "您好，王先生"}],
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[
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greeting_message,
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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.assertFalse(
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any(
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isinstance(frame, OutputTransportMessageUrgentFrame)
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and frame.message.get("source") == "workflow-fixed-reply"
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for frame in queued
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)
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)
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await brain.on_client_ready()
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fixed_reply_events = [
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frame.message
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for frame in queued
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@@ -833,6 +884,22 @@ class WorkflowBrainTests(unittest.IsolatedAsyncioTestCase):
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self.assertTrue(call_end.ending)
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self.assertTrue(call_end.armed)
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self.assertTrue(any(getattr(frame, "text", "") == "感谢来电" for frame in queued))
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transition_context_frames = [
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frame
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for frame in worker.frames
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if isinstance(frame, LLMMessagesAppendFrame)
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and frame.messages
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== [{"role": "assistant", "content": "正在为你结束流程"}]
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]
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self.assertTrue(transition_context_frames)
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transition_events = [
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frame.message
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for frame in queued
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if isinstance(frame, OutputTransportMessageUrgentFrame)
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and frame.message.get("source") == "workflow-edge-transition"
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]
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self.assertEqual(transition_events[0]["content"], "正在为你结束流程")
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self.assertEqual(transition_events[0]["nodeId"], "end")
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assistant_transcripts = [
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frame.message.get("content")
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for frame in queued
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