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.

backend/tests/test_pipeline_events.py

@@ -0,0 +1,108 @@
+from __future__ import annotations
+
+import unittest
+from types import SimpleNamespace
+from unittest.mock import patch
+
+from pipecat.frames.frames import OutputTransportMessageUrgentFrame
+from services.pipecat.pipeline_events import bind_cascade_pipeline_events
+
+
+class _EventSource:
+    def __init__(self):
+        self.handlers = {}
+
+    def event_handler(self, name):
+        def decorator(handler):
+            self.handlers[name] = handler
+            return handler
+
+        return decorator
+
+
+class _Worker:
+    def __init__(self):
+        self.frames = []
+
+    async def queue_frame(self, frame):
+        self.frames.append(frame)
+
+
+class _Brain:
+    spec = SimpleNamespace(owns_context=True)
+
+    def __init__(self, worker):
+        self.worker = worker
+        self.prepared_greeting = ""
+
+    def prepare_greeting_context(self, greeting, _context):
+        self.prepared_greeting = greeting
+
+    async def on_connected(self):
+        pass
+
+    async def on_client_ready(self):
+        for content, timestamp in (
+            ("Start Edge 过渡语", "2026-07-14T10:00:00.200+00:00"),
+            ("Agent 固定进入语", "2026-07-14T10:00:00.300+00:00"),
+        ):
+            await self.worker.queue_frame(
+                OutputTransportMessageUrgentFrame(
+                    message={
+                        "type": "transcript",
+                        "role": "assistant",
+                        "content": content,
+                        "timestamp": timestamp,
+                    }
+                )
+            )
+
+
+class PipelineEventTest(unittest.IsolatedAsyncioTestCase):
+    async def test_greeting_keeps_playback_timestamp_until_client_ready(self):
+        transport = _EventSource()
+        text_input = _EventSource()
+        user_aggregator = _EventSource()
+        assistant_aggregator = _EventSource()
+        worker = _Worker()
+        brain = _Brain(worker)
+
+        bind_cascade_pipeline_events(
+            transport=transport,
+            worker=worker,
+            brain=brain,
+            context=SimpleNamespace(),
+            text_input=text_input,
+            user_aggregator=user_aggregator,
+            assistant_aggregator=assistant_aggregator,
+            greeting="助手开场白",
+            vision_enabled=False,
+            vision_state={"client_id": None},
+        )
+
+        greeting_time = "2026-07-14T10:00:00.100+00:00"
+        with patch(
+            "services.pipecat.pipeline_events.time_now_iso8601",
+            return_value=greeting_time,
+        ) as clock:
+            await transport.handlers["on_client_connected"](transport, object())
+            await text_input.handlers["on_client_ready"](text_input)
+
+        transcripts = [
+            frame.message
+            for frame in worker.frames
+            if isinstance(frame, OutputTransportMessageUrgentFrame)
+            and frame.message.get("type") == "transcript"
+        ]
+        ordered = sorted(transcripts, key=lambda message: message["timestamp"])
+        self.assertEqual(
+            [message["content"] for message in ordered],
+            ["助手开场白", "Start Edge 过渡语", "Agent 固定进入语"],
+        )
+        self.assertEqual(transcripts[0]["timestamp"], greeting_time)
+        self.assertEqual(brain.prepared_greeting, "助手开场白")
+        clock.assert_called_once_with()
+
+
+if __name__ == "__main__":
+    unittest.main()