53e0065e3e
配置 SSOT（TOML + .env） 统一错误契约 Auth 与事务边界 Redis / Celery 可靠性:业务 Redis（DB/0）与 Celery broker/backend（DB/1）显式拆分；连接池、sync client 可观测性（OpenTelemetry + LGTM）
332 lines
11 KiB
Python
332 lines
11 KiB
Python
"""WS pipeline 回归：TTS 取消不能丢段，AGENT_RESPONSE 必须为每段下发。
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- 历史 bug：客户端在多段回复中途发送 ``tts_cancel`` 时，
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``process_user_message`` 在 TTS 分支 ``break``，导致剩余段的 ``agent_response``
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被静默丢弃；FE 失去后续文本气泡，并可能停留在 "正在回复…" 状态。
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- 期望：取消仅影响后续 TTS 合成，AGENT_RESPONSE 必须为每段完整下发。
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- 同时校验：``responses`` 为空时下发 ERROR；异常路径下发 ERROR。
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"""
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from __future__ import annotations
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from types import SimpleNamespace
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from unittest.mock import AsyncMock, MagicMock
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import pytest
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from app.features.conversation.chat_turn import ChatTurnDecision, ChatTurnResult
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from app.features.conversation.history_store import HumanAiTurnIds
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from app.features.conversation.ws import pipeline as ws_pipeline
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from app.features.conversation.ws.message_types import MessageType
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class _FakeResult:
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def __init__(self) -> None:
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self.rowcount = 0
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class _FakeDb:
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"""足以驱动 process_user_message 的最小 AsyncSession 替身。"""
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def __init__(self) -> None:
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self.execute = AsyncMock(return_value=_FakeResult())
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self.commit = AsyncMock(return_value=None)
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self.rollback = AsyncMock(return_value=None)
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def _make_segment(*, segment_id: str = "seg-1") -> MagicMock:
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"""构造与 pipeline 字段访问对齐的 Segment 替身（不真正落库）。"""
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seg = MagicMock()
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seg.id = segment_id
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seg.audio_url = None
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seg.audio_duration_seconds = None
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seg.created_at = None
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return seg
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def _make_conversation(*, conversation_id: str) -> MagicMock:
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conv = MagicMock()
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conv.id = conversation_id
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conv.last_message_at = None
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return conv
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def _make_user(*, user_id: str = "user-1", language: str = "zh") -> SimpleNamespace:
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return SimpleNamespace(id=user_id, language_preference=language)
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def _ids_for(conversation_id: str) -> HumanAiTurnIds:
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return HumanAiTurnIds(
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human_message_id=f"{conversation_id}-human",
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assistant_message_id=f"{conversation_id}-ai",
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)
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def _patch_common(monkeypatch: pytest.MonkeyPatch) -> tuple[list[dict], MagicMock]:
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"""统一 mock 持久化层与段间 sleep；返回 manager.send_message 的捕获列表。"""
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sent_messages: list[dict] = []
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async def _capture_send(_conv_id: str, message: dict) -> None:
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sent_messages.append(message)
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monkeypatch.setattr(ws_pipeline.manager, "send_message", _capture_send)
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monkeypatch.setattr(ws_pipeline.manager, "active_connections", {})
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fake_store = MagicMock()
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fake_store.record_human_ai_turn_with_segment = AsyncMock()
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fake_store.attach_ai_tts_for_turn = AsyncMock(return_value=None)
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monkeypatch.setattr(
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ws_pipeline, "ConversationHistoryStore", lambda _db: fake_store
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)
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# 段间 sleep 在测试里不需要真等；保留 await 语义
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async def _no_sleep(_seconds: float) -> None: # pragma: no cover - trivial
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return None
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monkeypatch.setattr(ws_pipeline.asyncio, "sleep", _no_sleep)
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return sent_messages, fake_store
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@pytest.mark.asyncio
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async def test_tts_cancel_mid_flight_still_emits_all_agent_response_segments(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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"""关键回归：i=0 完成 TTS 后客户端取消，i=1/i=2 的 AGENT_RESPONSE 必须仍下发。"""
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sent_messages, fake_store = _patch_common(monkeypatch)
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conversation_id = "conv-cancel-mid"
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ws_pipeline.manager.active_connections[conversation_id] = object()
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fake_store.record_human_ai_turn_with_segment.return_value = _ids_for(conversation_id)
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turn_result = ChatTurnResult(
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messages=["第一段", "第二段", "第三段"],
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skip_tts=False,
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decision=ChatTurnDecision(),
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)
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monkeypatch.setattr(
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ws_pipeline.chat_turn_service,
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"process_turn",
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AsyncMock(return_value=turn_result),
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)
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monkeypatch.setattr(ws_pipeline.settings, "enable_tts", True)
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tts_calls: list[int] = []
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async def _fake_send_tts_audio(
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_conv_id: str,
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_text: str,
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*,
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chunk_index: int,
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chunk_total: int, # noqa: ARG001
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assistant_message_id: str | None, # noqa: ARG001
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tts_epoch_start: int, # noqa: ARG001
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manual: bool = False, # noqa: ARG001
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language: str = "zh", # noqa: ARG001
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) -> str | None:
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tts_calls.append(chunk_index)
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# 第 0 段合成完成后客户端按取消，第 1 段进入循环时已经是新 epoch
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if chunk_index == 0:
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ws_pipeline.bump_tts_cancel_epoch(_conv_id)
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return f"https://cos/{_conv_id}/seg-0.mp3"
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return None
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monkeypatch.setattr(ws_pipeline, "_send_tts_audio", _fake_send_tts_audio)
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db = _FakeDb()
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await ws_pipeline.process_user_message(
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conversation_id=conversation_id,
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user_message="说说你小时候",
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conversation=_make_conversation(conversation_id=conversation_id),
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segment=_make_segment(),
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db=db,
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user=_make_user(),
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tts_this_turn=True,
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)
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agent_responses = [
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m for m in sent_messages if m["type"] == MessageType.AGENT_RESPONSE
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]
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assert [m["data"]["text"] for m in agent_responses] == [
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"第一段",
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"第二段",
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"第三段",
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], "TTS 取消后剩余段的 AGENT_RESPONSE 必须仍然下发"
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assert [m["data"]["index"] for m in agent_responses] == [0, 1, 2]
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assert all(m["data"]["total"] == 3 for m in agent_responses)
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# i=0 已合成；取消后不应再触发 i=1 / i=2 的 TTS 合成
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assert tts_calls == [0]
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@pytest.mark.asyncio
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async def test_tts_cancel_before_any_segment_still_emits_agent_response(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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"""边界：TTS 在第 0 段刚开始就被取消，第 0 段的 AGENT_RESPONSE 仍必须下发。"""
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sent_messages, fake_store = _patch_common(monkeypatch)
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conversation_id = "conv-cancel-pre"
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ws_pipeline.manager.active_connections[conversation_id] = object()
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fake_store.record_human_ai_turn_with_segment.return_value = _ids_for(conversation_id)
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turn_result = ChatTurnResult(
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messages=["唯一段"],
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skip_tts=False,
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decision=ChatTurnDecision(),
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)
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monkeypatch.setattr(
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ws_pipeline.chat_turn_service,
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"process_turn",
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AsyncMock(return_value=turn_result),
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)
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monkeypatch.setattr(ws_pipeline.settings, "enable_tts", True)
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async def _fake_tts_then_cancel(
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_conv_id: str,
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_text: str,
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*,
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chunk_index: int, # noqa: ARG001
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chunk_total: int, # noqa: ARG001
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assistant_message_id: str | None, # noqa: ARG001
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tts_epoch_start: int, # noqa: ARG001
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manual: bool = False, # noqa: ARG001
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language: str = "zh", # noqa: ARG001
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) -> str | None:
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ws_pipeline.bump_tts_cancel_epoch(_conv_id)
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return None
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monkeypatch.setattr(ws_pipeline, "_send_tts_audio", _fake_tts_then_cancel)
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db = _FakeDb()
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await ws_pipeline.process_user_message(
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conversation_id=conversation_id,
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user_message="嗯",
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conversation=_make_conversation(conversation_id=conversation_id),
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segment=_make_segment(),
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db=db,
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user=_make_user(),
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tts_this_turn=True,
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)
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agent_responses = [
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m for m in sent_messages if m["type"] == MessageType.AGENT_RESPONSE
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]
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assert len(agent_responses) == 1
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assert agent_responses[0]["data"]["text"] == "唯一段"
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assert agent_responses[0]["data"]["index"] == 0
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assert agent_responses[0]["data"]["total"] == 1
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@pytest.mark.asyncio
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async def test_empty_responses_emits_terminal_error(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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"""无回复时必须下发 ERROR，否则 FE 会卡在 "正在回复…"。"""
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sent_messages, fake_store = _patch_common(monkeypatch)
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conversation_id = "conv-empty"
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ws_pipeline.manager.active_connections[conversation_id] = object()
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fake_store.record_human_ai_turn_with_segment.return_value = None
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monkeypatch.setattr(
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ws_pipeline.chat_turn_service,
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"process_turn",
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AsyncMock(
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return_value=ChatTurnResult(
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messages=[],
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skip_tts=False,
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decision=ChatTurnDecision(),
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)
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),
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)
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db = _FakeDb()
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await ws_pipeline.process_user_message(
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conversation_id=conversation_id,
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user_message="x",
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conversation=_make_conversation(conversation_id=conversation_id),
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segment=_make_segment(),
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db=db,
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user=_make_user(),
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tts_this_turn=False,
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)
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error_messages = [m for m in sent_messages if m["type"] == MessageType.ERROR]
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assert len(error_messages) == 1
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@pytest.mark.asyncio
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async def test_process_turn_exception_emits_terminal_error(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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"""LLM/编排抛错时必须下发 ERROR，否则 FE 会卡在 "正在回复…"。"""
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sent_messages, _ = _patch_common(monkeypatch)
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conversation_id = "conv-boom"
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ws_pipeline.manager.active_connections[conversation_id] = object()
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async def _boom(*_args, **_kwargs):
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raise RuntimeError("upstream blew up")
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monkeypatch.setattr(ws_pipeline.chat_turn_service, "process_turn", _boom)
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db = _FakeDb()
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await ws_pipeline.process_user_message(
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conversation_id=conversation_id,
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user_message="y",
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conversation=_make_conversation(conversation_id=conversation_id),
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segment=_make_segment(),
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db=db,
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user=_make_user(),
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tts_this_turn=False,
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)
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error_messages = [m for m in sent_messages if m["type"] == MessageType.ERROR]
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assert len(error_messages) == 1
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@pytest.mark.asyncio
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async def test_tts_disabled_emits_all_segments_without_tts_calls(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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"""未开启本轮 TTS 时不调用合成，但每段 AGENT_RESPONSE 仍必须下发。"""
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sent_messages, fake_store = _patch_common(monkeypatch)
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conversation_id = "conv-text-only"
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ws_pipeline.manager.active_connections[conversation_id] = object()
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fake_store.record_human_ai_turn_with_segment.return_value = _ids_for(conversation_id)
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monkeypatch.setattr(
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ws_pipeline.chat_turn_service,
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"process_turn",
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AsyncMock(
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return_value=ChatTurnResult(
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messages=["A", "B"],
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skip_tts=False,
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decision=ChatTurnDecision(),
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)
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),
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)
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tts_calls: list[int] = []
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async def _should_not_be_called(*_args, **_kwargs):
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tts_calls.append(1)
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return None
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monkeypatch.setattr(ws_pipeline, "_send_tts_audio", _should_not_be_called)
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db = _FakeDb()
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await ws_pipeline.process_user_message(
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conversation_id=conversation_id,
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user_message="hi",
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conversation=_make_conversation(conversation_id=conversation_id),
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segment=_make_segment(),
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db=db,
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user=_make_user(),
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tts_this_turn=False,
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)
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agent_responses = [
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m for m in sent_messages if m["type"] == MessageType.AGENT_RESPONSE
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]
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assert [m["data"]["text"] for m in agent_responses] == ["A", "B"]
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assert tts_calls == []
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