feat(adapters): 实现 GovernedLLMClient 四层治理栈
流式 SSE + 三层看门狗 + 重试退避 + 熔断 + Redis 缓存 + 遥测。 provider 差异处理（DeepSeek reasoning_content vs Qwen think 标签）。 Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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"""GovernedLLMClient 单元测试 — 四层治理栈核心路径验证。"""
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from __future__ import annotations
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import json
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import time
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from typing import Any
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from unittest.mock import patch
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import httpx
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import pytest
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from adapters.breaker import CircuitBreaker
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from adapters.llm import CircuitOpenError, GovernedLLMClient
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from core.types import LLMResponse
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# ── 辅助类 ──────────────────────────────────────────────────────────
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class _FakeRedisCache:
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"""内存字典替身，模拟 RedisResponseCache 的 get/set 接口。"""
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def __init__(self) -> None:
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self._store: dict[str, LLMResponse] = {}
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async def get(
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self, model: str, messages: list[dict[str, str]]
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) -> LLMResponse | None:
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key = f"{model}:{json.dumps(messages, sort_keys=True)}"
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return self._store.get(key)
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async def set(
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self,
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model: str,
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messages: list[dict[str, str]],
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response: LLMResponse,
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) -> None:
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key = f"{model}:{json.dumps(messages, sort_keys=True)}"
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self._store[key] = response
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class _FakeTelemetry:
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"""记录所有 record_llm_call 调用的替身。"""
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def __init__(self) -> None:
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self.calls: list[dict[str, Any]] = []
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async def record_llm_call(self, **kwargs: Any) -> None:
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self.calls.append(kwargs)
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# ── 工具函数 ─────────────────────────────────────────────────────────
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async def _async_line_iter(lines: list[str]):
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"""将字符串列表转为异步行迭代器。"""
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for line in lines:
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yield line
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def _make_sse_lines(
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content_chunks: list[str],
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*,
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reasoning_chunks: list[str] | None = None,
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model: str = "test-model",
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usage: dict[str, int] | None = None,
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) -> list[str]:
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"""构造 SSE 文本行序列，模拟 OpenAI 兼容流式响应。"""
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lines: list[str] = []
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# 先产出 reasoning 帧
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for chunk in reasoning_chunks or []:
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frame = {
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"choices": [{"delta": {"reasoning_content": chunk}}],
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"model": model,
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}
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lines.append(f"data: {json.dumps(frame)}\n")
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# 再产出 content 帧
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for chunk in content_chunks:
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frame = {
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"choices": [{"delta": {"content": chunk}}],
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"model": model,
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}
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lines.append(f"data: {json.dumps(frame)}\n")
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# usage 帧
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if usage is None:
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usage = {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}
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frame_usage = {"choices": [], "usage": usage, "model": model}
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lines.append(f"data: {json.dumps(frame_usage)}\n")
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# 终止标记
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lines.append("data: [DONE]\n")
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return lines
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def _build_client(
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*,
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breaker: CircuitBreaker | None = None,
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cache: _FakeRedisCache | None = None,
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telemetry: _FakeTelemetry | None = None,
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provider: str = "test-provider",
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model: str = "test-model",
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thinking: bool = False,
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) -> GovernedLLMClient:
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"""构造标准测试客户端。"""
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return GovernedLLMClient(
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model=model,
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base_url="http://localhost:8000/v1",
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api_key="test-key",
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provider=provider,
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thinking=thinking,
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breaker=breaker or CircuitBreaker(fail_threshold=3, cooldown_s=60),
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cache=cache or _FakeRedisCache(),
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telemetry=telemetry or _FakeTelemetry(),
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timeout_s=30.0,
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ttft_timeout_s=10.0,
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inter_token_timeout_s=5.0,
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max_retries=3,
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retry_base_delay_s=0.0, # 测试不等待
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retry_max_delay_s=0.0,
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)
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# ── 测试用例 ─────────────────────────────────────────────────────────
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@pytest.mark.asyncio
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async def test_circuit_open_raises():
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"""熔断器开启 → 直接抛 CircuitOpenError，不发请求。"""
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breaker = CircuitBreaker(fail_threshold=1, cooldown_s=600)
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breaker.force_open("test-provider", time.monotonic())
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client = _build_client(breaker=breaker)
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with pytest.raises(CircuitOpenError):
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await client.chat([{"role": "user", "content": "hello"}])
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@pytest.mark.asyncio
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async def test_cache_hit_returns_cached_and_records_telemetry():
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"""缓存命中 → 返回缓存响应 + 新 call_id + 遥测记录 cache_hit=True。"""
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cache = _FakeRedisCache()
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telemetry = _FakeTelemetry()
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client = _build_client(cache=cache, telemetry=telemetry)
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# 预填缓存
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cached_resp = LLMResponse(
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content="cached answer",
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thinking="",
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model="test-model",
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provider="test-provider",
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prompt_tokens=10,
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completion_tokens=5,
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latency_ms=0,
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ttft_ms=None,
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max_inter_token_ms=None,
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cache_hit=True,
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call_id="old-id",
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)
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messages = [{"role": "user", "content": "hello"}]
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await cache.set("test-model", messages, cached_resp)
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result = await client.chat(messages)
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assert result.content == "cached answer"
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assert result.cache_hit is True
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# 每次调用都生成新 call_id
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assert result.call_id != "old-id"
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# 遥测已记录
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assert len(telemetry.calls) == 1
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assert telemetry.calls[0]["cache_hit"] is True
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@pytest.mark.asyncio
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async def test_successful_streaming_call():
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"""正常流式调用 → 正确累积 content + thinking + 采集 ttft_ms + tokens。"""
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telemetry = _FakeTelemetry()
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client = _build_client(telemetry=telemetry)
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messages = [{"role": "user", "content": "hello"}]
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sse_lines = _make_sse_lines(
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["Hello", " world"],
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reasoning_chunks=["Let me", " think"],
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usage={"prompt_tokens": 20, "completion_tokens": 10, "total_tokens": 30},
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)
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async def fake_stream_request(_messages: Any) -> list[str]:
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return sse_lines
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with patch.object(client, "_stream_request", side_effect=fake_stream_request):
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result = await client.chat(messages)
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assert result.content == "Hello world"
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assert result.thinking == "Let me think"
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assert result.prompt_tokens == 20
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assert result.completion_tokens == 10
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assert result.ttft_ms is not None
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assert result.ttft_ms >= 0
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assert result.cache_hit is False
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# 遥测已记录
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assert len(telemetry.calls) == 1
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assert telemetry.calls[0]["cache_hit"] is False
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assert telemetry.calls[0]["error"] is None
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@pytest.mark.asyncio
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async def test_transient_error_retries_and_records_telemetry():
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"""ConnectError 重试 2 次后成功 → 结果正确 + 遥测记录成功。"""
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telemetry = _FakeTelemetry()
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client = _build_client(telemetry=telemetry)
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messages = [{"role": "user", "content": "hello"}]
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sse_lines = _make_sse_lines(["OK"])
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call_count = 0
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async def flaky_stream(_messages: Any) -> list[str]:
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nonlocal call_count
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call_count += 1
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if call_count <= 2:
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raise httpx.ConnectError("connection refused")
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return sse_lines
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with patch.object(client, "_stream_request", side_effect=flaky_stream):
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result = await client.chat(messages)
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assert result.content == "OK"
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assert call_count == 3
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# 前 2 次失败也应记遥测
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error_calls = [c for c in telemetry.calls if c.get("error") is not None]
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assert len(error_calls) == 2
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# 最后 1 次成功也记了遥测
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success_calls = [c for c in telemetry.calls if c.get("error") is None]
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assert len(success_calls) == 1
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@pytest.mark.asyncio
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async def test_fatal_error_force_opens_breaker():
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"""401 → force_open 熔断器 + 遥测记录 error。"""
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breaker = CircuitBreaker(fail_threshold=3, cooldown_s=60)
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telemetry = _FakeTelemetry()
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client = _build_client(breaker=breaker, telemetry=telemetry)
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messages = [{"role": "user", "content": "hello"}]
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mock_response = httpx.Response(
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status_code=401,
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request=httpx.Request("POST", "http://localhost:8000/v1/chat/completions"),
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)
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async def auth_fail(_messages: Any) -> list[str]:
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raise httpx.HTTPStatusError(
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"Unauthorized", request=mock_response.request, response=mock_response
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)
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with patch.object(client, "_stream_request", side_effect=auth_fail), \
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pytest.raises(httpx.HTTPStatusError):
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await client.chat(messages)
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# 熔断器已被 force_open
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assert breaker.is_open("test-provider", time.monotonic())
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# 遥测已记录 error
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assert len(telemetry.calls) == 1
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assert telemetry.calls[0]["error"] is not None
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@pytest.mark.asyncio
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async def test_qwen_thinking_stripped():
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"""Qwen 模型 <think> 标签被正确剥离到 thinking 字段。"""
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from adapters.llm import _strip_qwen_thinking
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content_with_think = "<think>这是思考过程</think>这是正式输出"
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content, thinking = _strip_qwen_thinking(content_with_think)
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assert content == "这是正式输出"
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assert thinking == "这是思考过程"
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# 无 think 标签时原样返回
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plain = "纯文本输出"
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content2, thinking2 = _strip_qwen_thinking(plain)
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assert content2 == "纯文本输出"
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assert thinking2 == ""
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@pytest.mark.asyncio
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async def test_parent_call_id_forwarded_to_telemetry():
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"""parent_call_id 和 session_id 正确传递到遥测记录。"""
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telemetry = _FakeTelemetry()
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client = _build_client(telemetry=telemetry)
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messages = [{"role": "user", "content": "hello"}]
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sse_lines = _make_sse_lines(["result"])
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async def fake_stream(_messages: Any) -> list[str]:
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return sse_lines
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with patch.object(client, "_stream_request", side_effect=fake_stream):
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await client.chat(
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messages, session_id="sess-42", parent_call_id="parent-99"
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)
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assert len(telemetry.calls) == 1
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assert telemetry.calls[0]["session_id"] == "sess-42"
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assert telemetry.calls[0]["parent_call_id"] == "parent-99"
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