fix: gate cache writes and reads on a shared cacheability verdict

Cacheable is now a strict subset of deliverable: salvaged streams,
content-less results and length/filter/unknown finishes are delivered
but never written, and the read path applies the same verdict to the
stored values before hit overrides (invalid stream_end or non-string
finish read as a miss; 1.3.9 fidelity entries fall back to the
completion's finish). Hits reset stream_end. The legacy
_has_completion_output helper is folded into _is_cacheable.

Red: 13 tests in tests/unit/test_cache.py failed before this change
(uncacheable results were written and replayed; new fields not reset).
This commit is contained in:
2026-10-14 23:39:50 -04:00
parent 39a319e34e
commit 48ba36dd94
4 changed files with 203 additions and 36 deletions
+58 -20
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@@ -24,7 +24,8 @@ from polygateway.types import (
OpenAIChatCompletion, OpenAIChatCompletion,
ResponseMode, ResponseMode,
ThinkingObservation, ThinkingObservation,
_has_completion_output, _effective_finish,
_is_cacheable,
) )
if TYPE_CHECKING: if TYPE_CHECKING:
@@ -148,6 +149,54 @@ def build_cache_key(
return _KEY_PREFIX + hashlib.sha256(payload.encode("utf-8")).hexdigest() return _KEY_PREFIX + hashlib.sha256(payload.encode("utf-8")).hexdigest()
def _response_cacheable(mode: ResponseMode, response: LLMResponse) -> bool:
"""写路径判据;与读路径共用 `_is_cacheable` 与 `_effective_finish`,口径不分叉。"""
return _is_cacheable(
mode=mode,
content=response.content,
finish_reason=_effective_finish(response.finish_reason, response.completion),
stream_end=response.stream_end,
completion=response.completion,
)
def _restore_fields(raw: str, mode: ResponseMode) -> dict[str, Any]:
"""缓存原文 → LLMResponse 字段;不可缓存或形态坏抛 ValueError(调用方按 miss)。
可缓存判定对**存储原值**进行、先于命中覆盖: 覆盖后 `stream_end` 恒 None,
在那之后判会把 salvaged 条目放行(设计 §6)。
"""
data = json.loads(raw)
fields = {k: v for k, v in data.items() if k in _RESPONSE_FIELDS}
completion = fields.get("completion")
if completion is not None:
if not isinstance(completion, dict):
raise ValueError("缓存 completion 必须为对象")
fields["completion"] = OpenAIChatCompletion(**completion)
finish = _effective_finish(fields.get("finish_reason"), fields.get("completion"))
if finish is not None and not isinstance(finish, str):
raise ValueError("缓存 finish_reason 必须为字符串或 null")
if not _is_cacheable(
mode=mode,
content=fields.get("content", ""),
finish_reason=finish,
stream_end=fields.get("stream_end"),
completion=fields.get("completion"),
):
# 非法 stream_end 也落这里: 它关乎内容完整性,不像 thinking_observation
# 那样可以宽容降级
raise ValueError("缓存条目不可缓存(截断/空正文/非自然结束/非法 stream_end)")
fields["finish_reason"] = finish
# JSON 里存的是 StrEnum 的字符串值,不转就复活成裸 str,与字段注解分叉
# (下游 `is ThinkingObservation.OBSERVED` 会在命中路径上静默为 False);
# 键缺失即升级前写入的旧条目,交给 dataclass 默认值
if "thinking_observation" in fields:
fields["thinking_observation"] = _coerce_observation(fields["thinking_observation"])
if "applied_effort" in fields:
fields["applied_effort"] = _coerce_applied_effort(fields["applied_effort"])
return fields
class CacheMW: class CacheMW:
"""洋葱第二层(遥测内、结构化外)。 """洋葱第二层(遥测内、结构化外)。
@@ -195,6 +244,11 @@ class CacheMW:
if hit is not None: if hit is not None:
return hit return hit
response = await call_next(request) response = await call_next(request)
if not _response_cacheable(request.response_mode, response):
# 交付照常,只是不进 TTL: 截断/空正文/非自然结束固化后会把一次偶然
# 变成必然(设计 §6)。debug 级: 这是常规分流,不是故障
logger.debug("结果不可缓存(截断/空正文/非自然结束),跳过写入")
return response
try: try:
serialized = self._serialize(response) serialized = self._serialize(response)
except Exception as exc: except Exception as exc:
@@ -208,31 +262,15 @@ class CacheMW:
def _rehydrate(self, raw: str, request: ChatRequest) -> LLMResponse | None: def _rehydrate(self, raw: str, request: ChatRequest) -> LLMResponse | None:
"""反序列化 + 按本次调用的 structured 档零网络重建;失败按未命中。""" """反序列化 + 按本次调用的 structured 档零网络重建;失败按未命中。"""
try: try:
data = json.loads(raw) fields = _restore_fields(raw, request.response_mode)
fields = {k: v for k, v in data.items() if k in _RESPONSE_FIELDS}
completion = fields.get("completion")
if completion is not None:
if not isinstance(completion, dict):
raise ValueError("缓存 completion 必须为对象")
fields["completion"] = OpenAIChatCompletion(**completion)
if request.response_mode == "openai":
if fields.get("completion") is None:
raise ValueError("保真缓存缺 completion")
if not _has_completion_output(fields.get("content", ""), fields["completion"]):
raise ValueError("保真缓存无有效正文或工具产物")
structured_data = self._rebuild_structured(fields.get("content", ""), request) structured_data = self._rebuild_structured(fields.get("content", ""), request)
# JSON 里存的是 StrEnum 的字符串值,不转就复活成裸 str,与字段注解分叉
# (下游 `is ThinkingObservation.OBSERVED` 会在命中路径上静默为 False);
# 键缺失即升级前写入的旧条目,交给 dataclass 默认值
if "thinking_observation" in fields:
fields["thinking_observation"] = _coerce_observation(fields["thinking_observation"])
if "applied_effort" in fields:
fields["applied_effort"] = _coerce_applied_effort(fields["applied_effort"])
fields.update( fields.update(
cache_hit=True, cache_hit=True,
latency_ms=0, latency_ms=0,
ttft_ms=None, ttft_ms=None,
max_inter_token_ms=None, max_inter_token_ms=None,
# 结束方式描述的是"那次流",命中没有流可言(与 ttft_ms 同口径)
stream_end=None,
call_id=str(uuid.uuid4()), call_id=str(uuid.uuid4()),
structured_data=structured_data, structured_data=structured_data,
# 显式覆盖: 历史条目里的 `call_stats` 是个 dict,而 `_RESPONSE_FIELDS` # 显式覆盖: 历史条目里的 `call_stats` 是个 dict,而 `_RESPONSE_FIELDS`
+7 -16
View File
@@ -663,23 +663,14 @@ def _is_cacheable(
if _classify_finish(finish_reason) not in ("natural", "absent"): if _classify_finish(finish_reason) not in ("natural", "absent"):
return False return False
if mode == "openai": if mode == "openai":
return completion is not None and _has_completion_output(content, completion) # 判原文而非投影: 协议原文为空时不信任缓存里的旧投影(1.3.9 同口径)
return content.strip() != "" if completion is None:
def _has_completion_output(content: str, completion: OpenAIChatCompletion | None) -> bool:
"""成功须有投影正文或完整工具;协议原文为空时不信任缓存旧投影。
只判定产物存在性,不替代协议结构校验,也不收紧快照类型的构造用途。
transport 与缓存共用此规则,避免空响应从缓存旁路成功。
"""
if completion is not None:
if completion.message.get("tool_calls"):
return True
raw_content = completion.message.get("content")
if not isinstance(raw_content, str) or not raw_content.strip():
return False return False
return isinstance(content, str) and bool(content.strip()) raw = completion.message.get("content")
return _summarize_message(
completion.message, raw if isinstance(raw, str) else ""
).body_output
return content.strip() != ""
@dataclass(frozen=True) @dataclass(frozen=True)
+24
View File
@@ -30,6 +30,13 @@ def _resp(content="cached"):
return LLMResponse(content, "", "m", "p", 1, 2, 30, None, None, False, "orig") return LLMResponse(content, "", "m", "p", 1, 2, 30, None, None, False, "orig")
def _const(response):
async def terminal(request):
return response
return terminal
@pytest.fixture @pytest.fixture
async def redis_cache(): async def redis_cache():
import redis.asyncio as aioredis import redis.asyncio as aioredis
@@ -82,6 +89,23 @@ class TestRealRedisRoundtrip:
assert first.cache_hit is False and second.cache_hit is True assert first.cache_hit is False and second.cache_hit is True
assert calls["n"] == 1 assert calls["n"] == 1
async def test_completion_verdict_fields_roundtrip(self, redis_cache, namespace):
"""1.3.10: finish_reason/stream_end 经真实 Redis 往返;不可缓存结果不落库。"""
mw = CacheMW(
backend=redis_cache, model_fingerprint="m", default_namespace=namespace, ttl_s=60
)
from dataclasses import replace
ok = replace(_resp(), finish_reason="stop", stream_end="eof_after_finish")
first = await mw(ChatRequest(messages=_MSGS), _const(ok))
second = await mw(ChatRequest(messages=_MSGS), _const(ok))
assert first.cache_hit is False and second.cache_hit is True
assert second.finish_reason == "stop" and second.stream_end is None
truncated = replace(_resp(), stream_end="salvaged")
other = [{"role": "user", "content": "integration-salvaged"}]
await mw(ChatRequest(messages=other), _const(truncated))
assert await redis_cache.get(build_cache_key("m", other, namespace, None)) is None
async def test_namespace_isolation_on_shared_instance(self, redis_cache, namespace): async def test_namespace_isolation_on_shared_instance(self, redis_cache, namespace):
"""多项目共用同一 Redis 时,namespace 不同绝不互相命中(防毒化铁律)。""" """多项目共用同一 Redis 时,namespace 不同绝不互相命中(防毒化铁律)。"""
other = f"pgw:test:{uuid.uuid4().hex}" other = f"pgw:test:{uuid.uuid4().hex}"
+114
View File
@@ -1002,3 +1002,117 @@ async def test_openai_tool_only_cache_hits_without_origin():
hit = await mw(request, terminal) hit = await mw(request, terminal)
assert hit.cache_hit and terminal.calls == 0 assert hit.cache_hit and terminal.calls == 0
assert hit.completion == completion assert hit.completion == completion
# —— 1.3.10(#30/#31): 可缓存 ⊂ 可交付,读写共用同一判据(设计 §6)——
_OK_COMPLETION = OpenAIChatCompletion({"role": "assistant", "content": "ok"}, "stop", "up", None)
_THINK_LENGTH = OpenAIChatCompletion(
{"role": "assistant", "reasoning_content": "t"}, "length", "up", None
)
_THINK_STOP = OpenAIChatCompletion(
{"role": "assistant", "reasoning_content": "t"}, "stop", "up", None
)
@pytest.mark.parametrize(
("mode", "response"),
[
("text", _resp(stream_end="salvaged")),
("text", _resp(finish_reason="length")),
("text", _resp(finish_reason="content_filter")),
("text", _resp(finish_reason="end_turn")),
("openai", _resp(content="", finish_reason="length", completion=_THINK_LENGTH)),
("openai", _resp(content="", finish_reason="stop", completion=_THINK_STOP)),
],
)
async def test_uncacheable_results_are_delivered_but_not_written(mode, response):
"""截断/空正文/非自然结束: 照常交回,但不写缓存,下次回源。"""
backend = InMemoryCache()
mw = _mw(backend)
terminal = _Terminal(response)
request = ChatRequest(messages=_MSGS, response_mode=mode)
assert (await mw(request, terminal)) is response
assert (await mw(request, terminal)).cache_hit is False
assert terminal.calls == 2 and not backend._store
def _stored(mode, **fields):
"""直接注入一条缓存原文(模拟旧版本或别的进程写入)。"""
backend = InMemoryCache()
data = dataclasses.asdict(_resp(**fields))
data.pop("structured_data", None)
data.pop("call_stats", None)
key = build_cache_key("m", _MSGS, "proj", None, response_mode=mode)
backend._store[key] = (float("inf"), json.dumps(data))
return backend, key
async def _hit(backend, mode):
terminal = _Terminal(_resp(content="fresh", completion=_OK_COMPLETION, finish_reason="stop"))
response = await _mw(backend)(ChatRequest(messages=_MSGS, response_mode=mode), terminal)
return response, terminal.calls
@pytest.mark.parametrize(
("mode", "fields"),
[
("text", {"stream_end": "salvaged"}),
("text", {"stream_end": "bogus"}),
("text", {"finish_reason": "length"}),
("text", {"finish_reason": 5}),
("openai", {"content": "", "completion": _THINK_LENGTH, "finish_reason": "length"}),
],
)
async def test_injected_uncacheable_entries_read_as_miss(mode, fields):
"""读路径对存储原值判定(覆盖之前): 不可缓存即 miss 回源。"""
backend, _ = _stored(mode, **fields)
response, calls = await _hit(backend, mode)
assert response.cache_hit is False and calls == 1
async def test_legacy_fidelity_length_entry_falls_back_to_completion_finish():
"""1.3.9 保真条目无顶层 finish: 回退 completion.finish_reason 识别为不可缓存。"""
completion = OpenAIChatCompletion({"role": "assistant", "content": "a"}, "length", None, None)
backend, key = _stored("openai", completion=completion)
data = json.loads(backend._store[key][1])
for name in ("finish_reason", "stream_end"):
data.pop(name)
backend._store[key] = (float("inf"), json.dumps(data))
response, calls = await _hit(backend, "openai")
assert response.cache_hit is False and calls == 1
async def test_legacy_text_entry_without_new_fields_still_hits():
"""1.3.9 文本条目无新键: 仍命中;命中 stream_end=None。"""
backend, key = _stored("text")
data = json.loads(backend._store[key][1])
for name in ("finish_reason", "stream_end"):
data.pop(name)
backend._store[key] = (float("inf"), json.dumps(data))
response, calls = await _hit(backend, "text")
assert response.cache_hit is True and calls == 0
assert response.stream_end is None and response.finish_reason is None
async def test_hit_resets_stream_end_and_keeps_effective_finish():
"""命中: stream_end 置 None;finish_reason 取判定所用值(顶层缺省时回退)。"""
backend, key = _stored("openai", completion=_OK_COMPLETION, stream_end="eof_after_finish")
data = json.loads(backend._store[key][1])
data.pop("finish_reason")
backend._store[key] = (float("inf"), json.dumps(data))
response, calls = await _hit(backend, "openai")
assert response.cache_hit is True and calls == 0
assert response.stream_end is None and response.finish_reason == "stop"
async def test_new_fields_roundtrip_through_cache():
"""两新字段随序列化往返;命中只重置 stream_end。"""
backend = InMemoryCache()
mw = _mw(backend)
terminal = _Terminal(_resp(finish_reason="stop", stream_end="eof_after_finish"))
await mw(ChatRequest(messages=_MSGS), terminal)
stored = json.loads(next(iter(backend._store.values()))[1])
assert stored["finish_reason"] == "stop" and stored["stream_end"] == "eof_after_finish"
hit = await mw(ChatRequest(messages=_MSGS), terminal)
assert hit.cache_hit is True and hit.finish_reason == "stop" and hit.stream_end is None