feat: add governed embedding client with batching
This commit is contained in:
@@ -6,7 +6,8 @@
|
||||
"""
|
||||
|
||||
from polygateway.client import GatewayClient, gather_bounded
|
||||
from polygateway.config import GatewaySettings
|
||||
from polygateway.config import EmbeddingSettings, GatewaySettings
|
||||
from polygateway.embedding import EmbeddingClient
|
||||
from polygateway.errors import (
|
||||
AllSourcesExhausted,
|
||||
CircuitOpenError,
|
||||
@@ -18,8 +19,9 @@ from polygateway.errors import (
|
||||
SourceDeadError,
|
||||
TransientError,
|
||||
)
|
||||
from polygateway.pricing import ModelPrice, PricingTable
|
||||
from polygateway.providers import DEFAULT_PROFILES, ProviderProfile, register_provider
|
||||
from polygateway.types import LLMResponse, SourceConfig
|
||||
from polygateway.types import EmbeddingResponse, LLMResponse, SourceConfig
|
||||
|
||||
__version__ = "0.1.0"
|
||||
|
||||
@@ -27,12 +29,17 @@ __all__ = [
|
||||
"DEFAULT_PROFILES",
|
||||
"AllSourcesExhausted",
|
||||
"CircuitOpenError",
|
||||
"EmbeddingClient",
|
||||
"EmbeddingResponse",
|
||||
"EmbeddingSettings",
|
||||
"GatewayClient",
|
||||
"GatewaySettings",
|
||||
"GatewayUnavailableError",
|
||||
"GovernanceBackendError",
|
||||
"LLMResponse",
|
||||
"ModelPrice",
|
||||
"PolyGatewayError",
|
||||
"PricingTable",
|
||||
"ProviderProfile",
|
||||
"RequestRejectedError",
|
||||
"ResultInvalidError",
|
||||
|
||||
@@ -341,3 +341,48 @@ def _guard_stall(settings: GatewaySettings) -> None:
|
||||
def _load_lease_ttl(env: Mapping[str, str]) -> float:
|
||||
found = _first(env, "PGW_LEASE_TTL_S")
|
||||
return float(_cast(found[1], "float", found[0])) if found else _DEFAULT_LEASE_TTL_S
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class EmbeddingSettings:
|
||||
"""Embedding scope 装配配置(M2 §7): 复用 GatewaySettings + embedding 专用键。
|
||||
|
||||
专用键不进 GatewaySettings(LLM scope 不受影响): `{SCOPE}__BATCH_SIZE`
|
||||
必填(分批是行为关键,不设默认)、`{SCOPE}__NORMALIZE`/`{SCOPE}__EXPECTED_DIM`
|
||||
可选。cache/structured 键对 embedding 无意义,装配时忽略。
|
||||
"""
|
||||
|
||||
gateway: GatewaySettings
|
||||
batch_size: int
|
||||
normalize: bool = False
|
||||
expected_dim: int | None = None
|
||||
|
||||
@classmethod
|
||||
def from_env(
|
||||
cls,
|
||||
scope: str = "EMBED",
|
||||
env: Mapping[str, str] | None = None,
|
||||
*,
|
||||
env_file: str = ".env",
|
||||
) -> EmbeddingSettings:
|
||||
if env is None:
|
||||
env = {
|
||||
k: v for k, v in {**dotenv_values(env_file), **os.environ}.items() if v is not None
|
||||
}
|
||||
scope_u = scope.upper()
|
||||
gateway = GatewaySettings.from_env(scope_u, env=env)
|
||||
key, raw = _require(env, f"{scope_u}__BATCH_SIZE")
|
||||
batch_size = int(_cast(raw, "int", key))
|
||||
if batch_size < 1:
|
||||
raise ValueError(f"{scope_u}__BATCH_SIZE 必须 ≥ 1")
|
||||
norm = _first(env, f"{scope_u}__NORMALIZE")
|
||||
dim = _first(env, f"{scope_u}__EXPECTED_DIM")
|
||||
expected_dim = int(_cast(dim[1], "int", dim[0])) if dim else None
|
||||
if expected_dim is not None and expected_dim < 1:
|
||||
raise ValueError(f"{scope_u}__EXPECTED_DIM 必须 ≥ 1")
|
||||
return cls(
|
||||
gateway=gateway,
|
||||
batch_size=batch_size,
|
||||
normalize=bool(_cast(norm[1], "bool", norm[0])) if norm else False,
|
||||
expected_dim=expected_dim,
|
||||
)
|
||||
|
||||
@@ -0,0 +1,492 @@
|
||||
"""EmbeddingClient: 治理化 embedding 调用(M2 设计 §7,方案 G2)。
|
||||
|
||||
独立精简治理循环,**复用**库的算法件: `RateLimiter`/`ProviderGate` 端口与
|
||||
两种后端、错误四分类、`backoff_delay` 退避公式、`SourceCooldownMemo`、
|
||||
`TelemetryEmitter`(遥测单一 helper 铁律)。选源/等待循环与 RetryMW 同构
|
||||
——这是设计 §7.1 已声明的有限重复(chat 循环含流式/结构化/缓存分支,
|
||||
强行合一才是复制);行为口径(stall 双条件、记账降级、取消穿透)与 chat
|
||||
完全一致。
|
||||
|
||||
对参考实现的已声明裁决(设计 §7.3): async httpx;返回 list[list[float]]
|
||||
(核心不依赖 numpy);normalize 开关(VT 语义,防除零 max(norm,1e-12));
|
||||
必填 batch_size 批间串行;GovDoc 自研退避与 on_usage 回调、VT 同步接口
|
||||
均**有意放弃**。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import math
|
||||
import random
|
||||
import time
|
||||
import uuid
|
||||
from dataclasses import dataclass
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
from loguru import logger
|
||||
|
||||
from polygateway.config import EmbeddingSettings
|
||||
from polygateway.errors import (
|
||||
AllSourcesExhausted,
|
||||
CircuitOpenError,
|
||||
GovernanceBackendError,
|
||||
PolyGatewayError,
|
||||
RequestRejectedError,
|
||||
ResultInvalidError,
|
||||
SourceDeadError,
|
||||
TransientError,
|
||||
)
|
||||
from polygateway.middleware.breaker import BreakerGate
|
||||
from polygateway.middleware.ratelimit import QuotaGate
|
||||
from polygateway.middleware.retry import _failure_reason, backoff_delay
|
||||
from polygateway.middleware.telemetry import TelemetryEmitter
|
||||
from polygateway.sources import SourceCooldownMemo
|
||||
from polygateway.types import ChatRequest, EmbeddingResponse, LLMResponse
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from collections.abc import Awaitable, Callable, Mapping
|
||||
|
||||
from polygateway.ports import (
|
||||
EmbeddingTransport,
|
||||
GateDecision,
|
||||
Permit,
|
||||
ProviderGate,
|
||||
RateLimiter,
|
||||
SourceSelector,
|
||||
TelemetryRecorder,
|
||||
)
|
||||
from polygateway.pricing import PricingTable
|
||||
from polygateway.types import (
|
||||
BackpressurePolicy,
|
||||
EmbeddingTransportResult,
|
||||
RetryPolicy,
|
||||
SourceConfig,
|
||||
)
|
||||
|
||||
_TELEMETRY_TEXT_CAP = 200 # 遥测行每条 text 截断长度(原文不整段入库,VT R12)
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class _FailedBatch:
|
||||
exc: PolyGatewayError
|
||||
immediate: bool
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class _BatchOutcome:
|
||||
result: EmbeddingTransportResult
|
||||
source: SourceConfig
|
||||
call_id: str
|
||||
latency_ms: int
|
||||
|
||||
|
||||
class EmbeddingClient:
|
||||
"""治理化 embedding 入口;与 GatewayClient 共享后端实例即共享全局闸。"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
scope: str,
|
||||
sources: list[SourceConfig],
|
||||
selector: SourceSelector,
|
||||
limiter: RateLimiter,
|
||||
breaker: ProviderGate,
|
||||
transport: EmbeddingTransport,
|
||||
retry: RetryPolicy,
|
||||
backpressure: BackpressurePolicy,
|
||||
quota_full: str = "wait",
|
||||
telemetry: TelemetryRecorder | None = None,
|
||||
pricing: PricingTable | None = None,
|
||||
batch_size: int,
|
||||
normalize: bool = False,
|
||||
expected_dim: int | None = None,
|
||||
now: Callable[[], float] = time.monotonic,
|
||||
sleep: Callable[[float], Awaitable[None]] = asyncio.sleep,
|
||||
rng: Callable[[], float] = random.random,
|
||||
) -> None:
|
||||
if batch_size < 1:
|
||||
raise ValueError("batch_size 必须 ≥ 1")
|
||||
if quota_full not in ("wait", "fail_fast"):
|
||||
raise ValueError(f"quota_full 必须是 wait|fail_fast: {quota_full!r}")
|
||||
if expected_dim is not None and expected_dim < 1:
|
||||
raise ValueError("expected_dim 必须 ≥ 1")
|
||||
self._scope = scope
|
||||
self._sources = list(sources)
|
||||
self._selector = selector
|
||||
self._quota = QuotaGate(limiter)
|
||||
self._breaker = BreakerGate(breaker)
|
||||
self._transport = transport
|
||||
self._retry = retry
|
||||
self._bp = backpressure
|
||||
self._quota_full = quota_full
|
||||
self._emitter = TelemetryEmitter(telemetry, pricing=pricing) if telemetry else None
|
||||
self._telemetry = telemetry
|
||||
self._pricing = pricing
|
||||
self._batch_size = batch_size
|
||||
self._normalize = normalize
|
||||
self._expected_dim = expected_dim
|
||||
self._memo = SourceCooldownMemo(now=now)
|
||||
self._now = now
|
||||
self._sleep = sleep
|
||||
self._rng = rng
|
||||
self._closed = False
|
||||
|
||||
async def embed(
|
||||
self,
|
||||
texts: list[str],
|
||||
*,
|
||||
session_id: str | None = None,
|
||||
parent_call_id: str | None = None,
|
||||
) -> EmbeddingResponse:
|
||||
"""一次治理 embedding 调用: 按 batch_size 切批,批间串行,全批合并返回。"""
|
||||
if not isinstance(texts, list) or any(not isinstance(t, str) for t in texts):
|
||||
raise TypeError("texts 必须是 list[str](显式优于隐式,不收单条 str)")
|
||||
if not texts:
|
||||
return EmbeddingResponse(
|
||||
vectors=[],
|
||||
dim=0,
|
||||
model="",
|
||||
provider="",
|
||||
prompt_tokens=0,
|
||||
usage_source="measured",
|
||||
latency_ms=0,
|
||||
call_id=str(uuid.uuid4()),
|
||||
source_name="",
|
||||
)
|
||||
if not self._sources:
|
||||
raise AllSourcesExhausted(scope=self._scope, reason="no_sources", retry_after_s=0.0)
|
||||
outcomes = []
|
||||
for start in range(0, len(texts), self._batch_size):
|
||||
outcomes.append(
|
||||
await self._embed_batch(texts[start : start + self._batch_size], session_id, parent_call_id)
|
||||
)
|
||||
return self._merge(outcomes)
|
||||
|
||||
# —— 治理循环(与 RetryMW 同构;设计 §7.1 已声明的有限重复)——
|
||||
|
||||
async def _embed_batch(
|
||||
self, batch: list[str], session_id: str | None, parent_call_id: str | None
|
||||
) -> _BatchOutcome:
|
||||
fails = 0
|
||||
reasons: dict[str, str] = {}
|
||||
entered_at = self._now()
|
||||
while True:
|
||||
picked, gate_rejections = await self._pick_runnable(reasons)
|
||||
if picked is None:
|
||||
await self._on_no_runnable(gate_rejections, reasons, entered_at)
|
||||
continue
|
||||
outcome = await self._attempt(batch, *picked, reasons, session_id, parent_call_id)
|
||||
if isinstance(outcome, _BatchOutcome):
|
||||
return outcome
|
||||
fails += 1
|
||||
if fails >= self._retry.max_attempts:
|
||||
raise AllSourcesExhausted(
|
||||
scope=self._scope,
|
||||
reason="retry_exhausted",
|
||||
retry_after_s=self._retry.backoff_base_s,
|
||||
per_source_reasons=reasons,
|
||||
) from outcome.exc
|
||||
if not outcome.immediate:
|
||||
await self._sleep(backoff_delay(self._retry, fails, outcome.exc, self._rng))
|
||||
|
||||
async def _pick_runnable(
|
||||
self, reasons: dict[str, str]
|
||||
) -> tuple[tuple[SourceConfig, Permit, GateDecision] | None, int]:
|
||||
stats = {s.name: await self._quota.stats(s) for s in self._sources}
|
||||
gate_rejections = 0
|
||||
for cand in self._selector.order(self._sources, stats):
|
||||
if self._memo.active(cand.name):
|
||||
gate_rejections += 1
|
||||
reasons[cand.name] = "cooldown"
|
||||
continue
|
||||
permit = await self._quota.try_acquire(cand)
|
||||
if permit is None:
|
||||
reasons.setdefault(cand.name, "rate_limited")
|
||||
continue
|
||||
entry = None
|
||||
try:
|
||||
entry = await self._breaker.try_enter(cand, uuid.uuid4().hex)
|
||||
finally:
|
||||
if entry is None:
|
||||
await self._settle_and_release(permit, 0)
|
||||
if entry.allowed:
|
||||
return (cand, permit, entry), gate_rejections
|
||||
gate_rejections += 1
|
||||
reasons[cand.name] = "circuit_open"
|
||||
self._memo.set_until(cand.name, self._now() + entry.retry_after_s)
|
||||
await self._settle_and_release(permit, 0)
|
||||
return None, gate_rejections
|
||||
|
||||
async def _on_no_runnable(
|
||||
self, gate_rejections: int, reasons: dict[str, str], entered_at: float
|
||||
) -> None:
|
||||
if gate_rejections == len(self._sources):
|
||||
names = tuple(s.name for s in self._sources)
|
||||
raise CircuitOpenError(
|
||||
scope=self._scope,
|
||||
retry_after_s=await self._breaker.retry_after_s(names),
|
||||
per_source_reasons=reasons,
|
||||
)
|
||||
if self._quota_full == "fail_fast":
|
||||
raise AllSourcesExhausted(
|
||||
scope=self._scope,
|
||||
reason="quota_exhausted",
|
||||
retry_after_s=self._bp.poll_interval_s,
|
||||
per_source_reasons=reasons,
|
||||
)
|
||||
stall = self._bp.stall_window_s
|
||||
if self._now() - entered_at > stall and await self._quota.progress_age_s() > stall:
|
||||
names = tuple(s.name for s in self._sources)
|
||||
raise AllSourcesExhausted(
|
||||
scope=self._scope,
|
||||
reason="stalled",
|
||||
retry_after_s=await self._breaker.retry_after_s(names),
|
||||
per_source_reasons=reasons,
|
||||
)
|
||||
await self._sleep(self._bp.poll_interval_s * (0.5 + 0.5 * self._rng()))
|
||||
|
||||
async def _attempt(
|
||||
self,
|
||||
batch: list[str],
|
||||
source: SourceConfig,
|
||||
permit: Permit,
|
||||
entry: GateDecision,
|
||||
reasons: dict[str, str],
|
||||
session_id: str | None,
|
||||
parent_call_id: str | None,
|
||||
) -> _BatchOutcome | _FailedBatch:
|
||||
call_id = str(uuid.uuid4())
|
||||
started = self._now()
|
||||
actual = 0
|
||||
try:
|
||||
result = await self._transport.embed(texts=batch, source=source, call_id=call_id)
|
||||
if self._expected_dim is not None and result.dim != self._expected_dim:
|
||||
raise ResultInvalidError(
|
||||
f"{source.name} 维度 {result.dim} 不符期望 {self._expected_dim}",
|
||||
source_name=source.name,
|
||||
operation="embedding",
|
||||
)
|
||||
actual = result.prompt_tokens
|
||||
await self._record_quietly(self._breaker.record_success(entry))
|
||||
await self._record_quietly(self._quota.mark_progress())
|
||||
latency_ms = int((self._now() - started) * 1000)
|
||||
await self._emit(batch, source, call_id, started, session_id, parent_call_id, result)
|
||||
return _BatchOutcome(result, source, call_id, latency_ms)
|
||||
except (RequestRejectedError, ResultInvalidError) as exc:
|
||||
await self._gate_on_terminal(exc, entry)
|
||||
await self._emit(batch, source, call_id, started, session_id, parent_call_id, error=exc)
|
||||
raise
|
||||
except asyncio.CancelledError:
|
||||
if entry.is_probe:
|
||||
await self._record_quietly(self._breaker.release_probe(entry))
|
||||
await self._emit(
|
||||
batch, source, call_id, started, session_id, parent_call_id, error="cancelled"
|
||||
)
|
||||
raise
|
||||
except (SourceDeadError, TransientError) as exc:
|
||||
dead = isinstance(exc, SourceDeadError)
|
||||
reason = _failure_reason(exc)
|
||||
reasons[source.name] = reason
|
||||
await self._record_quietly(self._breaker.record_failure(entry, reason, dead))
|
||||
if not dead:
|
||||
actual = source.est_tokens # 保守: 失败请求可能已被网关计费(CHS 同款)
|
||||
await self._emit(batch, source, call_id, started, session_id, parent_call_id, error=exc)
|
||||
return _FailedBatch(exc, immediate=dead)
|
||||
finally:
|
||||
await self._settle_and_release(permit, actual)
|
||||
|
||||
# —— 辅助 ——
|
||||
|
||||
async def _gate_on_terminal(self, exc: PolyGatewayError, entry: GateDecision) -> None:
|
||||
"""终态异常的门控写回(与 RetryMW 同口径): 坏结果/网关健康拒绝 ≠ 坏服务
|
||||
→ 记成功;网关没响应的拒绝若持探针则归还。"""
|
||||
if isinstance(exc, ResultInvalidError) or exc.status_code is not None:
|
||||
await self._record_quietly(self._breaker.record_success(entry))
|
||||
elif entry.is_probe:
|
||||
await self._record_quietly(self._breaker.release_probe(entry))
|
||||
|
||||
async def _record_quietly(self, write_back: Awaitable[object]) -> None:
|
||||
"""记账侧写回降级(与 RetryMW._record_quietly 同口径,设计 §10)。"""
|
||||
try:
|
||||
await write_back
|
||||
except asyncio.CancelledError:
|
||||
raise
|
||||
except GovernanceBackendError as exc:
|
||||
logger.warning("embedding 治理记账写回降级(不冒泡): {}", exc)
|
||||
|
||||
async def _settle_and_release(self, permit: Permit, actual: int) -> None:
|
||||
try:
|
||||
try:
|
||||
await permit.settle(actual)
|
||||
finally:
|
||||
await permit.release()
|
||||
except asyncio.CancelledError:
|
||||
raise
|
||||
except Exception as exc:
|
||||
logger.warning("embedding permit 结算/释放失败(不掩盖主异常): {}", exc)
|
||||
|
||||
async def _emit(
|
||||
self,
|
||||
batch: list[str],
|
||||
source: SourceConfig,
|
||||
call_id: str,
|
||||
started: float,
|
||||
session_id: str | None,
|
||||
parent_call_id: str | None,
|
||||
result: EmbeddingTransportResult | None = None,
|
||||
error: object | None = None,
|
||||
) -> None:
|
||||
"""逐批遥测(经同一 Emitter): messages=截断 texts、向量绝不入库。"""
|
||||
if self._emitter is None:
|
||||
return
|
||||
request = ChatRequest(
|
||||
messages=[{"role": "user", "content": t[:_TELEMETRY_TEXT_CAP]} for t in batch],
|
||||
session_id=session_id,
|
||||
parent_call_id=parent_call_id,
|
||||
)
|
||||
response = None
|
||||
if result is not None:
|
||||
response = LLMResponse(
|
||||
content=f"<vectors n={len(result.vectors)} dim={result.dim}>",
|
||||
thinking="",
|
||||
model=source.model,
|
||||
provider=source.provider,
|
||||
prompt_tokens=result.prompt_tokens,
|
||||
completion_tokens=0,
|
||||
latency_ms=int((self._now() - started) * 1000),
|
||||
ttft_ms=None,
|
||||
max_inter_token_ms=None,
|
||||
cache_hit=False,
|
||||
call_id=call_id,
|
||||
source_name=source.name,
|
||||
usage_source=result.usage_source,
|
||||
)
|
||||
await self._emitter.emit_attempt(
|
||||
request=request,
|
||||
source=source,
|
||||
call_id=call_id,
|
||||
latency_ms=int((self._now() - started) * 1000),
|
||||
response=response,
|
||||
error=None if error is None else str(error),
|
||||
)
|
||||
|
||||
def _merge(self, outcomes: list[_BatchOutcome]) -> EmbeddingResponse:
|
||||
"""全批合并(设计 §7.3): vectors 拼接、tokens/latency 求和、保守 usage_source。"""
|
||||
vectors = [v for o in outcomes for v in o.result.vectors]
|
||||
if self._normalize:
|
||||
vectors = [_l2_normalize(v) for v in vectors]
|
||||
first = outcomes[0]
|
||||
prompt_tokens = sum(o.result.prompt_tokens for o in outcomes)
|
||||
estimated = any(o.result.usage_source == "estimated" for o in outcomes)
|
||||
return EmbeddingResponse(
|
||||
vectors=vectors,
|
||||
dim=first.result.dim,
|
||||
model=first.source.model,
|
||||
provider=first.source.provider,
|
||||
prompt_tokens=prompt_tokens,
|
||||
usage_source="estimated" if estimated else "measured",
|
||||
latency_ms=sum(o.latency_ms for o in outcomes),
|
||||
call_id=first.call_id,
|
||||
source_name=first.source.name,
|
||||
cost=self._total_cost(outcomes),
|
||||
)
|
||||
|
||||
def _total_cost(self, outcomes: list[_BatchOutcome]) -> float | None:
|
||||
if self._pricing is None:
|
||||
return None
|
||||
costs = [
|
||||
self._pricing.cost(o.source.model, o.result.prompt_tokens, 0) for o in outcomes
|
||||
]
|
||||
known = [c for c in costs if c is not None]
|
||||
return sum(known) if known else None
|
||||
|
||||
async def aclose(self) -> None:
|
||||
"""幂等释放 transport 连接池与遥测连接(与 GatewayClient 对称)。"""
|
||||
if self._closed:
|
||||
return
|
||||
self._closed = True
|
||||
transport_aclose = getattr(self._transport, "aclose", None)
|
||||
if transport_aclose is not None:
|
||||
await transport_aclose()
|
||||
telemetry_aclose = getattr(self._telemetry, "aclose", None)
|
||||
if telemetry_aclose is not None:
|
||||
await telemetry_aclose()
|
||||
else:
|
||||
telemetry_close = getattr(self._telemetry, "close", None)
|
||||
if telemetry_close is not None:
|
||||
telemetry_close()
|
||||
|
||||
async def __aenter__(self) -> EmbeddingClient:
|
||||
return self
|
||||
|
||||
async def __aexit__(self, *exc_info: object) -> None:
|
||||
await self.aclose()
|
||||
|
||||
# —— 工厂(与 GatewayClient 对称)——
|
||||
|
||||
@classmethod
|
||||
def from_settings(
|
||||
cls,
|
||||
settings: EmbeddingSettings,
|
||||
*,
|
||||
limiter: RateLimiter | None = None,
|
||||
breaker: ProviderGate | None = None,
|
||||
telemetry: TelemetryRecorder | None = None,
|
||||
registry: Mapping[str, object] | None = None,
|
||||
) -> EmbeddingClient:
|
||||
"""按配置装配;显式传入的后端实例即共享(与 chat scope 共享全局闸)。"""
|
||||
from polygateway.client import (
|
||||
_build_breaker,
|
||||
_build_limiter,
|
||||
_build_selector,
|
||||
_build_telemetry,
|
||||
)
|
||||
from polygateway.pricing import PricingTable
|
||||
from polygateway.transports.openai_compat import OpenAICompatTransport
|
||||
|
||||
gw = settings.gateway
|
||||
sources = list(gw.sources)
|
||||
return cls(
|
||||
scope=gw.scope,
|
||||
sources=sources,
|
||||
selector=_build_selector(gw.selector),
|
||||
limiter=limiter or _build_limiter(gw, sources),
|
||||
breaker=breaker or _build_breaker(gw),
|
||||
transport=OpenAICompatTransport(registry=registry),
|
||||
retry=gw.retry,
|
||||
backpressure=gw.backpressure,
|
||||
quota_full=gw.quota_full,
|
||||
telemetry=telemetry if telemetry is not None else _build_telemetry(gw),
|
||||
pricing=PricingTable.from_file(gw.pricing_path)
|
||||
if gw.pricing_path is not None
|
||||
else None,
|
||||
batch_size=settings.batch_size,
|
||||
normalize=settings.normalize,
|
||||
expected_dim=settings.expected_dim,
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def from_env(
|
||||
cls,
|
||||
scope: str = "EMBED",
|
||||
*,
|
||||
limiter: RateLimiter | None = None,
|
||||
breaker: ProviderGate | None = None,
|
||||
telemetry: TelemetryRecorder | None = None,
|
||||
registry: Mapping[str, object] | None = None,
|
||||
env: Mapping[str, str] | None = None,
|
||||
) -> EmbeddingClient:
|
||||
"""从 .env/环境变量装配一个 embedding scope 的 client。"""
|
||||
return cls.from_settings(
|
||||
EmbeddingSettings.from_env(scope, env=env),
|
||||
limiter=limiter,
|
||||
breaker=breaker,
|
||||
telemetry=telemetry,
|
||||
registry=registry,
|
||||
)
|
||||
|
||||
|
||||
def _l2_normalize(vector: list[float]) -> list[float]:
|
||||
"""L2 归一化;`max(norm, 1e-12)` 防除零(VT embedding.py:167-170 语义)。"""
|
||||
norm = max(math.sqrt(sum(x * x for x in vector)), 1e-12)
|
||||
return [x / norm for x in vector]
|
||||
@@ -0,0 +1,83 @@
|
||||
"""真实网关 /embeddings 端点探测(M2 设计 §11.6;人类默认口径: 实现时探测)。
|
||||
|
||||
对 .env 的 LLM 源网关发一次真实 embeddings 请求: 支持则记录向量证据,
|
||||
不支持(404/翻译为领域错误)则 skip 并把响应记录进 tests/outputs/
|
||||
(降级证据)。无 EMBED scope 配置时复用 LLM 源的 base_url/api_key。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import dataclasses
|
||||
import os
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
from dotenv import dotenv_values
|
||||
|
||||
from polygateway.errors import PolyGatewayError
|
||||
from polygateway.transports.openai_compat import OpenAICompatTransport
|
||||
from polygateway.types import SourceConfig
|
||||
|
||||
_ENV = {k: v for k, v in {**dotenv_values(".env"), **os.environ}.items() if v is not None}
|
||||
|
||||
pytestmark = pytest.mark.skipif(
|
||||
"LLM__MINIMAX__1__BASE_URL" not in _ENV, reason="缺真实网关配置(.env)"
|
||||
)
|
||||
|
||||
_OUT = Path("tests/outputs/embedding")
|
||||
|
||||
|
||||
def _record(name: str, lines: list[str]) -> Path:
|
||||
_OUT.mkdir(parents=True, exist_ok=True)
|
||||
path = _OUT / f"{name}_{datetime.now():%Y%m%d_%H%M%S}.md"
|
||||
path.write_text("\n".join(lines) + "\n", encoding="utf-8")
|
||||
return path
|
||||
|
||||
|
||||
async def test_probe_real_gateway_embeddings():
|
||||
source = SourceConfig(
|
||||
name="probe_1",
|
||||
provider="minimax",
|
||||
base_url=_ENV["LLM__MINIMAX__1__BASE_URL"],
|
||||
api_key=_ENV["LLM__MINIMAX__1__API_KEY"],
|
||||
model=_ENV.get("PGW_EMBED_PROBE_MODEL", "text-embedding-v1"),
|
||||
timeout_s=30.0,
|
||||
est_tokens=8,
|
||||
)
|
||||
transport = OpenAICompatTransport()
|
||||
try:
|
||||
result = await transport.embed(
|
||||
texts=["polygateway embedding probe"], source=source, call_id="probe"
|
||||
)
|
||||
except PolyGatewayError as exc:
|
||||
path = _record(
|
||||
"probe_unsupported",
|
||||
[
|
||||
"# Embedding 端点探测: 网关不支持",
|
||||
f"- base_url: {source.base_url}",
|
||||
f"- model: {source.model}",
|
||||
f"- 错误分类: {type(exc).__name__}",
|
||||
f"- status_code: {exc.status_code}",
|
||||
f"- 详情: {exc}",
|
||||
"",
|
||||
"结论: e2e 按设计 §11.6 降级,embedding 行为由 unit 全覆盖。",
|
||||
],
|
||||
)
|
||||
await transport.aclose()
|
||||
pytest.skip(f"网关不支持 embeddings({type(exc).__name__}),证据: {path}")
|
||||
else:
|
||||
await transport.aclose()
|
||||
assert result.dim > 0 and len(result.vectors) == 1
|
||||
_record(
|
||||
"probe_supported",
|
||||
[
|
||||
"# Embedding 端点探测: 网关支持",
|
||||
f"- base_url: {source.base_url}",
|
||||
f"- model: {source.model}",
|
||||
f"- dim: {result.dim}",
|
||||
f"- usage: {result.prompt_tokens}({result.usage_source})",
|
||||
f"- 向量前 5 维: {result.vectors[0][:5]}",
|
||||
f"- raw: {dataclasses.asdict(result)['raw']}",
|
||||
],
|
||||
)
|
||||
@@ -155,3 +155,214 @@ class TestEmbedTransport:
|
||||
async def test_empty_texts_rejected(self):
|
||||
with pytest.raises(ValueError):
|
||||
await _transport_with(lambda r: None).embed(texts=[], source=_src(), call_id="c")
|
||||
|
||||
|
||||
# ═══════════ T9: EmbeddingClient 治理循环 ═══════════
|
||||
|
||||
import asyncio # noqa: E402
|
||||
|
||||
from polygateway.backends.memory.breaker import InMemoryGate # noqa: E402
|
||||
from polygateway.backends.memory.limiter import InMemoryLimiter # noqa: E402
|
||||
from polygateway.config import EmbeddingSettings # noqa: E402
|
||||
from polygateway.embedding import EmbeddingClient # noqa: E402
|
||||
from polygateway.sources import RoundRobinSelector # noqa: E402
|
||||
from polygateway.types import ( # noqa: E402
|
||||
BackpressurePolicy,
|
||||
BreakerConfig,
|
||||
GlobalLimits,
|
||||
RetryPolicy,
|
||||
)
|
||||
|
||||
_BREAKER = BreakerConfig(fail_threshold=3, cooldown_s=60.0, probe_ttl_s=120.0)
|
||||
_NO_GLOBAL = GlobalLimits(max_concurrency=0, rpm=0, tpm=0)
|
||||
|
||||
|
||||
def _vec_for(texts):
|
||||
"""确定性向量: 每条 text 一个 [len(text)] 一维向量,便于断言保序。"""
|
||||
return EmbeddingTransportResult(
|
||||
vectors=[[float(len(t))] for t in texts],
|
||||
dim=1,
|
||||
prompt_tokens=len(texts),
|
||||
usage_source="measured",
|
||||
raw={},
|
||||
)
|
||||
|
||||
|
||||
class ScriptedEmbedTransport:
|
||||
"""按脚本响应: 条目为 Exception / "ok"(按输入生成) / EmbeddingTransportResult / "hang"。"""
|
||||
|
||||
def __init__(self, script):
|
||||
self.script = list(script)
|
||||
self.calls = []
|
||||
|
||||
async def embed(self, *, texts, source, call_id):
|
||||
self.calls.append((source.name, list(texts), call_id))
|
||||
action = self.script.pop(0)
|
||||
if isinstance(action, Exception):
|
||||
raise action
|
||||
if action == "hang":
|
||||
await asyncio.Event().wait()
|
||||
if action == "ok":
|
||||
return _vec_for(texts)
|
||||
return action
|
||||
|
||||
|
||||
class _MemoryRecorder:
|
||||
def __init__(self):
|
||||
self.rows = []
|
||||
|
||||
async def record_llm_call(self, **fields):
|
||||
self.rows.append(fields)
|
||||
|
||||
|
||||
def _embed_client(sources, script, *, batch_size=2, telemetry=None, **overrides):
|
||||
limiter = InMemoryLimiter(
|
||||
scope="embed",
|
||||
sources={s.name: s for s in sources},
|
||||
global_limits=_NO_GLOBAL,
|
||||
lease_ttl_s=100.0,
|
||||
)
|
||||
kwargs = {
|
||||
"scope": "embed",
|
||||
"sources": sources,
|
||||
"selector": RoundRobinSelector(),
|
||||
"limiter": limiter,
|
||||
"breaker": InMemoryGate(config=_BREAKER),
|
||||
"transport": ScriptedEmbedTransport(script),
|
||||
"retry": RetryPolicy(max_attempts=3, backoff_base_s=0.001, backoff_max_s=0.01),
|
||||
"backpressure": BackpressurePolicy(stall_window_s=300.0, poll_interval_s=0.001),
|
||||
"batch_size": batch_size,
|
||||
"telemetry": telemetry,
|
||||
}
|
||||
kwargs.update(overrides)
|
||||
client = EmbeddingClient(**kwargs)
|
||||
return client, limiter
|
||||
|
||||
|
||||
class TestEmbedBatching:
|
||||
async def test_batches_sequential_and_order_preserved(self):
|
||||
texts = ["a", "bb", "ccc", "dddd", "eeeee"]
|
||||
client, _ = _embed_client([_src()], ["ok", "ok", "ok"], batch_size=2)
|
||||
resp = await client.embed(texts)
|
||||
transport = client._transport
|
||||
assert [len(batch) for _, batch, _ in transport.calls] == [2, 2, 1]
|
||||
assert resp.vectors == [[1.0], [2.0], [3.0], [4.0], [5.0]] # 全批拼接保序
|
||||
assert resp.prompt_tokens == 5 and resp.dim == 1
|
||||
|
||||
async def test_empty_input_short_circuits(self):
|
||||
client, _ = _embed_client([_src()], [])
|
||||
resp = await client.embed([])
|
||||
assert resp.vectors == [] and resp.prompt_tokens == 0
|
||||
assert client._transport.calls == []
|
||||
|
||||
async def test_usage_source_aggregates_conservatively(self):
|
||||
estimated = EmbeddingTransportResult(
|
||||
vectors=[[1.0], [1.0]], dim=1, prompt_tokens=9, usage_source="estimated", raw={}
|
||||
)
|
||||
client, _ = _embed_client([_src()], ["ok", estimated], batch_size=2)
|
||||
resp = await client.embed(["a", "b", "c", "d"])
|
||||
assert resp.usage_source == "estimated" # 任一批 estimated 则整体 estimated
|
||||
assert resp.prompt_tokens == 2 + 9
|
||||
|
||||
|
||||
class TestEmbedPostProcess:
|
||||
async def test_normalize_l2(self):
|
||||
raw = EmbeddingTransportResult(
|
||||
vectors=[[3.0, 4.0]], dim=2, prompt_tokens=1, usage_source="measured", raw={}
|
||||
)
|
||||
client, _ = _embed_client([_src()], [raw], normalize=True)
|
||||
resp = await client.embed(["x"])
|
||||
assert resp.vectors[0] == pytest.approx([0.6, 0.8])
|
||||
|
||||
async def test_zero_vector_normalize_no_nan(self):
|
||||
raw = EmbeddingTransportResult(
|
||||
vectors=[[0.0, 0.0]], dim=2, prompt_tokens=1, usage_source="measured", raw={}
|
||||
)
|
||||
client, _ = _embed_client([_src()], [raw], normalize=True)
|
||||
resp = await client.embed(["x"])
|
||||
assert resp.vectors[0] == [0.0, 0.0] # max(norm, 1e-12) 防除零(VT 语义)
|
||||
|
||||
async def test_expected_dim_violation_is_result_invalid(self):
|
||||
client, _ = _embed_client([_src()], ["ok"], expected_dim=768)
|
||||
with pytest.raises(ResultInvalidError):
|
||||
await client.embed(["x"])
|
||||
|
||||
|
||||
class TestEmbedGovernance:
|
||||
async def test_transient_retries_then_succeeds(self):
|
||||
client, _ = _embed_client(
|
||||
[_src()], [TransientError("boom", status_code=500), "ok"], batch_size=8
|
||||
)
|
||||
resp = await client.embed(["a", "b"])
|
||||
assert resp.vectors == [[1.0], [1.0]]
|
||||
assert len(client._transport.calls) == 2
|
||||
|
||||
async def test_source_dead_switches_source(self):
|
||||
s1, s2 = _src(name="e1"), _src(name="e2")
|
||||
client, _ = _embed_client(
|
||||
[s1, s2], [SourceDeadError("401", status_code=401), "ok"], batch_size=8
|
||||
)
|
||||
await client.embed(["a"])
|
||||
assert [name for name, _, _ in client._transport.calls] == ["e1", "e2"]
|
||||
|
||||
async def test_cancel_releases_permit(self):
|
||||
client, limiter = _embed_client([_src(max_concurrency=1)], ["hang"])
|
||||
task = asyncio.create_task(client.embed(["a"]))
|
||||
while not (await limiter.source_stats("e1")).inflight:
|
||||
await asyncio.sleep(0.01)
|
||||
task.cancel()
|
||||
with pytest.raises(asyncio.CancelledError):
|
||||
await task
|
||||
assert (await limiter.source_stats("e1")).inflight == 0
|
||||
|
||||
|
||||
class TestEmbedTelemetry:
|
||||
async def test_per_batch_rows_with_digest(self):
|
||||
rec = _MemoryRecorder()
|
||||
client, _ = _embed_client([_src()], ["ok", "ok"], batch_size=1, telemetry=rec)
|
||||
await client.embed(["hello", "x" * 5000], session_id="sess", parent_call_id="pc")
|
||||
assert len(rec.rows) == 2 # 每批一行
|
||||
row = rec.rows[0]
|
||||
assert row["session_id"] == "sess" and row["parent_call_id"] == "pc"
|
||||
assert row["completion_tokens"] == 0
|
||||
assert row["response"] == "<vectors n=1 dim=1>" # 向量绝不入库
|
||||
assert len(rec.rows[1]["messages"]) < 1000 # 长文本截断后入库
|
||||
|
||||
|
||||
class TestEmbeddingSettings:
|
||||
_ENV = {
|
||||
"EMBED__QWEN__1__BASE_URL": "https://gw.example/v1",
|
||||
"EMBED__QWEN__1__API_KEY": "sk-a",
|
||||
"EMBED__QWEN__1__MODEL": "text-embedding-v3",
|
||||
"EMBED__QWEN__1__TIMEOUT_S": "60",
|
||||
"EMBED__RETRY__MAX_ATTEMPTS": "3",
|
||||
"EMBED__RETRY__BACKOFF_BASE_S": "1.0",
|
||||
"EMBED__RETRY__BACKOFF_MAX_S": "10.0",
|
||||
"EMBED__BREAKER__FAIL_THRESHOLD": "5",
|
||||
"EMBED__BREAKER__COOLDOWN_S": "60",
|
||||
"PGW_CACHE_BACKEND": "none",
|
||||
"PGW_TELEMETRY_BACKEND": "none",
|
||||
"EMBED__BATCH_SIZE": "64",
|
||||
}
|
||||
|
||||
def test_loads_scope_and_batch(self):
|
||||
s = EmbeddingSettings.from_env("EMBED", env=self._ENV)
|
||||
assert s.gateway.sources[0].model == "text-embedding-v3"
|
||||
assert s.batch_size == 64 and s.normalize is False and s.expected_dim is None
|
||||
|
||||
def test_batch_size_required_and_positive(self):
|
||||
env = {k: v for k, v in self._ENV.items() if k != "EMBED__BATCH_SIZE"}
|
||||
with pytest.raises(ValueError, match="BATCH_SIZE"):
|
||||
EmbeddingSettings.from_env("EMBED", env=env)
|
||||
with pytest.raises(ValueError, match="BATCH_SIZE"):
|
||||
EmbeddingSettings.from_env("EMBED", env={**self._ENV, "EMBED__BATCH_SIZE": "0"})
|
||||
|
||||
def test_optional_normalize_and_dim(self):
|
||||
env = {**self._ENV, "EMBED__NORMALIZE": "true", "EMBED__EXPECTED_DIM": "768"}
|
||||
s = EmbeddingSettings.from_env("EMBED", env=env)
|
||||
assert s.normalize is True and s.expected_dim == 768
|
||||
|
||||
def test_from_settings_assembles_client(self):
|
||||
s = EmbeddingSettings.from_env("EMBED", env=self._ENV)
|
||||
client = EmbeddingClient.from_settings(s)
|
||||
assert isinstance(client, EmbeddingClient)
|
||||
|
||||
Reference in New Issue
Block a user