"""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",
                )
            if result.usage_source == "unavailable":
                # 与 RetryMW 同口径: 用量不可得时按入场预扣量结算(设计 §3.2 #9)
                actual = source.effective_est_tokens()
            else:
                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:
                # 保守: 失败请求可能已被网关计费(CHS 同款);与入场预扣同源取值
                actual = source.effective_est_tokens()
            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:
            # M2.5 §3.1: 记成功但不计失败率窗口样本(坏结果/坏请求 ≠ 坏服务)
            await self._record_quietly(self._breaker.record_success(entry, count_attempt=False))
        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)
        # 三态合并优先级(解耦设计 §3.2 #10): 任一批不可得 → 整体不可得
        sources = {o.result.usage_source for o in outcomes}
        if "unavailable" in sources:
            merged_source = "unavailable"
        elif "estimated" in sources:
            merged_source = "estimated"
        else:
            merged_source = "measured"
        return EmbeddingResponse(
            vectors=vectors,
            dim=first.result.dim,
            model=first.source.model,
            provider=first.source.provider,
            prompt_tokens=prompt_tokens,
            usage_source=merged_source,
            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:
        """全批成本;任一批用量不可得则整体记 NULL(解耦设计 §3.2 #11)。

        逐批求和会把不可得的批当 0 计入,给出一个偏低却看似有效的金额——
        与"宁可算不出成本,也不算错成本"的不变式相悖。
        """
        if self._pricing is None:
            return None
        if any(o.result.usage_source == "unavailable" for o in outcomes):
            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]