"""OpenAI 兼容 transport(D2 默认): 手写 httpx + SSE 解析 + 错误翻译。

SSE 纯函数移植 VT `adapters/llm.py:51-124`;错误翻译移植 CHS
`app/providers/invokers.py:127-227`。职责只到"一次原始调用"——重试/限流/
缓存归中间件。看门狗活性口径: content 与 reasoning_content 增量都作为流
元素产出,思考流天然刷新计时(CHS 迁移约束 R1)。
"""

from __future__ import annotations

import json
import re
import time
from typing import TYPE_CHECKING, Any

import httpx

from polygateway.errors import (
    RequestRejectedError,
    ResultInvalidError,
    SourceDeadError,
    TransientError,
)
from polygateway.providers import ProviderProfile, get_provider
from polygateway.streaming import StreamLivenessTimeout, stream_with_liveness_timeouts
from polygateway.types import EmbeddingTransportResult, SourceConfig, TransportResult

if TYPE_CHECKING:
    from collections.abc import AsyncIterator, Callable, Mapping

_THINK_PATTERN = re.compile(r"<think>(.*?)</think>", re.DOTALL)

# —— SSE 纯函数(VT llm.py 同款)——


def _sse_data_payload(raw: str) -> str | None:
    """提取 SSE data 行载荷;ping(: 开头)/空行/非 data 行返回 None 跳过。"""
    line = raw.strip()
    if not line or line.startswith(":") or not line.startswith("data:"):
        return None
    return line[len("data:") :].strip()


def _sse_delta(chunk: dict[str, Any], usage_sink: dict[str, Any]) -> tuple[bool, str] | None:
    """从 chunk 提取增量: (True, content) 或 (False, reasoning);usage 帧旁路进 sink。"""
    if chunk.get("usage"):
        usage_sink["usage"] = chunk["usage"]
    choices = chunk.get("choices") or []
    if not choices:
        return None
    delta = choices[0].get("delta") or {}
    content = delta.get("content")
    if content:
        return (True, content)
    reasoning = delta.get("reasoning_content")
    if reasoning:
        return (False, reasoning)
    return None


async def _iter_sse_deltas(
    lines: AsyncIterator[str], usage_sink: dict[str, Any]
) -> AsyncIterator[tuple[bool, str]]:
    """逐行解析 SSE 流;[DONE] 置 sink["done"];畸形 JSON 帧 → 瞬时错误(可重试)。"""
    async for raw in lines:
        data = _sse_data_payload(raw)
        if data is None:
            continue
        if data == "[DONE]":
            usage_sink["done"] = True
            return
        try:
            chunk = json.loads(data)
        except json.JSONDecodeError as exc:
            raise TransientError(
                f"SSE 帧畸形(malformed_json): {data[:80]!r}", operation="chat"
            ) from exc
        delta = _sse_delta(chunk, usage_sink)
        if delta is not None:
            yield delta


# —— 错误翻译(CHS invokers.py 同款)——


def _parse_retry_after(raw: str | None) -> float | None:
    """解析 Retry-After 头;仅支持秒数形态,HTTP-date 返回 None(CHS 同款)。"""
    if raw is None:
        return None
    try:
        seconds = float(raw.strip())
    except ValueError:
        return None
    return seconds if seconds > 0 else None


def _translate_429(source: SourceConfig, body_text: str, headers: Mapping[str, str]) -> Exception:
    try:
        err_type = json.loads(body_text).get("error", {}).get("type", "")
    except (json.JSONDecodeError, AttributeError):
        err_type = ""
    if err_type == "insufficient_quota":
        return SourceDeadError(
            f"{source.name} 配额耗尽(insufficient_quota)",
            source_name=source.name,
            status_code=429,
            operation="chat",
        )
    return TransientError(
        f"{source.name} 限速: 429",
        retry_after_s=_parse_retry_after(headers.get("retry-after")),
        source_name=source.name,
        status_code=429,
        operation="chat",
    )


def _status_to_error(
    source: SourceConfig, status: int, body_text: str, headers: Mapping[str, str]
) -> Exception:
    ctx: dict[str, Any] = {"source_name": source.name, "status_code": status, "operation": "chat"}
    if status in (401, 403):
        return SourceDeadError(f"{source.name} 凭据失效/欠费: {status}", **ctx)
    if status == 400:
        return RequestRejectedError(f"{source.name} 请求被拒: 400", **ctx)
    if status == 429:
        return _translate_429(source, body_text, headers)
    if status >= 500:
        return TransientError(f"{source.name} 瞬时错误: {status}", **ctx)
    return RequestRejectedError(f"{source.name} 客户端错误: {status}", **ctx)


def _strip_think(content: str) -> tuple[str, str]:
    """剥离 <think> 标签(qwen 系),返回 (正文, 思考流)。VT llm.py:147-164 同款。"""
    match = _THINK_PATTERN.search(content)
    if match is None:
        return content, ""
    return _THINK_PATTERN.sub("", content).strip(), match.group(1).strip()


def _resolve_usage(usage: dict[str, Any], source: SourceConfig) -> tuple[int, int, str]:
    """usage 帧读取;缺失/非法按 est_tokens 保守兜底并标 estimated(CHS invokers.py:241)。"""
    prompt, completion = usage.get("prompt_tokens"), usage.get("completion_tokens")
    if isinstance(prompt, int) and isinstance(completion, int) and prompt + completion > 0:
        return prompt, completion, "measured"
    return 0, source.est_tokens, "estimated"


def _extract_vectors(
    data: dict[str, Any], source: SourceConfig, expected_count: int, ctx: dict[str, Any]
) -> list[list[float]]:
    """按 data[].index 重排提取向量并校验条数/维度一致性。"""
    try:
        vectors = [
            [float(x) for x in item["embedding"]]
            for item in sorted(data["data"], key=lambda it: int(it["index"]))
        ]
    except (KeyError, TypeError, ValueError) as exc:
        raise ResultInvalidError(f"{source.name} embedding 响应形态异常: {exc}", **ctx) from exc
    if len(vectors) != expected_count:
        raise ResultInvalidError(
            f"{source.name} 返回 {len(vectors)} 条向量,与输入 {expected_count} 条不符", **ctx
        )
    if len({len(v) for v in vectors}) != 1 or not vectors[0]:
        raise ResultInvalidError(
            f"{source.name} 向量维度异常: {sorted({len(v) for v in vectors})}", **ctx
        )
    return vectors


def _resolve_embedding_usage(data: dict[str, Any], source: SourceConfig) -> tuple[int, str]:
    """usage 读取;缺失/非法按 est_tokens 保守兜底并标 estimated(与 chat 同口径)。"""
    prompt = (data.get("usage") or {}).get("prompt_tokens")
    if isinstance(prompt, int) and prompt > 0:
        return prompt, "measured"
    return source.est_tokens, "estimated"


def _parse_embedding_payload(
    resp: httpx.Response, source: SourceConfig, expected_count: int
) -> EmbeddingTransportResult:
    """解析 /embeddings 响应;一切形态异常归 ResultInvalidError(坏结果≠坏服务)。"""
    ctx: dict[str, Any] = {"source_name": source.name, "operation": "embedding"}
    try:
        data = resp.json()
    except json.JSONDecodeError as exc:
        raise ResultInvalidError(f"{source.name} embedding 响应非 JSON: {exc}", **ctx) from exc
    vectors = _extract_vectors(data, source, expected_count, ctx)
    prompt_tokens, usage_source = _resolve_embedding_usage(data, source)
    return EmbeddingTransportResult(
        vectors=vectors,
        dim=len(vectors[0]),
        prompt_tokens=prompt_tokens,
        usage_source=usage_source,
        raw={"id": data.get("id")},
    )


def _default_client_factory(source: SourceConfig) -> httpx.AsyncClient:
    return httpx.AsyncClient(
        headers={"Authorization": f"Bearer {source.api_key}"},
        timeout=httpx.Timeout(source.timeout_s),
        trust_env=source.trust_env,
    )


class OpenAICompatTransport:
    """默认 transport: 每源一个预配 httpx client,懒创建,aclose 统一释放。"""

    def __init__(
        self,
        *,
        registry: Mapping[str, ProviderProfile] | None = None,
        client_factory: Callable[[SourceConfig], httpx.AsyncClient] | None = None,
    ) -> None:
        self._registry = registry
        self._client_factory = client_factory or _default_client_factory
        self._clients: dict[str, httpx.AsyncClient] = {}

    def _client_for(self, source: SourceConfig) -> httpx.AsyncClient:
        client = self._clients.get(source.name)
        if client is None:
            client = self._client_factory(source)
            self._clients[source.name] = client
        return client

    def _build_payload(
        self,
        *,
        messages: list[dict[str, Any]],
        source: SourceConfig,
        profile: ProviderProfile,
        stream: bool,
        overlay: dict[str, Any],
    ) -> dict[str, Any]:
        payload: dict[str, Any] = {"model": source.model, "messages": messages, "stream": stream}
        if stream:
            payload["stream_options"] = {"include_usage": True}  # 强制 usage 帧(三项目同款)
        if source.enable_thinking is True:
            payload.update(profile.thinking_on)
        elif source.enable_thinking is False:
            payload.update(profile.thinking_off)
        payload.update(overlay)
        return payload

    async def complete(
        self,
        *,
        messages: list[dict[str, Any]],
        source: SourceConfig,
        stream: bool,
        overlay: dict[str, Any],
        call_id: str,
    ) -> TransportResult:
        """一次原始调用;HTTP/线路/流式异常按 ARCH §6.2 翻译为领域错误。"""
        profile = get_provider(source.provider, registry=self._registry)
        payload = self._build_payload(
            messages=messages, source=source, profile=profile, stream=stream, overlay=overlay
        )
        url = source.base_url.rstrip("/") + "/chat/completions"
        client = self._client_for(source)
        ctx: dict[str, Any] = {"source_name": source.name, "operation": "chat"}
        try:
            if stream:
                return await self._complete_stream(client, url, payload, source, profile)
            return await self._complete_once(client, url, payload, source, profile)
        except StreamLivenessTimeout as exc:
            raise TransientError(f"{source.name} 流活性超时({exc.kind})", **ctx) from exc
        except httpx.TimeoutException as exc:
            raise TransientError(f"{source.name} 超时: {exc}", **ctx) from exc
        except httpx.TransportError as exc:
            # VT 宽集: 覆盖断连/协议错误/读写失败(设计 §9 行 8)
            raise TransientError(f"{source.name} 网络错误: {exc}", **ctx) from exc

    async def embed(
        self, *, texts: list[str], source: SourceConfig, call_id: str
    ) -> EmbeddingTransportResult:
        """一次原始 embedding 调用(M2 §7): POST /embeddings,错误翻译同 chat。

        响应按 data[].index 重排保序(GovDoc embedding.py:149 / VT :164 同款);
        空 data/长度不符/维度不一致 → ResultInvalidError(坏结果不熔断)。
        """
        if not texts:
            raise ValueError("texts 不能为空(空输入由 EmbeddingClient 短路)")
        url = source.base_url.rstrip("/") + "/embeddings"
        client = self._client_for(source)
        ctx: dict[str, Any] = {"source_name": source.name, "operation": "embedding"}
        try:
            resp = await client.post(url, json={"model": source.model, "input": texts})
        except httpx.TimeoutException as exc:
            raise TransientError(f"{source.name} 超时: {exc}", **ctx) from exc
        except httpx.TransportError as exc:
            raise TransientError(f"{source.name} 网络错误: {exc}", **ctx) from exc
        if resp.status_code != 200:
            raise _status_to_error(source, resp.status_code, resp.text, resp.headers)
        return _parse_embedding_payload(resp, source, len(texts))

    async def _complete_stream(
        self,
        client: httpx.AsyncClient,
        url: str,
        payload: dict[str, Any],
        source: SourceConfig,
        profile: ProviderProfile,
    ) -> TransportResult:
        started = time.monotonic()
        async with client.stream("POST", url, json=payload) as resp:
            if resp.status_code != 200:
                body = (await resp.aread()).decode("utf-8", errors="replace")
                raise _status_to_error(source, resp.status_code, body, resp.headers)
            sink: dict[str, Any] = {}
            guarded = stream_with_liveness_timeouts(
                _iter_sse_deltas(resp.aiter_lines(), sink),
                ttft_s=source.ttft_timeout_s or source.timeout_s,
                inter_token_s=source.inter_token_timeout_s or source.timeout_s,
                total_s=source.timeout_s,
            )
            content_parts: list[str] = []
            thinking_parts: list[str] = []
            ttft_ms: float | None = None
            last = started
            max_gap = 0.0
            async for is_content, text in guarded:
                now = time.monotonic()
                if ttft_ms is None:
                    ttft_ms = (now - started) * 1000
                else:
                    max_gap = max(max_gap, (now - last) * 1000)
                last = now
                (content_parts if is_content else thinking_parts).append(text)
        salvaged = self._check_done(sink, content_parts, thinking_parts, source)
        content, thinking = self._finalize_text(content_parts, thinking_parts, profile)
        self._reject_empty_completion(content, source)
        prompt, completion, usage_source = _resolve_usage(sink.get("usage") or {}, source)
        if salvaged:
            usage_source = "estimated"  # 打捞路径强制 estimated(设计 §6)
        return TransportResult(
            content=content,
            thinking=thinking,
            prompt_tokens=prompt,
            completion_tokens=completion,
            usage_source=usage_source,
            ttft_ms=ttft_ms,
            max_inter_token_ms=(max_gap if ttft_ms is not None else None),
            raw={"usage": sink.get("usage")},
        )

    def _check_done(
        self,
        sink: dict[str, Any],
        content_parts: list[str],
        thinking_parts: list[str],
        source: SourceConfig,
    ) -> bool:
        """缺 [DONE] 语义(设计 §6): 零内容恒 retry;有内容按 missing_done 策略。"""
        if sink.get("done"):
            return False
        ctx: dict[str, Any] = {"source_name": source.name, "operation": "chat"}
        if not content_parts and not thinking_parts:
            raise TransientError(f"{source.name} SSE early_eof: 零内容断流", **ctx)
        if source.missing_done == "retry":
            raise TransientError(f"{source.name} SSE missing_done: 截断且无 [DONE]", **ctx)
        return True

    def _reject_empty_completion(self, content: str, source: SourceConfig) -> None:
        """空补全 → 瞬时错误(2026-07-20 人类裁决,M1 验证发现)。

        服务 200 且流程完整([DONE]/usage 正常)但 content 为空——MiniMax 等
        网关的间歇异常形态。视为服务抖动: 退避重试/换源,**绝不缓存空响应**;
        承 CHS "VLM 零 content"归瞬时的先例(invokers.py:309)。
        """
        if not content.strip():
            raise TransientError(
                f"{source.name} 空补全(empty_completion): 流程完整但零内容",
                source_name=source.name,
                operation="chat",
            )

    def _finalize_text(
        self, content_parts: list[str], thinking_parts: list[str], profile: ProviderProfile
    ) -> tuple[str, str]:
        content = "".join(content_parts)
        thinking = "".join(thinking_parts)
        if profile.strip_think_tags and "<think>" in content:
            content, tag_thinking = _strip_think(content)
            if tag_thinking:
                thinking = tag_thinking
        return content, thinking

    async def _complete_once(
        self,
        client: httpx.AsyncClient,
        url: str,
        payload: dict[str, Any],
        source: SourceConfig,
        profile: ProviderProfile,
    ) -> TransportResult:
        """非流式快路径(三项目均无,库新增): 单 JSON 响应,仅 total 超时。"""
        resp = await client.post(url, json=payload)
        if resp.status_code != 200:
            raise _status_to_error(source, resp.status_code, resp.text, resp.headers)
        try:
            body = resp.json()
        except json.JSONDecodeError as exc:
            raise TransientError(
                f"{source.name} 非流式响应非法 JSON", source_name=source.name, operation="chat"
            ) from exc
        choices = body.get("choices") or []
        if not choices:
            raise TransientError(
                f"{source.name} 响应缺 choices", source_name=source.name, operation="chat"
            )
        message = choices[0].get("message") or {}
        content, thinking = self._finalize_text(
            [message.get("content") or ""], [message.get("reasoning_content") or ""], profile
        )
        self._reject_empty_completion(content, source)
        prompt, completion, usage_source = _resolve_usage(body.get("usage") or {}, source)
        return TransportResult(
            content=content,
            thinking=thinking,
            prompt_tokens=prompt,
            completion_tokens=completion,
            usage_source=usage_source,
            ttft_ms=None,
            max_inter_token_ms=None,
            raw={"usage": body.get("usage")},
        )

    async def aclose(self) -> None:
        """幂等关闭全部源 client。"""
        clients, self._clients = self._clients, {}
        for client in clients.values():
            await client.aclose()