"""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']}",
            ],
        )