"""慢更新动量生成（app/harness/momentum.py）单元测试。

覆盖:
- _categorize_pair 四分类 + 缺键 KeyError
- _format_comparison_pairs 分组排序 + 空列表
- run_slow_momentum 正常解析 + 解析失败保留 prev_guidance
"""

from __future__ import annotations

import json
from dataclasses import dataclass
from typing import TYPE_CHECKING, Any
from unittest.mock import AsyncMock

import pytest

from app.harness.momentum import (
    IMPROVED,
    PERSISTENT_FAIL,
    REGRESSED,
    STABLE_SUCCESS,
    _categorize_pair,
    _format_comparison_pairs,
    run_slow_momentum,
)

if TYPE_CHECKING:
    from pathlib import Path


# =========================================================================
# _categorize_pair
# =========================================================================


class TestCategorizePair:
    """_categorize_pair 四分类测试。"""

    def test_categorize_pair_all_four(self) -> None:
        """四种 correct_prev/correct_curr 组合应返回对应类别常量。"""
        assert _categorize_pair({"correct_prev": False, "correct_curr": True}) == IMPROVED
        assert _categorize_pair({"correct_prev": True, "correct_curr": False}) == REGRESSED
        assert _categorize_pair({"correct_prev": False, "correct_curr": False}) == PERSISTENT_FAIL
        assert _categorize_pair({"correct_prev": True, "correct_curr": True}) == STABLE_SUCCESS

    def test_categorize_pair_truthy_values(self) -> None:
        """非布尔真值（int / str）也能正确分类。"""
        assert _categorize_pair({"correct_prev": 0, "correct_curr": 1}) == IMPROVED
        assert _categorize_pair({"correct_prev": "yes", "correct_curr": ""}) == REGRESSED

    def test_categorize_pair_missing_key(self) -> None:
        """缺 correct_prev 或 correct_curr 键时抛 KeyError。"""
        with pytest.raises(KeyError):
            _categorize_pair({"correct_prev": True})
        with pytest.raises(KeyError):
            _categorize_pair({"correct_curr": False})
        with pytest.raises(KeyError):
            _categorize_pair({})


# =========================================================================
# _format_comparison_pairs
# =========================================================================


class TestFormatComparisonPairs:
    """_format_comparison_pairs 分组排序测试。"""

    def test_format_comparison_pairs_empty(self) -> None:
        """空列表返回占位说明。"""
        result = _format_comparison_pairs([])
        assert "无可用" in result

    def test_format_comparison_pairs_order(self) -> None:
        """REGRESSED 标题应出现在 IMPROVED 标题之前（伤害信号优先）。"""
        pairs = [
            {
                "question": "Q1",
                "prev_prediction": "A",
                "curr_prediction": "B",
                "correct_prev": False,
                "correct_curr": True,
            },
            {
                "question": "Q2",
                "prev_prediction": "C",
                "curr_prediction": "D",
                "correct_prev": True,
                "correct_curr": False,
            },
        ]
        result = _format_comparison_pairs(pairs)
        regressed_pos = result.index("回退")
        improved_pos = result.index("改善")
        assert regressed_pos < improved_pos, "REGRESSED 应排在 IMPROVED 之前"

    def test_format_comparison_pairs_all_categories(self) -> None:
        """四种类别的 pair 都能被正确分组。"""
        pairs = [
            {"question": "Q1", "correct_prev": False, "correct_curr": True},
            {"question": "Q2", "correct_prev": True, "correct_curr": False},
            {"question": "Q3", "correct_prev": False, "correct_curr": False},
            {"question": "Q4", "correct_prev": True, "correct_curr": True},
        ]
        result = _format_comparison_pairs(pairs)
        assert "固定样本总数：4" in result
        # 每个类别都应标注 1 题
        assert "1 题" in result

    def test_format_comparison_pairs_missing_key(self) -> None:
        """pair 缺键时 KeyError 不被吞。"""
        with pytest.raises(KeyError):
            _format_comparison_pairs([{"question": "Q1"}])


# =========================================================================
# run_slow_momentum
# =========================================================================


def _make_mock_llm(response_content: str) -> Any:
    """构造一个返回指定 content 的 mock LLMProvider。"""

    @dataclass(frozen=True)
    class _FakeResponse:
        content: str
        thinking: str = ""
        model: str = "mock"
        provider: str = "mock"
        prompt_tokens: int = 0
        completion_tokens: int = 0
        latency_ms: int = 0
        ttft_ms: float | None = None
        max_inter_token_ms: float | None = None
        cache_hit: bool = False
        call_id: str = "test-call-id"

    mock_llm = AsyncMock()
    mock_llm.chat.return_value = _FakeResponse(content=response_content)
    return mock_llm


@pytest.mark.asyncio
async def test_run_slow_momentum_basic(tmp_path: Path) -> None:
    """正常解析时返回新的动量指导文本。"""
    # 准备 prompt 文件
    prompt_file = tmp_path / "slow_momentum.md"
    prompt_file.write_text("你是一个慢更新动量裁判。", encoding="utf-8")

    new_guidance_text = "新一轮的动量指导内容"
    llm_response = json.dumps({"slow_update_content": new_guidance_text}, ensure_ascii=False)
    mock_llm = _make_mock_llm(llm_response)

    result = await run_slow_momentum(
        llm=mock_llm,
        diagnose_prompts_dir=tmp_path,
        skill_content="当前 skill 正文",
        prev_skill="上一版 skill 正文",
        prev_guidance="旧的动量指导",
        comparison_pairs=[
            {
                "question": "Q1",
                "prev_prediction": "A",
                "curr_prediction": "B",
                "correct_prev": False,
                "correct_curr": True,
            }
        ],
    )
    assert result == new_guidance_text
    mock_llm.chat.assert_awaited_once()


@pytest.mark.asyncio
async def test_run_slow_momentum_parse_failure(tmp_path: Path) -> None:
    """LLM 返回无法解析的内容时保留 prev_guidance。"""
    prompt_file = tmp_path / "slow_momentum.md"
    prompt_file.write_text("你是一个慢更新动量裁判。", encoding="utf-8")

    mock_llm = _make_mock_llm("这不是 JSON，无法解析")
    prev_guidance = "应该被保留的旧动量指导"

    result = await run_slow_momentum(
        llm=mock_llm,
        diagnose_prompts_dir=tmp_path,
        skill_content="当前 skill",
        prev_skill="上一版 skill",
        prev_guidance=prev_guidance,
        comparison_pairs=[
            {
                "question": "Q1",
                "prev_prediction": "A",
                "curr_prediction": "B",
                "correct_prev": True,
                "correct_curr": True,
            }
        ],
    )
    assert result == prev_guidance


@pytest.mark.asyncio
async def test_run_slow_momentum_missing_field(tmp_path: Path) -> None:
    """LLM 返回合法 JSON 但缺少 slow_update_content 字段时保留 prev_guidance。"""
    prompt_file = tmp_path / "slow_momentum.md"
    prompt_file.write_text("你是一个慢更新动量裁判。", encoding="utf-8")

    llm_response = json.dumps({"other_field": "无关内容"}, ensure_ascii=False)
    mock_llm = _make_mock_llm(llm_response)
    prev_guidance = "应该被保留的旧动量指导"

    result = await run_slow_momentum(
        llm=mock_llm,
        diagnose_prompts_dir=tmp_path,
        skill_content="当前 skill",
        prev_skill="上一版 skill",
        prev_guidance=prev_guidance,
        comparison_pairs=[],
    )
    assert result == prev_guidance


@pytest.mark.asyncio
async def test_run_slow_momentum_keyerror_not_swallowed(tmp_path: Path) -> None:
    """comparison_pairs 缺键时 KeyError 不被 ValueError 吞掉。"""
    prompt_file = tmp_path / "slow_momentum.md"
    prompt_file.write_text("你是一个慢更新动量裁判。", encoding="utf-8")

    mock_llm = _make_mock_llm('{"slow_update_content": "ok"}')

    with pytest.raises(KeyError):
        await run_slow_momentum(
            llm=mock_llm,
            diagnose_prompts_dir=tmp_path,
            skill_content="当前 skill",
            prev_skill="上一版 skill",
            prev_guidance="旧指导",
            comparison_pairs=[{"question": "Q1"}],  # 缺 correct_prev/correct_curr
        )


@pytest.mark.asyncio
async def test_run_slow_momentum_fenced_json(tmp_path: Path) -> None:
    """LLM 返回 fenced code block 中的 JSON 也能正确解析。"""
    prompt_file = tmp_path / "slow_momentum.md"
    prompt_file.write_text("你是一个慢更新动量裁判。", encoding="utf-8")

    new_guidance = "从 fenced block 中提取的指导"
    llm_response = f'```json\n{{"slow_update_content": "{new_guidance}"}}\n```'
    mock_llm = _make_mock_llm(llm_response)

    result = await run_slow_momentum(
        llm=mock_llm,
        diagnose_prompts_dir=tmp_path,
        skill_content="当前 skill",
        prev_skill="上一版 skill",
        prev_guidance="旧指导",
        comparison_pairs=[],
    )
    assert result == new_guidance