"""app/search/summarizer 模块的单元测试。

覆盖 anchor 工具函数（纯函数）和 summarize_* 异步函数（FakeLLMProvider mock）。
"""

from __future__ import annotations

from dataclasses import dataclass
from typing import TYPE_CHECKING, Any

import pytest

if TYPE_CHECKING:
    from pathlib import Path

from app.search.summarizer import (
    _expand_anchor_ids,
    assemble_anchored_output,
    check_anchors,
    summarize_children,
    summarize_node,
    summarize_nodes_batch,
)

# ── Fake LLM 基础设施 ──────────────────────────────────────────────


@dataclass
class FakeLLMResponse:
    """FakeLLMProvider 返回的响应对象。"""

    content: str
    thinking: str = ""
    model: str = "fake"
    provider: str = "fake"
    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 = "fake-call"


class FakeLLMProvider:
    """按顺序返回预设响应的 LLMProvider 假实现。"""

    def __init__(self, responses: list[str]) -> None:
        self._responses = iter(responses)

    async def chat(
        self,
        messages: list[dict[str, Any]],
        *,
        session_id: str | None = None,
        parent_call_id: str | None = None,
    ) -> FakeLLMResponse:
        """返回下一个预设响应。"""
        return FakeLLMResponse(content=next(self._responses))


class FailingLLMProvider:
    """始终抛出异常的 LLMProvider 假实现。"""

    def __init__(self, error_msg: str = "LLM 调用失败") -> None:
        self._error_msg = error_msg

    async def chat(
        self,
        messages: list[dict[str, Any]],
        *,
        session_id: str | None = None,
        parent_call_id: str | None = None,
    ) -> FakeLLMResponse:
        """始终抛出异常。"""
        raise RuntimeError(self._error_msg)


class FailOnNthLLMProvider:
    """第 N 次调用抛异常，其余正常返回的 LLMProvider。"""

    def __init__(self, responses: list[str], fail_on: int) -> None:
        self._responses = list(responses)
        self._fail_on = fail_on
        self._call_count = 0

    async def chat(
        self,
        messages: list[dict[str, Any]],
        *,
        session_id: str | None = None,
        parent_call_id: str | None = None,
    ) -> FakeLLMResponse:
        """第 fail_on 次调用抛异常。"""
        self._call_count += 1
        if self._call_count == self._fail_on:
            raise RuntimeError(f"第 {self._fail_on} 次调用失败")
        idx = self._call_count - 1
        if self._call_count > self._fail_on:
            idx -= 1
        return FakeLLMResponse(content=self._responses[idx])


# ── Prompt 文件 fixture ──────────────────────────────────────────────


@pytest.fixture()
def prompts_dir(tmp_path: Path) -> Path:
    """创建包含最小化 prompt 文件的临时目录。"""
    prompts = {
        "view_node_extract.md": "提取与问题相关的信息。",
        "view_node_verify.md": "核实摘要准确性。",
        "view_node_children_extract.md": "标注子节点相关性。",
        "view_node_children_verify.md": "核实子节点标注。",
        "search_similar_extract.md": "提取搜索结果摘要。",
        "search_similar_verify.md": "核实搜索结果摘要。",
    }
    for filename, content in prompts.items():
        (tmp_path / filename).write_text(content, encoding="utf-8")
    return tmp_path


# ══════════════════════════════════════════════════════════════════════
# Part A: Anchor 工具函数测试（纯函数，无需 mock）
# ══════════════════════════════════════════════════════════════════════


class TestExpandAnchorIds:
    """_expand_anchor_ids 展开范围语法。"""

    def test_single_ids(self) -> None:
        """单个 id 不展开。"""
        assert _expand_anchor_ids("s1") == ["s1"]
        assert _expand_anchor_ids("c2") == ["c2"]

    def test_comma_separated(self) -> None:
        """逗号分隔的多个 id。"""
        assert _expand_anchor_ids("s1,c2,s5") == ["s1", "c2", "s5"]

    def test_range_expansion(self) -> None:
        """范围语法 s3-s5 展开为 [s3, s4, s5]。"""
        assert _expand_anchor_ids("s3-s5") == ["s3", "s4", "s5"]

    def test_range_short_form(self) -> None:
        """短范围语法 s3-5（省略第二个前缀）也应展开。"""
        assert _expand_anchor_ids("s3-5") == ["s3", "s4", "s5"]

    def test_range_with_c_prefix(self) -> None:
        """c 前缀范围展开。"""
        assert _expand_anchor_ids("c1-c3") == ["c1", "c2", "c3"]

    def test_mixed_ids_and_ranges(self) -> None:
        """混合单 id 和范围。"""
        result = _expand_anchor_ids("s1,c2-c4,s10")
        assert result == ["s1", "c2", "c3", "c4", "s10"]

    def test_cross_prefix_range_kept_as_token(self) -> None:
        """跨前缀范围（c3-s5）保留原 token。"""
        result = _expand_anchor_ids("c3-s5")
        assert result == ["c3-s5"]

    def test_reversed_range_kept_as_token(self) -> None:
        """起点>终点的范围保留原 token。"""
        result = _expand_anchor_ids("s5-s3")
        assert result == ["s5-s3"]

    def test_explosion_guard(self) -> None:
        """超过 50 条展开上限的范围保留原 token。"""
        result = _expand_anchor_ids("s1-s100")
        assert result == ["s1-s100"]

    def test_fullwidth_comma(self) -> None:
        """全角逗号分隔。"""
        result = _expand_anchor_ids("s1，s2")
        assert result == ["s1", "s2"]


class TestCheckAnchors:
    """check_anchors 校验行号引注。"""

    def test_legal_anchors_preserved(self) -> None:
        """合法锚保留不变。"""
        anchor_map = {"s1": "第一行", "s2": "第二行", "c1": "字幕一"}
        summary = "[相关信息]\n- 关键发现(s1)\n- 另一个发现(c1)"
        cleaned, stats = check_anchors(summary, anchor_map)
        assert "(s1)" in cleaned
        assert "(c1)" in cleaned
        assert stats["n_illegal"] == 0
        assert stats["n_assertions"] == 2
        assert stats["n_anchored"] == 2

    def test_illegal_anchors_removed(self) -> None:
        """非法锚被删除，断言文本保留。"""
        anchor_map = {"s1": "第一行"}
        summary = "[相关信息]\n- 关键发现(s99)"
        cleaned, stats = check_anchors(summary, anchor_map)
        assert "(s99)" not in cleaned
        assert "关键发现" in cleaned
        assert stats["n_illegal"] == 1
        assert stats["n_assertions"] == 1
        assert stats["n_anchored"] == 0

    def test_range_expansion_in_check(self) -> None:
        """范围语法在 check_anchors 中展开并校验。"""
        anchor_map = {"s1": "行1", "s2": "行2", "s3": "行3"}
        summary = "[相关信息]\n- 发现(s1-s3)"
        cleaned, stats = check_anchors(summary, anchor_map)
        assert "(s1,s2,s3)" in cleaned
        assert stats["n_illegal"] == 0

    def test_partial_legal_range(self) -> None:
        """范围中部分合法：仅保留合法子集。"""
        anchor_map = {"s1": "行1", "s2": "行2"}
        summary = "[相关信息]\n- 发现(s1-s4)"
        cleaned, stats = check_anchors(summary, anchor_map)
        assert "(s1,s2)" in cleaned
        assert stats["n_illegal"] == 2  # s3, s4 非法

    def test_no_info_statement_not_counted(self) -> None:
        """声明句"未包含…相关…信息"不计入 n_assertions。"""
        anchor_map = {"s1": "行1"}
        summary = (
            "[相关信息]\n"
            "- 该节点未包含与问题直接相关的信息\n"
            "- 关键发现(s1)"
        )
        _, stats = check_anchors(summary, anchor_map)
        assert stats["n_assertions"] == 1  # 声明句不计
        assert stats["n_anchored"] == 1

    def test_no_relevant_section(self) -> None:
        """无 [相关信息] 段落时，只清理锚，统计为零。"""
        anchor_map = {"s1": "行1"}
        summary = "一些分析文本(s1)(s99)"
        cleaned, stats = check_anchors(summary, anchor_map)
        assert "(s1)" in cleaned
        assert "(s99)" not in cleaned
        assert stats["n_assertions"] == 0
        assert stats["n_anchored"] == 0
        assert stats["n_illegal"] == 1

    def test_fullwidth_brackets(self) -> None:
        """全角括号也应被识别。"""
        anchor_map = {"s1": "行1"}
        summary = "[相关信息]\n- 发现（s1）"
        cleaned, stats = check_anchors(summary, anchor_map)
        assert stats["n_anchored"] == 1

    def test_all_illegal_group_removed(self) -> None:
        """组内全非法则整组删除。"""
        anchor_map = {"s1": "行1"}
        summary = "[相关信息]\n- 发现(s99,s100)"
        cleaned, stats = check_anchors(summary, anchor_map)
        assert "(s99" not in cleaned
        assert "(s100" not in cleaned
        assert stats["n_illegal"] == 2


class TestAssembleAnchoredOutput:
    """assemble_anchored_output 三种模式 + 封顶逻辑。"""

    def test_ids_mode_no_expansion(self) -> None:
        """ids 模式：不展开引文，原样输出。"""
        anchor_map = {"s1": "行1", "s2": "行2"}
        summary = "关键发现(s1)"
        result, stats = assemble_anchored_output(summary, anchor_map, "ids")
        assert result == summary
        assert stats["n_expanded"] == 0

    def test_ids_expand_mode(self) -> None:
        """ids_expand 模式：保留行号 + 附加引文段。"""
        anchor_map = {"s1": "第一行内容", "s2": "第二行内容"}
        summary = "关键发现(s1,s2)"
        result, stats = assemble_anchored_output(
            summary, anchor_map, "ids_expand"
        )
        assert "(s1,s2)" in result
        assert "[引文]" in result
        assert 's1: "第一行内容"' in result
        assert 's2: "第二行内容"' in result
        assert stats["n_expanded"] == 2

    def test_expand_only_mode_strips_anchors(self) -> None:
        """expand_only 模式：剥除行号 + 附加引文段。"""
        anchor_map = {"s1": "第一行内容"}
        summary = "关键发现(s1)"
        result, stats = assemble_anchored_output(
            summary, anchor_map, "expand_only"
        )
        assert "(s1)" not in result
        assert "[引文]" in result
        assert 's1: "第一行内容"' in result
        assert stats["n_expanded"] == 1

    def test_max_items_cap(self) -> None:
        """超过 5 条引文的封顶。"""
        anchor_map = {f"s{i}": f"行{i}" for i in range(1, 10)}
        refs = ",".join(f"s{i}" for i in range(1, 10))
        summary = f"发现({refs})"
        result, stats = assemble_anchored_output(
            summary, anchor_map, "ids_expand"
        )
        assert stats["n_expanded"] == 5

    def test_max_chars_cap(self) -> None:
        """总字符超过 800 时截断。"""
        anchor_map = {
            f"s{i}": "A" * 300 for i in range(1, 6)
        }
        refs = ",".join(f"s{i}" for i in range(1, 6))
        summary = f"发现({refs})"
        result, stats = assemble_anchored_output(
            summary, anchor_map, "ids_expand"
        )
        # 300 字符原文 + 前缀 ≈ 310+ 每条，800 / 310 ≈ 2 条
        assert stats["n_expanded"] < 5

    def test_line_cap_truncation(self) -> None:
        """单行超 200 字符截断并标记 n_trunc。"""
        anchor_map = {"s1": "A" * 250}
        summary = "发现(s1)"
        result, stats = assemble_anchored_output(
            summary, anchor_map, "ids_expand"
        )
        assert stats["n_trunc"] == 1
        assert "…" in result

    def test_invalid_mode_raises(self) -> None:
        """无效模式应抛出 AssertionError。"""
        with pytest.raises(AssertionError, match="未知装配形态"):
            assemble_anchored_output("text", {}, "bad_mode")


# ══════════════════════════════════════════════════════════════════════
# Part B: summarize_* 异步函数测试（FakeLLMProvider mock）
# ══════════════════════════════════════════════════════════════════════


class TestSummarizeNode:
    """summarize_node 两轮摘要。"""

    @pytest.mark.asyncio()
    async def test_normal_two_round(self, prompts_dir: Path) -> None:
        """正常两轮：提取 + 核实。"""
        llm = FakeLLMProvider(["提取结果摘要", "核实通过"])
        result = await summarize_node(
            llm,
            "视频片段内容",
            "这个视频讲了什么？",
            prompts_dir,
            anchor_map=None,
            assemble_mode="ids",
        )
        assert "[内容摘要] 提取结果摘要" in result
        assert "[核实] 核实通过" in result

    @pytest.mark.asyncio()
    async def test_extract_failure(self, prompts_dir: Path) -> None:
        """提取轮失败返回错误信息。"""
        llm = FailingLLMProvider("网络超时")
        result = await summarize_node(
            llm,
            "视频片段内容",
            "问题",
            prompts_dir,
            anchor_map=None,
            assemble_mode="ids",
        )
        assert "[摘要错误]" in result
        assert "网络超时" in result

    @pytest.mark.asyncio()
    async def test_verify_failure_degrades(self, prompts_dir: Path) -> None:
        """核实轮失败降级为"跳过"。"""
        llm = FailOnNthLLMProvider(["提取结果"], fail_on=2)
        result = await summarize_node(
            llm,
            "视频片段内容",
            "问题",
            prompts_dir,
            anchor_map=None,
            assemble_mode="ids",
        )
        assert "[内容摘要] 提取结果" in result
        assert "跳过（调用失败）" in result

    @pytest.mark.asyncio()
    async def test_anchor_mode(self, prompts_dir: Path) -> None:
        """锚模式：check_anchors + assemble。"""
        anchor_map = {"s1": "第一行", "s2": "第二行"}
        llm = FakeLLMProvider([
            "[相关信息]\n- 关键发现(s1)\n- 补充(s2)",
            "核实通过",
        ])
        result = await summarize_node(
            llm,
            "带行号的内容",
            "问题",
            prompts_dir,
            anchor_map=anchor_map,
            assemble_mode="ids_expand",
        )
        assert "[内容摘要]" in result
        assert "[核实] 核实通过" in result
        assert "[引文]" in result

    @pytest.mark.asyncio()
    async def test_anchor_mode_with_stats_sink(self, prompts_dir: Path) -> None:
        """锚模式 stats_sink 回调接收完整统计。"""
        anchor_map = {"s1": "第一行"}
        collected: list[dict] = []
        llm = FakeLLMProvider([
            "[相关信息]\n- 关键发现(s1)",
            "核实通过",
        ])
        await summarize_node(
            llm,
            "内容",
            "问题",
            prompts_dir,
            anchor_map=anchor_map,
            assemble_mode="ids_expand",
            stats_sink=collected.append,
        )
        assert len(collected) == 1
        s = collected[0]
        assert "n_assertions" in s
        assert "n_anchored" in s
        assert "n_expanded" in s
        assert "output_chars" in s
        assert "pre_assembly" in s
        assert "anchor_map" in s

    @pytest.mark.asyncio()
    async def test_session_id_forwarded(self, prompts_dir: Path) -> None:
        """session_id 和 parent_call_id 应透传给 LLM。"""
        received_kwargs: list[dict] = []

        class CaptureLLM:
            """捕获 kwargs 的 LLM。"""

            async def chat(self, messages: list, **kwargs: Any) -> FakeLLMResponse:
                received_kwargs.append(kwargs)
                return FakeLLMResponse(content="ok")

        llm = CaptureLLM()
        await summarize_node(
            llm,
            "内容",
            "问题",
            prompts_dir,
            anchor_map=None,
            assemble_mode="ids",
            session_id="sess-1",
            parent_call_id="call-0",
        )
        assert len(received_kwargs) == 2
        for kw in received_kwargs:
            assert kw["session_id"] == "sess-1"
            assert kw["parent_call_id"] == "call-0"


class TestSummarizeChildren:
    """summarize_children 子节点标注。"""

    @pytest.mark.asyncio()
    async def test_normal(self, prompts_dir: Path) -> None:
        """正常两轮标注。"""
        children_info = [
            {"id": "n1", "time_range": (0.0, 30.0), "summary": "开头"},
            {"id": "n2", "time_range": (30.0, 60.0), "summary": "中间"},
        ]
        llm = FakeLLMProvider(["相关性标注结果", "核实通过"])
        result = await summarize_children(
            llm, children_info, "问题", prompts_dir
        )
        assert "相关性标注结果" in result
        assert "[核实] 核实通过" in result

    @pytest.mark.asyncio()
    async def test_extract_failure_fallback(self, prompts_dir: Path) -> None:
        """提取失败回退到原始列表。"""
        children_info = [
            {"id": "n1", "time_range": (0.0, 30.0), "summary": "开头"},
        ]
        llm = FailingLLMProvider("网络错误")
        result = await summarize_children(
            llm, children_info, "问题", prompts_dir
        )
        assert "n1" in result
        assert "0-30s" in result
        assert "开头" in result

    @pytest.mark.asyncio()
    async def test_verify_failure_returns_extract_only(
        self, prompts_dir: Path
    ) -> None:
        """核实轮失败仍返回提取结果。"""
        children_info = [
            {"id": "n1", "time_range": (0.0, 30.0), "summary": "开头"},
        ]
        llm = FailOnNthLLMProvider(["标注结果"], fail_on=2)
        result = await summarize_children(
            llm, children_info, "问题", prompts_dir
        )
        assert "标注结果" in result


class TestSummarizeNodesBatch:
    """summarize_nodes_batch 并发多节点。"""

    @pytest.mark.asyncio()
    async def test_batch_normal(self, prompts_dir: Path) -> None:
        """并发三个节点，结果顺序与输入一致。"""
        # 每个节点需要 2 轮 LLM 调用（提取 + 核实）
        llm = FakeLLMProvider([
            "摘要A", "核实A",
            "摘要B", "核实B",
            "摘要C", "核实C",
        ])
        items = [
            ("n1", "内容1", "extra1"),
            ("n2", "内容2", "extra2"),
            ("n3", "内容3", "extra3"),
        ]
        results = await summarize_nodes_batch(
            llm, items, "问题", prompts_dir
        )
        assert len(results) == 3
        assert results[0][0] == "n1"
        assert results[1][0] == "n2"
        assert results[2][0] == "n3"
        assert "[内容摘要]" in results[0][1]
        assert "[内容摘要]" in results[1][1]
        assert "[内容摘要]" in results[2][1]

    @pytest.mark.asyncio()
    async def test_batch_empty(self, prompts_dir: Path) -> None:
        """空列表返回空结果。"""
        llm = FakeLLMProvider([])
        results = await summarize_nodes_batch(
            llm, [], "问题", prompts_dir
        )
        assert results == []