"""VideoTreeBuilder 单元测试。

测试覆盖：
- _segment_video: 时间切分
- _get_l2_clips: 片段切分
- _sample_representative_frames: 帧采样
- _parse_l3_cards: L3 JSON 解析 + fallback 条件
- _parse_l2_card: L2 JSON 解析
- _parse_l1_card: L1 JSON 解析
- _parse_l3_card_single: 单帧 L3 JSON 解析
- build: 完整构建流程（mock VLM/LLM）
- checkpoint/resume: 断点续跑机制
"""

from __future__ import annotations

import json
from pathlib import Path
from typing import Any
from unittest.mock import patch

import pytest

from app.tree.config import TreeConfig
from app.tree.index import (
    L1Card,
    L1Node,
    L2Card,
    L2Node,
    L3Card,
    L3Node,
)
from app.tree.video_builder import VideoTreeBuilder
from core.types import LLMResponse

# ---------------------------------------------------------------------------
# Mock 提供者
# ---------------------------------------------------------------------------


def _make_llm_response(content: str) -> LLMResponse:
    """构造 LLMResponse 测试工具。"""
    return LLMResponse(
        content=content,
        thinking="",
        model="mock",
        provider="mock",
        prompt_tokens=10,
        completion_tokens=10,
        latency_ms=10,
        ttft_ms=1.0,
        max_inter_token_ms=1.0,
        cache_hit=False,
        call_id="mock-call",
    )


def _l3_card_dict(idx: int = 0) -> dict[str, Any]:
    """构造单个 L3Card 的字典表示。"""
    return {
        "frame_summary": f"帧 {idx} 的描述",
        "visible_entities": ["实体A"],
        "ongoing_actions": ["动作A"],
        "visible_text": [],
        "spatial_layout": "居中",
        "visual_attributes": {
            "lighting": "自然光",
            "dominant_colors": ["白"],
            "camera_angle": "正面",
        },
    }


def _l2_card_dict() -> dict[str, Any]:
    """构造 L2Card 的字典表示。"""
    return {
        "event_description": "视频片段描述",
        "entities": ["实体A"],
        "actions": ["动作A"],
        "action_subjects": ["主体A"],
        "visible_text": [],
        "spatial_relations": "居中",
        "state_changes": None,
    }


def _l1_card_dict() -> dict[str, Any]:
    """构造 L1Card 的字典表示。"""
    return {
        "scene_summary": "场景摘要描述",
        "main_setting": "室内",
        "key_entities": ["实体A"],
        "main_actions": ["动作A"],
        "topic_keywords": ["关键词A"],
        "visible_text": [],
        "temporal_flow": "从开始到结束",
    }


class MockVLMProvider:
    """模拟 VLM 提供者，根据 prompt 类型返回固定 JSON 响应。"""

    def __init__(self) -> None:
        self.calls: list[dict[str, Any]] = []

    async def chat_with_images(
        self,
        messages: list[dict[str, Any]],
        images: list[str | Path],
        *,
        session_id: str | None = None,
        parent_call_id: str | None = None,
    ) -> LLMResponse:
        """根据 prompt 内容判断调用类型，返回对应 JSON。"""
        self.calls.append({"messages": messages, "images": images})
        content = messages[0]["content"]
        n_images = len(images)

        if "JSON 数组" in content:
            # L3 batch prompt
            cards = [_l3_card_dict(i) for i in range(n_images)]
            return _make_llm_response(json.dumps(cards, ensure_ascii=False))
        if "用一到两句话描述这帧" in content:
            # L3 single prompt
            return _make_llm_response(
                json.dumps(_l3_card_dict(0), ensure_ascii=False),
            )
        # L2 prompt
        return _make_llm_response(
            json.dumps(_l2_card_dict(), ensure_ascii=False),
        )


class MockLLMProvider:
    """模拟 LLM 提供者，返回固定 L1Card JSON 响应。"""

    def __init__(self) -> None:
        self.calls: list[dict[str, Any]] = []

    async def chat(
        self,
        messages: list[dict[str, Any]],
        *,
        session_id: str | None = None,
        parent_call_id: str | None = None,
    ) -> LLMResponse:
        """返回 L1Card JSON。"""
        self.calls.append({"messages": messages})
        return _make_llm_response(
            json.dumps(_l1_card_dict(), ensure_ascii=False),
        )


# ---------------------------------------------------------------------------
# Fixtures
# ---------------------------------------------------------------------------


@pytest.fixture()
def tree_config(tmp_path: Path) -> TreeConfig:
    """简化配置：10 秒视频→1 个 L1 段→2 个 L2 clip→每 clip 5 帧。"""
    return TreeConfig(
        l1_segment_duration=10.0,
        l2_clip_duration=5.0,
        l3_fps=1.0,
        l2_representative_frames=2,
        cache_dir=str(tmp_path / "cache"),
        concurrency=4,
    )


@pytest.fixture()
def mock_vlm() -> MockVLMProvider:
    """返回 MockVLMProvider 实例。"""
    return MockVLMProvider()


@pytest.fixture()
def mock_llm() -> MockLLMProvider:
    """返回 MockLLMProvider 实例。"""
    return MockLLMProvider()


@pytest.fixture()
def builder(
    mock_vlm: MockVLMProvider,
    mock_llm: MockLLMProvider,
    tree_config: TreeConfig,
) -> VideoTreeBuilder:
    """构造带 mock 依赖的 VideoTreeBuilder。"""
    return VideoTreeBuilder(vlm=mock_vlm, llm=mock_llm, config=tree_config)


# ---------------------------------------------------------------------------
# 测试：_segment_video
# ---------------------------------------------------------------------------


class TestSegmentVideo:
    """测试时间切分逻辑。"""

    def test_exact_division(self, builder: VideoTreeBuilder) -> None:
        """总时长能被 L1 段时长整除时的切分。"""
        ranges = builder._segment_video("dummy", duration_hint=20.0)
        assert ranges == [(0.0, 10.0), (10.0, 20.0)]

    def test_non_divisible(self, builder: VideoTreeBuilder) -> None:
        """总时长不能被整除时，末段截断。"""
        ranges = builder._segment_video("dummy", duration_hint=15.0)
        assert len(ranges) == 2
        assert ranges[0] == (0.0, 10.0)
        assert ranges[1] == (10.0, 15.0)

    def test_short_video(self, builder: VideoTreeBuilder) -> None:
        """短视频（时长 < L1 段时长）产生单段。"""
        ranges = builder._segment_video("dummy", duration_hint=5.0)
        assert ranges == [(0.0, 5.0)]


# ---------------------------------------------------------------------------
# 测试：_get_l2_clips
# ---------------------------------------------------------------------------


class TestGetL2Clips:
    """测试 L2 clip 切分逻辑。"""

    def test_basic_clips(self, builder: VideoTreeBuilder) -> None:
        """L1 区间能被 L2 步长整除。"""
        clips = builder._get_l2_clips((0.0, 10.0))
        assert clips == [(0.0, 5.0), (5.0, 10.0)]

    def test_remainder_clip(self, builder: VideoTreeBuilder) -> None:
        """L1 区间不能被整除时，末段截断。"""
        clips = builder._get_l2_clips((0.0, 7.0))
        assert len(clips) == 2
        assert clips[0] == (0.0, 5.0)
        assert clips[1] == (5.0, 7.0)


# ---------------------------------------------------------------------------
# 测试：_sample_representative_frames
# ---------------------------------------------------------------------------


class TestSampleRepresentativeFrames:
    """测试帧采样逻辑。"""

    def test_fewer_frames_than_n(self) -> None:
        """帧数不足时返回全部。"""
        frames = [("a.jpg", 0.0), ("b.jpg", 1.0)]
        result = VideoTreeBuilder._sample_representative_frames(frames, 5)
        assert result == ["a.jpg", "b.jpg"]

    def test_exact_n(self) -> None:
        """帧数恰等于 n 时返回全部。"""
        frames = [("a.jpg", 0.0), ("b.jpg", 1.0), ("c.jpg", 2.0)]
        result = VideoTreeBuilder._sample_representative_frames(frames, 3)
        assert result == ["a.jpg", "b.jpg", "c.jpg"]

    def test_uniform_sampling(self) -> None:
        """10 帧中采样 3 帧，应均匀分布。"""
        frames = [(f"{i}.jpg", float(i)) for i in range(10)]
        result = VideoTreeBuilder._sample_representative_frames(frames, 3)
        # step = 10/3 = 3.33 → indices 0, 3, 6
        assert result == ["0.jpg", "3.jpg", "6.jpg"]

    def test_sampling_two_from_five(self) -> None:
        """5 帧中采样 2 帧。"""
        frames = [(f"{i}.jpg", float(i)) for i in range(5)]
        result = VideoTreeBuilder._sample_representative_frames(frames, 2)
        # step = 5/2 = 2.5 → indices 0, 2
        assert result == ["0.jpg", "2.jpg"]


# ---------------------------------------------------------------------------
# 测试：_parse_l3_cards
# ---------------------------------------------------------------------------


class TestParseL3Cards:
    """测试 L3 批量 JSON 解析（保真算法 #2 的解析环节）。"""

    def test_valid_json_array(self, builder: VideoTreeBuilder) -> None:
        """正常 JSON 数组解析成功。"""
        raw = json.dumps([_l3_card_dict(i) for i in range(3)])
        result = builder._parse_l3_cards(raw, 3)
        assert result is not None
        assert len(result) == 3
        assert result[0].frame_summary == "帧 0 的描述"
        assert result[2].frame_summary == "帧 2 的描述"

    def test_count_mismatch_returns_none(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """数量不匹配 → 返回 None（触发 fallback）。"""
        raw = json.dumps([_l3_card_dict(0), _l3_card_dict(1)])
        result = builder._parse_l3_cards(raw, 3)
        assert result is None

    def test_missing_field_returns_none(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """必填字段缺失 → 整批次返回 None。"""
        card = _l3_card_dict(0)
        del card["frame_summary"]
        raw = json.dumps([card])
        result = builder._parse_l3_cards(raw, 1)
        assert result is None

    def test_invalid_json_returns_none(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """非法 JSON 返回 None。"""
        result = builder._parse_l3_cards("not json at all", 1)
        assert result is None

    def test_json_in_code_block(self, builder: VideoTreeBuilder) -> None:
        """Markdown 代码块包裹的 JSON 也能解析。"""
        inner = json.dumps([_l3_card_dict(0)])
        raw = f"```json\n{inner}\n```"
        result = builder._parse_l3_cards(raw, 1)
        assert result is not None
        assert len(result) == 1

    def test_non_dict_item_returns_none(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """数组元素非 dict → 返回 None。"""
        raw = json.dumps(["string_item"])
        result = builder._parse_l3_cards(raw, 1)
        assert result is None


# ---------------------------------------------------------------------------
# 测试：_parse_l2_card
# ---------------------------------------------------------------------------


class TestParseL2Card:
    """测试 L2 JSON 解析。"""

    def test_valid_json(self, builder: VideoTreeBuilder) -> None:
        """正常 JSON 解析成功。"""
        raw = json.dumps(_l2_card_dict(), ensure_ascii=False)
        card = builder._parse_l2_card(raw)
        assert card.event_description == "视频片段描述"
        assert card.entities == ["实体A"]
        assert card.state_changes is None

    def test_invalid_json_fallback(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """JSON 解析失败 → 退化卡片。"""
        card = builder._parse_l2_card("这是一段普通文字描述")
        assert card.event_description == "这是一段普通文字描述"
        assert card.entities == []

    def test_with_state_changes(self, builder: VideoTreeBuilder) -> None:
        """state_changes 非 null 时正常解析。"""
        d = _l2_card_dict()
        d["state_changes"] = "从站立到坐下"
        raw = json.dumps(d, ensure_ascii=False)
        card = builder._parse_l2_card(raw)
        assert card.state_changes == "从站立到坐下"


# ---------------------------------------------------------------------------
# 测试：_parse_l1_card
# ---------------------------------------------------------------------------


class TestParseL1Card:
    """测试 L1 JSON 解析。"""

    def test_valid_json(self, builder: VideoTreeBuilder) -> None:
        """正常 JSON 解析成功。"""
        raw = json.dumps(_l1_card_dict(), ensure_ascii=False)
        card = builder._parse_l1_card(raw)
        assert card.scene_summary == "场景摘要描述"
        assert card.main_setting == "室内"

    def test_invalid_json_fallback(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """JSON 解析失败 → 退化卡片。"""
        card = builder._parse_l1_card("这是段落摘要")
        assert card.scene_summary == "这是段落摘要"
        assert card.key_entities == []


# ---------------------------------------------------------------------------
# 测试：_parse_l3_card_single
# ---------------------------------------------------------------------------


class TestParseL3CardSingle:
    """测试单帧 L3 JSON 解析。"""

    def test_valid_json(self, builder: VideoTreeBuilder) -> None:
        """正常 JSON 解析成功。"""
        raw = json.dumps(_l3_card_dict(0), ensure_ascii=False)
        card = builder._parse_l3_card_single(raw)
        assert card.frame_summary == "帧 0 的描述"

    def test_invalid_json_fallback(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """JSON 解析失败 → 退化卡片。"""
        card = builder._parse_l3_card_single("一帧画面的描述")
        assert card.frame_summary == "一帧画面的描述"
        assert card.visible_entities == []


# ---------------------------------------------------------------------------
# 测试：_extract_json
# ---------------------------------------------------------------------------


class TestExtractJson:
    """测试 JSON 提取辅助方法。"""

    def test_plain_object(self) -> None:
        """直接 JSON 对象。"""
        result = VideoTreeBuilder._extract_json('{"key": "value"}')
        assert result == {"key": "value"}

    def test_plain_array(self) -> None:
        """直接 JSON 数组。"""
        result = VideoTreeBuilder._extract_json("[1, 2, 3]")
        assert result == [1, 2, 3]

    def test_code_block(self) -> None:
        """Markdown 代码块中的 JSON。"""
        raw = '```json\n{"key": "value"}\n```'
        result = VideoTreeBuilder._extract_json(raw)
        assert result == {"key": "value"}

    def test_surrounding_text(self) -> None:
        """JSON 前后有文字。"""
        raw = 'Here is the result: {"key": "value"} end'
        result = VideoTreeBuilder._extract_json(raw)
        assert result == {"key": "value"}

    def test_invalid(self) -> None:
        """完全无 JSON 内容。"""
        result = VideoTreeBuilder._extract_json("no json here")
        assert result is None


# ---------------------------------------------------------------------------
# 测试：完整构建流程
# ---------------------------------------------------------------------------


def _mock_ffmpeg_factory(tmp_path: Path):
    """创建 mock ffmpeg 帧提取函数。"""

    def _mock_extract(
        video_path: str,
        ts: float,
        out_path: str,
    ) -> bool:
        Path(out_path).parent.mkdir(parents=True, exist_ok=True)
        Path(out_path).write_bytes(b"FAKE_JPEG")
        return True

    return _mock_extract


class TestBuildFullFlow:
    """测试完整构建流程（mock VLM/LLM/ffmpeg）。"""

    def test_build_produces_correct_structure(
        self,
        mock_vlm: MockVLMProvider,
        mock_llm: MockLLMProvider,
        tmp_path: Path,
    ) -> None:
        """10 秒视频 → 1 L1 → 2 L2 → 每 L2 约 5 帧 L3。"""
        config = TreeConfig(
            l1_segment_duration=10.0,
            l2_clip_duration=5.0,
            l3_fps=1.0,
            l2_representative_frames=2,
            cache_dir=str(tmp_path / "cache"),
            concurrency=4,
        )
        builder = VideoTreeBuilder(
            vlm=mock_vlm,
            llm=mock_llm,
            config=config,
        )

        dummy_video = tmp_path / "test_video.mp4"
        dummy_video.write_bytes(b"FAKE")

        with (
            patch.object(
                builder,
                "_segment_video",
                return_value=[(0.0, 10.0)],
            ),
            patch.object(
                builder,
                "_ffmpeg_extract_frame",
                side_effect=_mock_ffmpeg_factory(tmp_path),
            ),
        ):
            index = builder.build(str(dummy_video))

        # 结构校验
        assert len(index.roots) == 1
        l1 = index.roots[0]
        assert l1.id == "l1_0"
        assert l1.card.scene_summary == "场景摘要描述"
        assert l1.time_range == (0.0, 10.0)

        # 2 个 L2 clip
        assert len(l1.children) == 2
        for j, l2 in enumerate(l1.children):
            assert l2.id == f"l1_0_l2_{j}"
            assert l2.card.event_description == "视频片段描述"
            # 5 帧/clip（5 秒 * 1 fps）
            assert len(l2.children) == 5
            for k, l3 in enumerate(l2.children):
                assert l3.id == f"l1_0_l2_{j}_l3_{k}"
                assert l3.card.frame_summary is not None
                assert l3.frame_path is not None
                assert l3.timestamp is not None

        # 确认 VLM/LLM 被调用
        # L2: 2 calls (one per clip)
        # L3: 2 calls (one batch per clip, each batch has 5 frames)
        # L1: 1 call
        assert len(mock_vlm.calls) == 4  # 2 L2 + 2 L3 batches
        assert len(mock_llm.calls) == 1  # 1 L1

        # metadata 校验
        assert index.metadata.source_path == str(dummy_video)
        assert index.metadata.modality == "video"

    def test_build_cleans_up_intermediate(
        self,
        mock_vlm: MockVLMProvider,
        mock_llm: MockLLMProvider,
        tmp_path: Path,
    ) -> None:
        """构建成功后中间文件已清理。"""
        config = TreeConfig(
            l1_segment_duration=10.0,
            l2_clip_duration=10.0,
            l3_fps=1.0,
            l2_representative_frames=2,
            cache_dir=str(tmp_path / "cache"),
            concurrency=4,
        )
        builder = VideoTreeBuilder(
            vlm=mock_vlm,
            llm=mock_llm,
            config=config,
        )

        dummy_video = tmp_path / "test_video.mp4"
        dummy_video.write_bytes(b"FAKE")

        with (
            patch.object(
                builder,
                "_segment_video",
                return_value=[(0.0, 10.0)],
            ),
            patch.object(
                builder,
                "_ffmpeg_extract_frame",
                side_effect=_mock_ffmpeg_factory(tmp_path),
            ),
        ):
            builder.build(str(dummy_video))

        # 中间文件应已清理
        progress_dir = tmp_path / "cache" / "progress"
        inter_dir = tmp_path / "cache" / "intermediate" / "test_video"
        assert not (progress_dir / "test_video.json").exists()
        # intermediate 目录可能不存在或为空
        if inter_dir.exists():
            assert len(list(inter_dir.glob("l1_*.json"))) == 0


# ---------------------------------------------------------------------------
# 测试：L3 fallback（保真算法 #2）
# ---------------------------------------------------------------------------


class MockVLMWithBatchFailure:
    """模拟批量 VLM 调用失败、单帧调用成功的 VLM 提供者。"""

    def __init__(self) -> None:
        self.calls: list[dict[str, Any]] = []

    async def chat_with_images(
        self,
        messages: list[dict[str, Any]],
        images: list[str | Path],
        *,
        session_id: str | None = None,
        parent_call_id: str | None = None,
    ) -> LLMResponse:
        """batch 返回无效 JSON，single 返回有效 JSON，L2 正常。"""
        self.calls.append({"n_images": len(images)})
        content = messages[0]["content"]

        if "JSON 数组" in content:
            # L3 batch: 返回无效 JSON 触发 fallback
            return _make_llm_response("INVALID JSON OUTPUT")
        if "用一到两句话描述这帧" in content:
            # L3 single fallback: 有效 JSON
            return _make_llm_response(
                json.dumps(_l3_card_dict(0), ensure_ascii=False),
            )
        # L2: 有效 JSON
        return _make_llm_response(
            json.dumps(_l2_card_dict(), ensure_ascii=False),
        )


class TestL3Fallback:
    """测试 L3 批量失败→逐帧 fallback（保真算法 #2）。"""

    def test_fallback_to_single_frame(
        self,
        mock_llm: MockLLMProvider,
        tmp_path: Path,
    ) -> None:
        """批量 VLM 解析失败时，逐帧 fallback 仍能构建完整树。"""
        vlm = MockVLMWithBatchFailure()
        config = TreeConfig(
            l1_segment_duration=10.0,
            l2_clip_duration=10.0,
            l3_fps=1.0,
            l2_representative_frames=2,
            cache_dir=str(tmp_path / "cache"),
            concurrency=4,
        )
        builder = VideoTreeBuilder(vlm=vlm, llm=mock_llm, config=config)

        dummy_video = tmp_path / "test_video.mp4"
        dummy_video.write_bytes(b"FAKE")

        with (
            patch.object(
                builder,
                "_segment_video",
                return_value=[(0.0, 10.0)],
            ),
            patch.object(
                builder,
                "_ffmpeg_extract_frame",
                side_effect=_mock_ffmpeg_factory(tmp_path),
            ),
        ):
            index = builder.build(str(dummy_video))

        # 结构仍然完整
        assert len(index.roots) == 1
        l1 = index.roots[0]
        assert len(l1.children) == 1  # 1 clip (10s clip)
        l2 = l1.children[0]

        # 10 frames (10s * 1fps), all from single-frame fallback
        assert len(l2.children) == 10
        for l3 in l2.children:
            assert l3.card.frame_summary == "帧 0 的描述"

        # VLM 调用次数：1 L2 + 1 batch(fail) + 10 single = 12
        # 但 batch 分为 2 batches (10 frames / 5 per batch)
        # 所以: 1 L2 + 2 batch(fail) + 10 single = 13
        assert len(vlm.calls) == 13


# ---------------------------------------------------------------------------
# 测试：断点续跑（保真算法 #3）
# ---------------------------------------------------------------------------


class TestCheckpointResume:
    """测试断点续跑机制。"""

    def test_save_and_load_progress(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """进度文件保存和加载。"""
        stem = "test_video"
        builder._save_progress(stem, total_l1=3, finished_l1_ids={0, 1})
        progress = builder._load_progress(stem)

        assert progress is not None
        assert progress["total_l1"] == 3
        assert sorted(progress["finished_l1_ids"]) == [0, 1]
        assert "created_at" in progress
        assert "updated_at" in progress

    def test_load_nonexistent_progress(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """不存在的进度文件返回 None。"""
        assert builder._load_progress("nonexistent") is None

    def test_save_and_load_l1_intermediate(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """L1 中间结果保存和加载。"""
        stem = "test_video"
        l1_card = L1Card(
            scene_summary="测试摘要",
            main_setting="测试场景",
            key_entities=["实体"],
            main_actions=["动作"],
            topic_keywords=["关键词"],
            visible_text=[],
            temporal_flow="测试流向",
        )
        l2_card = L2Card(
            event_description="事件描述",
            entities=["实体"],
            actions=["动作"],
            action_subjects=["主体"],
            visible_text=[],
            spatial_relations="居中",
            state_changes=None,
        )
        l3_card = L3Card(
            frame_summary="帧描述",
            visible_entities=["实体"],
            ongoing_actions=["动作"],
            visible_text=[],
            spatial_layout="居中",
            visual_attributes={"lighting": "自然光"},
        )
        l3_node = L3Node(
            id="l1_0_l2_0_l3_0",
            card=l3_card,
            timestamp=1.0,
            frame_path="/tmp/frame.jpg",
        )
        l2_node = L2Node(
            id="l1_0_l2_0",
            card=l2_card,
            time_range=(0.0, 5.0),
            children=[l3_node],
        )
        l1_node = L1Node(
            id="l1_0",
            card=l1_card,
            time_range=(0.0, 10.0),
            children=[l2_node],
        )

        builder._save_l1_intermediate(stem, l1_node, 0)
        assert builder._has_l1_intermediate(stem, 0)
        assert not builder._has_l1_intermediate(stem, 1)

        loaded = builder._load_l1_intermediate(stem, 0)
        assert loaded is not None
        assert loaded.id == "l1_0"
        assert loaded.card.scene_summary == "测试摘要"
        assert len(loaded.children) == 1
        assert loaded.children[0].id == "l1_0_l2_0"

    def test_cleanup_removes_files(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """清理函数删除进度文件和中间 JSON。"""
        stem = "test_video"
        builder._save_progress(stem, total_l1=1, finished_l1_ids={0})

        # 创建一个假的中间文件
        inter_dir = builder._intermediate_dir(stem)
        inter_dir.mkdir(parents=True, exist_ok=True)
        (inter_dir / "l1_0.json").write_text("{}")

        builder._cleanup_intermediate_and_progress(stem)

        assert not builder._progress_path(stem).is_file()
        assert not (inter_dir / "l1_0.json").is_file()

    def test_resume_skips_finished_segments(
        self,
        mock_vlm: MockVLMProvider,
        mock_llm: MockLLMProvider,
        tmp_path: Path,
    ) -> None:
        """断点续跑：跳过已完成的 L1 段，只构建未完成的段。"""
        config = TreeConfig(
            l1_segment_duration=5.0,
            l2_clip_duration=5.0,
            l3_fps=1.0,
            l2_representative_frames=2,
            cache_dir=str(tmp_path / "cache"),
            concurrency=4,
        )
        builder = VideoTreeBuilder(
            vlm=mock_vlm,
            llm=mock_llm,
            config=config,
        )

        source_id = "test_resume"

        # Phase 1: 手动创建 L1_0 的中间结果（模拟已完成）
        l1_card = L1Card(
            scene_summary="已完成的段",
            main_setting="场景A",
            key_entities=["实体A"],
            main_actions=["动作A"],
            topic_keywords=["关键词A"],
            visible_text=[],
            temporal_flow="流向A",
        )
        l2_card = L2Card(
            event_description="已完成的片段",
            entities=["实体A"],
            actions=["动作A"],
            action_subjects=["主体A"],
            visible_text=[],
            spatial_relations="居中",
            state_changes=None,
        )
        l3_card = L3Card(
            frame_summary="已完成的帧",
            visible_entities=["实体A"],
            ongoing_actions=["动作A"],
            visible_text=[],
            spatial_layout="居中",
            visual_attributes={"lighting": "自然光"},
        )
        l3_node = L3Node(
            id="l1_0_l2_0_l3_0",
            card=l3_card,
            timestamp=1.0,
        )
        l2_node = L2Node(
            id="l1_0_l2_0",
            card=l2_card,
            time_range=(0.0, 5.0),
            children=[l3_node],
        )
        l1_node_0 = L1Node(
            id="l1_0",
            card=l1_card,
            time_range=(0.0, 5.0),
            children=[l2_node],
        )
        builder._save_l1_intermediate(source_id, l1_node_0, 0)

        # Phase 2: 创建进度文件（标记 L1_0 完成）
        builder._save_progress(
            source_id,
            total_l1=2,
            finished_l1_ids={0},
        )

        # Phase 3: 构建（应跳过 L1_0，只构建 L1_1）
        dummy_video = tmp_path / f"{source_id}.mp4"
        dummy_video.write_bytes(b"FAKE")

        with (
            patch.object(
                builder,
                "_segment_video",
                return_value=[(0.0, 5.0), (5.0, 10.0)],
            ),
            patch.object(
                builder,
                "_ffmpeg_extract_frame",
                side_effect=_mock_ffmpeg_factory(tmp_path),
            ),
        ):
            index = builder.build(str(dummy_video))

        # Phase 4: 验证
        assert len(index.roots) == 2

        # L1_0 来自中间结果
        assert index.roots[0].id == "l1_0"
        assert index.roots[0].card.scene_summary == "已完成的段"

        # L1_1 是新构建的
        assert index.roots[1].id == "l1_1"
        assert index.roots[1].card.scene_summary == "场景摘要描述"

        # VLM 只被调用了 L1_1 的部分（1 L2 + 1 L3 batch）
        assert len(mock_vlm.calls) == 2  # 1 L2 + 1 L3
        assert len(mock_llm.calls) == 1  # 1 L1

        # 构建完成后，进度和中间文件已清理
        assert not builder._progress_path(source_id).is_file()


# ---------------------------------------------------------------------------
# 测试：字幕注入
# ---------------------------------------------------------------------------


class TestSubtitleInjection:
    """测试字幕注入功能。"""

    def test_build_subtitle_block_with_entries(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """有匹配字幕时返回字幕文本块。"""
        from app.tree.subtitle import SRTEntry

        entries = [
            SRTEntry(start=1.0, end=3.0, text="你好世界"),
            SRTEntry(start=4.0, end=6.0, text="再见"),
        ]
        block = builder._build_subtitle_block(entries, (0.0, 5.0))
        assert "字幕信息" in block
        assert "你好世界" in block

    def test_build_subtitle_block_no_match(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """无匹配字幕时返回空字符串。"""
        from app.tree.subtitle import SRTEntry

        entries = [SRTEntry(start=100.0, end=110.0, text="远处的字幕")]
        block = builder._build_subtitle_block(entries, (0.0, 5.0))
        assert block == ""

    def test_build_subtitle_block_none_entries(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """srt_entries 为 None 时返回空字符串。"""
        block = builder._build_subtitle_block(None, (0.0, 5.0))
        assert block == ""

    def test_build_subtitle_block_point_range(
        self,
        builder: VideoTreeBuilder,
    ) -> None:
        """点时间范围（单帧）自动扩展窗口。"""
        from app.tree.subtitle import SRTEntry

        entries = [SRTEntry(start=4.0, end=6.0, text="窗口内字幕")]
        # 点时间 5.0，窗口 ±5.0 → (0.0, 10.0)
        block = builder._build_subtitle_block(entries, (5.0, 5.0))
        assert "窗口内字幕" in block


# ---------------------------------------------------------------------------
# 测试：URL 与 stem 辅助
# ---------------------------------------------------------------------------


class TestHelpers:
    """测试静态辅助方法。"""

    def test_is_url_true(self) -> None:
        """HTTP/HTTPS URL 识别。"""
        assert VideoTreeBuilder._is_url("https://example.com/video.mp4")
        assert VideoTreeBuilder._is_url("http://example.com/video.mp4")

    def test_is_url_false(self) -> None:
        """本地路径不是 URL。"""
        assert not VideoTreeBuilder._is_url("/path/to/video.mp4")
        assert not VideoTreeBuilder._is_url("video.mp4")

    def test_source_stem_local(self) -> None:
        """本地文件的 stem。"""
        assert VideoTreeBuilder._source_stem("/path/to/my_video.mp4") == "my_video"

    def test_source_stem_youtube(self) -> None:
        """YouTube URL 的 stem 为视频 ID。"""
        stem = VideoTreeBuilder._source_stem(
            "https://www.youtube.com/watch?v=dQw4w9WgXcQ",
        )
        assert stem == "dQw4w9WgXcQ"

    def test_source_stem_long_name(self) -> None:
        """超长文件名截断到 64 字符。"""
        long_name = "a" * 100 + ".mp4"
        stem = VideoTreeBuilder._source_stem(f"/path/{long_name}")
        assert len(stem) == 64