feat(repair): regenerator + supplement 防御修复 + 迁移脚本
- 新增 app/tree/repair/regenerator.py（VLM 重生成 + 级联修复） - supplement.py: deduplicate_field str() 防御 + inject_value strip - patch.py: ruff format 格式化 - repair_trees.sh: conda source 激活修复 - 新增 migrate_from_trm4.sh 迁移工具 - enhance/__init__.py → repair/__init__.py 重命名 Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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"""树修复重生成器：VLM 重新描述问题节点 + 底向上级联。
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底向上修复流程:
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1. 收集需修复的 L3 节点 → VLM 重新描述帧
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2. 收集受影响的 L2 → LLM 从 L3 children 聚合
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3. 收集受影响的 L1 → LLM 从 L2 children 聚合
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仅处理 issue_type == "empty_field" 且 level == 3 的问题节点。
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帧文件不存在时跳过该节点（不中断整体修复流程）。
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"""
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from __future__ import annotations
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import json
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import re
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from dataclasses import dataclass
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from typing import TYPE_CHECKING, Any
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from loguru import logger
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from app.tree.index import (
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L1Card,
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L1Node,
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L2Card,
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L2Node,
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L3Card,
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L3Node,
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TreeIndex,
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)
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from app.tree.subtitle import extract_subtitle_for_range
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if TYPE_CHECKING:
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from pathlib import Path
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from app.tree.repair.detector import NodeIssue
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from app.tree.subtitle import SRTEntry
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from core.protocols import LLMProvider, VLMProvider
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# ---------------------------------------------------------------------------
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# Prompt 常量（与 VideoTreeBuilder 保持一致风格）
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# ---------------------------------------------------------------------------
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_L3_REPAIR_PROMPT = (
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'该片段的整体内容: "{l2_description}"\n'
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"用一到两句话描述这帧画面的具体内容。"
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"重点关注: 动作、物体变化、文字信息、人物表情。\n"
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"{subtitle_block}"
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"返回 JSON 对象，包含以下字段：\n"
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"- frame_summary: 画面描述\n"
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"- visible_entities: 可见实体列表\n"
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"- ongoing_actions: 动作列表\n"
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"- visible_text: 可见文字列表\n"
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"- spatial_layout: 空间布局\n"
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'- visual_attributes: {{"lighting": "...", "dominant_colors": [...], "camera_angle": "..."}}\n'
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"只返回 JSON 对象，不要其他内容。"
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)
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_L2_REGEN_PROMPT = (
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"以下是一个视频片段中各帧的描述:\n{l3_texts}\n"
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"用1-2句话描述该片段的核心内容。\n"
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"返回 JSON 对象，包含以下字段：\n"
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"- event_description: 1-2句片段描述\n"
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"- entities: 可见实体列表\n"
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"- actions: 动作列表\n"
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"- action_subjects: 动作主体列表\n"
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"- visible_text: 画面中可见文字列表\n"
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"- spatial_relations: 空间关系描述\n"
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"- state_changes: 状态变化描述（无则 null）\n"
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"只返回 JSON 对象，不要其他内容。"
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)
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_L1_REGEN_PROMPT = (
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"以下是一个视频段落中各片段的描述:\n{l2_texts}\n"
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"用2-3句话总结该段落的整体内容，涵盖所有片段的主题。\n"
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"返回 JSON 对象，包含以下字段：\n"
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"- scene_summary: 2-3句段落摘要\n"
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"- main_setting: 主要场景\n"
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"- key_entities: 关键实体列表\n"
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"- main_actions: 主要动作列表\n"
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"- topic_keywords: 主题关键词列表\n"
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"- visible_text: 出现的文字列表\n"
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"- temporal_flow: 时间流向描述\n"
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"只返回 JSON 对象，不要其他内容。"
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)
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# ---------------------------------------------------------------------------
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# 统计数据类
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# ---------------------------------------------------------------------------
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@dataclass
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class RepairStats:
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"""修复统计信息。
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属性:
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l3_repaired: 修复的 L3 节点数。
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l2_regenerated: 重生成的 L2 节点数。
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l1_regenerated: 重生成的 L1 节点数。
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"""
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l3_repaired: int = 0
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l2_regenerated: int = 0
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l1_regenerated: int = 0
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# ---------------------------------------------------------------------------
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# JSON 解析辅助（复用 VideoTreeBuilder 的解析逻辑）
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# ---------------------------------------------------------------------------
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def _extract_json(raw: str) -> Any:
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"""从 VLM/LLM 原始输出中提取 JSON（处理 markdown 代码块包裹）。
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参数:
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raw: 原始返回字符串。
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返回:
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解析后的 Python 对象（dict/list），解析失败返回 None。
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"""
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raw = raw.strip()
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# Phase 1: 尝试提取 markdown 代码块中的 JSON
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code_match = re.search(
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r"```(?:json)?\s*([\[{].*?[\]}])\s*```",
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raw,
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re.DOTALL,
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)
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if code_match:
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raw = code_match.group(1)
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# Phase 2: 直接解析
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try:
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return json.loads(raw)
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except json.JSONDecodeError:
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pass
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# Phase 3: 尝试提取裸 JSON 对象/数组
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json_match = re.search(r"[\[{].*[\]}]", raw, re.DOTALL)
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if json_match:
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try:
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return json.loads(json_match.group())
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except json.JSONDecodeError:
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pass
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return None
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def _parse_l3_card(raw: str) -> L3Card | None:
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"""解析 VLM 输出为 L3Card。解析失败返回 None。
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参数:
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raw: VLM 原始返回字符串。
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返回:
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L3Card 实例或 None（解析失败时）。
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"""
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data = _extract_json(raw)
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if isinstance(data, dict):
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try:
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return L3Card(
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frame_summary=str(data["frame_summary"]),
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visible_entities=list(data["visible_entities"]),
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ongoing_actions=list(data["ongoing_actions"]),
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visible_text=list(data["visible_text"]),
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spatial_layout=str(data["spatial_layout"]),
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visual_attributes=dict(data["visual_attributes"]),
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)
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except (KeyError, TypeError, ValueError):
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pass
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return None
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def _parse_l2_card(raw: str) -> L2Card | None:
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"""解析 LLM 输出为 L2Card。解析失败返回 None。
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参数:
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raw: LLM 原始返回字符串。
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返回:
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L2Card 实例或 None（解析失败时）。
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"""
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data = _extract_json(raw)
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if isinstance(data, dict):
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try:
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state_changes = data.get("state_changes")
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if state_changes is not None:
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state_changes = str(state_changes)
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return L2Card(
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event_description=str(data["event_description"]),
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entities=list(data["entities"]),
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actions=list(data["actions"]),
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action_subjects=list(data["action_subjects"]),
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visible_text=list(data["visible_text"]),
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spatial_relations=str(data["spatial_relations"]),
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state_changes=state_changes,
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)
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except (KeyError, TypeError, ValueError):
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pass
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return None
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def _parse_l1_card(raw: str) -> L1Card | None:
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"""解析 LLM 输出为 L1Card。解析失败返回 None。
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参数:
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raw: LLM 原始返回字符串。
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返回:
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L1Card 实例或 None（解析失败时）。
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"""
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data = _extract_json(raw)
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if isinstance(data, dict):
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try:
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return L1Card(
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scene_summary=str(data["scene_summary"]),
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main_setting=str(data["main_setting"]),
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key_entities=list(data["key_entities"]),
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main_actions=list(data["main_actions"]),
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topic_keywords=list(data["topic_keywords"]),
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visible_text=list(data["visible_text"]),
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temporal_flow=str(data["temporal_flow"]),
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)
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except (KeyError, TypeError, ValueError):
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pass
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return None
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# ---------------------------------------------------------------------------
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# 节点查找辅助
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# ---------------------------------------------------------------------------
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def _build_node_lookup(
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index: TreeIndex,
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) -> tuple[
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dict[str, L3Node],
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dict[str, L2Node],
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dict[str, L1Node],
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dict[str, L2Node],
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dict[str, L1Node],
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]:
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"""构建节点 ID 到节点的查找表 + 子节点到父节点的映射。
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参数:
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index: 树索引。
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返回:
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(l3_by_id, l2_by_id, l1_by_id, l3_parent_l2, l2_parent_l1)
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- l3_by_id: L3 节点 ID → L3Node
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- l2_by_id: L2 节点 ID → L2Node
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- l1_by_id: L1 节点 ID → L1Node
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- l3_parent_l2: L3 节点 ID → 其父 L2Node
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- l2_parent_l1: L2 节点 ID → 其父 L1Node
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"""
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l3_by_id: dict[str, L3Node] = {}
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l2_by_id: dict[str, L2Node] = {}
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l1_by_id: dict[str, L1Node] = {}
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l3_parent_l2: dict[str, L2Node] = {}
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l2_parent_l1: dict[str, L1Node] = {}
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for l1 in index.roots:
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l1_by_id[l1.id] = l1
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for l2 in l1.children:
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l2_by_id[l2.id] = l2
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l2_parent_l1[l2.id] = l1
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for l3 in l2.children:
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l3_by_id[l3.id] = l3
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l3_parent_l2[l3.id] = l2
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return l3_by_id, l2_by_id, l1_by_id, l3_parent_l2, l2_parent_l1
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# ---------------------------------------------------------------------------
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# 字幕辅助
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# ---------------------------------------------------------------------------
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def _build_subtitle_block(
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srt_entries: list[SRTEntry] | None,
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timestamp: float | None,
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) -> str:
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"""构建字幕注入文本块。
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参数:
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srt_entries: SRT 字幕条目列表。
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timestamp: 帧时间戳（秒）。
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返回:
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字幕文本块字符串（无匹配时返回空字符串）。
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"""
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if not srt_entries or timestamp is None:
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return ""
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window = 2.0
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start = max(0.0, timestamp - window)
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end = timestamp + window
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text = extract_subtitle_for_range(srt_entries, (start, end))
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if not text:
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return ""
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return f"字幕信息：\n{text}\n"
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# ---------------------------------------------------------------------------
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# 主修复函数
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# ---------------------------------------------------------------------------
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async def repair_tree(
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index: TreeIndex,
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issues: list[NodeIssue],
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vlm: VLMProvider,
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llm: LLMProvider,
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frames_dir: Path,
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srt_entries: list[SRTEntry] | None = None,
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) -> RepairStats:
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"""修复有问题的节点，底向上级联。
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流程:
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1. 收集需修复的 L3 节点 → VLM 重新描述帧
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2. 收集受影响的 L2 → LLM 从 L3 children 聚合
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3. 收集受影响的 L1 → LLM 从 L2 children 聚合
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参数:
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index: 待修复的 TreeIndex（原地修改）。
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issues: detect_issues() 返回的问题列表。
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vlm: VLM 调用端口。
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llm: LLM 调用端口。
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frames_dir: 帧文件根目录。
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srt_entries: 字幕条目列表（可选）。
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返回:
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RepairStats 统计。
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"""
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stats = RepairStats()
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if not issues:
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logger.info("无修复任务，跳过")
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return stats
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# 构建查找表
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l3_by_id, l2_by_id, l1_by_id, l3_parent_l2, l2_parent_l1 = _build_node_lookup(index)
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# Step 1: 修复 L3 节点（仅处理 empty_field + level 3）
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l3_issues = [
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issue for issue in issues if issue.issue_type == "empty_field" and issue.level == 3
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]
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affected_l2_ids: set[str] = set()
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for issue in l3_issues:
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l3_node = l3_by_id.get(issue.node_id)
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if l3_node is None:
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logger.warning(
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"L3 节点 ID 未在树中找到，跳过",
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node_id=issue.node_id,
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)
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continue
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# 查找帧文件
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if l3_node.frame_path is None:
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logger.warning(
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"L3 节点无 frame_path，跳过",
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node_id=issue.node_id,
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)
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continue
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frame_file = frames_dir / l3_node.frame_path
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if not frame_file.exists():
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logger.warning(
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"L3 帧文件不存在，跳过修复",
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node_id=issue.node_id,
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frame_path=str(frame_file),
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)
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continue
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# 获取 L2 父节点描述作为上下文
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parent_l2 = l3_parent_l2.get(issue.node_id)
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l2_description = parent_l2.card.event_description if parent_l2 else ""
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# 构建字幕块
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subtitle_block = _build_subtitle_block(srt_entries, l3_node.timestamp)
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# VLM 重新描述帧
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prompt = _L3_REPAIR_PROMPT.format(
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l2_description=l2_description,
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subtitle_block=subtitle_block,
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)
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messages = [{"role": "user", "content": prompt}]
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try:
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response = await vlm.chat_with_images(messages, [str(frame_file)])
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except Exception as exc:
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logger.warning(
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"L3 修复 VLM 调用失败，跳过: {}",
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exc,
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node_id=issue.node_id,
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)
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continue
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new_card = _parse_l3_card(response.content)
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if new_card is None:
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logger.warning(
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"L3 修复 VLM 输出解析失败，跳过",
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node_id=issue.node_id,
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raw_preview=response.content[:200],
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)
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continue
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# 原地替换 card（L3Node.card 不是 frozen dataclass 的限制字段）
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l3_node.card = new_card
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stats.l3_repaired += 1
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# 标记受影响的 L2 父节点
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if parent_l2 is not None:
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affected_l2_ids.add(parent_l2.id)
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logger.debug(
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"L3 节点修复完成",
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node_id=issue.node_id,
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frame_summary=new_card.frame_summary[:50],
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)
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# Step 2: 重生成受影响的 L2 节点
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affected_l1_ids: set[str] = set()
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for l2_id in affected_l2_ids:
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l2_node = l2_by_id.get(l2_id)
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if l2_node is None:
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continue
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# 从 L3 children 聚合描述
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l3_texts = "\n".join(f"- {l3.card.frame_summary}" for l3 in l2_node.children)
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prompt = _L2_REGEN_PROMPT.format(l3_texts=l3_texts)
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messages = [{"role": "user", "content": prompt}]
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try:
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response = await llm.chat(messages)
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except Exception as exc:
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logger.warning(
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||||
"L2 重生成 LLM 调用失败，跳过: {}",
|
||||
exc,
|
||||
l2_id=l2_id,
|
||||
)
|
||||
continue
|
||||
|
||||
new_card = _parse_l2_card(response.content)
|
||||
if new_card is None:
|
||||
logger.warning(
|
||||
"L2 重生成 LLM 输出解析失败，跳过",
|
||||
l2_id=l2_id,
|
||||
raw_preview=response.content[:200],
|
||||
)
|
||||
continue
|
||||
|
||||
l2_node.card = new_card
|
||||
stats.l2_regenerated += 1
|
||||
|
||||
# 标记受影响的 L1 父节点
|
||||
parent_l1 = l2_parent_l1.get(l2_id)
|
||||
if parent_l1 is not None:
|
||||
affected_l1_ids.add(parent_l1.id)
|
||||
|
||||
logger.debug(
|
||||
"L2 节点重生成完成",
|
||||
l2_id=l2_id,
|
||||
event_description=new_card.event_description[:50],
|
||||
)
|
||||
|
||||
# Step 3: 重生成受影响的 L1 节点
|
||||
for l1_id in affected_l1_ids:
|
||||
l1_node = l1_by_id.get(l1_id)
|
||||
if l1_node is None:
|
||||
continue
|
||||
|
||||
# 从 L2 children 聚合描述
|
||||
l2_texts = "\n".join(f"- {l2.card.event_description}" for l2 in l1_node.children)
|
||||
prompt = _L1_REGEN_PROMPT.format(l2_texts=l2_texts)
|
||||
messages = [{"role": "user", "content": prompt}]
|
||||
|
||||
try:
|
||||
response = await llm.chat(messages)
|
||||
except Exception as exc:
|
||||
logger.warning(
|
||||
"L1 重生成 LLM 调用失败，跳过: {}",
|
||||
exc,
|
||||
l1_id=l1_id,
|
||||
)
|
||||
continue
|
||||
|
||||
new_card = _parse_l1_card(response.content)
|
||||
if new_card is None:
|
||||
logger.warning(
|
||||
"L1 重生成 LLM 输出解析失败，跳过",
|
||||
l1_id=l1_id,
|
||||
raw_preview=response.content[:200],
|
||||
)
|
||||
continue
|
||||
|
||||
l1_node.card = new_card
|
||||
stats.l1_regenerated += 1
|
||||
|
||||
logger.debug(
|
||||
"L1 节点重生成完成",
|
||||
l1_id=l1_id,
|
||||
scene_summary=new_card.scene_summary[:50],
|
||||
)
|
||||
|
||||
logger.info(
|
||||
"树修复完成",
|
||||
l3_repaired=stats.l3_repaired,
|
||||
l2_regenerated=stats.l2_regenerated,
|
||||
l1_regenerated=stats.l1_regenerated,
|
||||
)
|
||||
return stats
|
||||
@@ -84,10 +84,11 @@ def deduplicate_field(values: list[str]) -> list[str]:
|
||||
seen: set[str] = set()
|
||||
result: list[str] = []
|
||||
for v in values:
|
||||
key = v.strip().lower()
|
||||
s = str(v).strip()
|
||||
key = s.lower()
|
||||
if key and key not in seen:
|
||||
seen.add(key)
|
||||
result.append(v)
|
||||
result.append(s)
|
||||
return result
|
||||
|
||||
|
||||
@@ -278,7 +279,7 @@ def apply_injections(index: TreeIndex, injections: list[dict[str, Any]]) -> Supp
|
||||
stats.facts_skipped += 1
|
||||
continue
|
||||
|
||||
inject_value = instr.get("inject_value", "")
|
||||
inject_value = str(instr.get("inject_value", "")).strip()
|
||||
if not inject_value:
|
||||
stats.facts_skipped += 1
|
||||
continue
|
||||
|
||||
+4
-12
@@ -15,9 +15,7 @@ APPENDIX_MAX_CHARS = 2000 # appendix 区软上限（守设计「长度上限+wa
|
||||
MOMENTUM_START = "<!-- MOMENTUM_START -->"
|
||||
MOMENTUM_END = "<!-- MOMENTUM_END -->"
|
||||
MOMENTUM_MAX_CHARS = 2000 # momentum 区软上限（与 appendix 一致：超限 warning 不截断）
|
||||
MOMENTUM_HEADING = (
|
||||
"## 动量指导（每轮重写，勿手改）" # replace_momentum 写入的固定标题行
|
||||
)
|
||||
MOMENTUM_HEADING = "## 动量指导（每轮重写，勿手改）" # replace_momentum 写入的固定标题行
|
||||
|
||||
|
||||
def momentum_region_bounds(text: str) -> tuple[int, int] | None:
|
||||
@@ -303,9 +301,7 @@ def _insert_at(content: str, at: int, payload: str) -> str:
|
||||
return head + "\n\n" + payload + "\n"
|
||||
|
||||
|
||||
def _do_append(
|
||||
content: str, payload: str, ranges: list[tuple[int, int]]
|
||||
) -> tuple[str, str]:
|
||||
def _do_append(content: str, payload: str, ranges: list[tuple[int, int]]) -> tuple[str, str]:
|
||||
"""执行 append 操作，返回更新后内容与状态字符串。"""
|
||||
return _insert_at(content, _append_at(content, ranges), payload), "applied_append"
|
||||
|
||||
@@ -351,9 +347,7 @@ def _do_replace_delete(
|
||||
return new_content, "applied_" + op
|
||||
|
||||
|
||||
def _apply_one(
|
||||
content: str, edit: dict, ranges: list[tuple[int, int]]
|
||||
) -> tuple[str, dict]:
|
||||
def _apply_one(content: str, edit: dict, ranges: list[tuple[int, int]]) -> tuple[str, dict]:
|
||||
"""应用单条 edit，返回 (更新后内容, 状态报告)。"""
|
||||
if not isinstance(edit, dict):
|
||||
return content, {
|
||||
@@ -382,9 +376,7 @@ def _apply_one(
|
||||
return content, report
|
||||
|
||||
if op in ("replace", "delete"):
|
||||
content, report["status"] = _do_replace_delete(
|
||||
op, content, target, payload, ranges
|
||||
)
|
||||
content, report["status"] = _do_replace_delete(op, content, target, payload, ranges)
|
||||
return content, report
|
||||
|
||||
logger.warning("未知 op，跳过: {}", op)
|
||||
|
||||
@@ -17,6 +17,8 @@ set -euo pipefail
|
||||
|
||||
CONCURRENCY="${CONCURRENCY:-16}"
|
||||
|
||||
# shellcheck source=/dev/null
|
||||
source "$(conda info --base)/etc/profile.d/conda.sh"
|
||||
conda activate Video-Tree-TRM
|
||||
|
||||
python tools/repair_trees.py \
|
||||
|
||||
@@ -0,0 +1,293 @@
|
||||
"""修复重生成器单元测试。"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
from app.tree.index import (
|
||||
IndexMeta,
|
||||
L1Card,
|
||||
L1Node,
|
||||
L2Card,
|
||||
L2Node,
|
||||
L3Card,
|
||||
L3Node,
|
||||
TreeIndex,
|
||||
)
|
||||
from app.tree.repair.detector import NodeIssue
|
||||
from app.tree.repair.regenerator import RepairStats, repair_tree
|
||||
from core.types import LLMResponse
|
||||
|
||||
|
||||
def _mock_response(content: str) -> LLMResponse:
|
||||
"""构造模拟 LLMResponse。"""
|
||||
return LLMResponse(
|
||||
content=content,
|
||||
thinking="",
|
||||
model="mock",
|
||||
provider="mock",
|
||||
prompt_tokens=0,
|
||||
completion_tokens=0,
|
||||
latency_ms=0,
|
||||
ttft_ms=None,
|
||||
max_inter_token_ms=None,
|
||||
cache_hit=False,
|
||||
call_id="mock",
|
||||
)
|
||||
|
||||
|
||||
class MockVLM:
|
||||
"""模拟 VLM 端口，返回固定的 L3Card JSON。"""
|
||||
|
||||
def __init__(self) -> None:
|
||||
self.call_count = 0
|
||||
|
||||
async def chat_with_images(
|
||||
self,
|
||||
messages: list[dict],
|
||||
images: list,
|
||||
**kw: object,
|
||||
) -> LLMResponse:
|
||||
"""模拟 VLM 图文调用。"""
|
||||
self.call_count += 1
|
||||
return _mock_response(
|
||||
json.dumps(
|
||||
{
|
||||
"frame_summary": "修复后的帧描述",
|
||||
"visible_entities": ["修复实体"],
|
||||
"ongoing_actions": ["修复动作"],
|
||||
"visible_text": [],
|
||||
"spatial_layout": "居中",
|
||||
"visual_attributes": {"lighting": "明亮"},
|
||||
}
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
class MockLLM:
|
||||
"""模拟 LLM 端口，根据 prompt 内容返回 L2Card 或 L1Card JSON。"""
|
||||
|
||||
def __init__(self) -> None:
|
||||
self.call_count = 0
|
||||
|
||||
async def chat(
|
||||
self,
|
||||
messages: list[dict],
|
||||
**kw: object,
|
||||
) -> LLMResponse:
|
||||
"""模拟 LLM 文本调用，按 prompt 内容区分 L2/L1 响应。"""
|
||||
self.call_count += 1
|
||||
content = messages[-1].get("content", "")
|
||||
if "段落" in content or "scene" in content.lower():
|
||||
return _mock_response(
|
||||
json.dumps(
|
||||
{
|
||||
"scene_summary": "修复后的场景",
|
||||
"main_setting": "室内",
|
||||
"key_entities": [],
|
||||
"main_actions": [],
|
||||
"topic_keywords": [],
|
||||
"visible_text": [],
|
||||
"temporal_flow": "",
|
||||
}
|
||||
)
|
||||
)
|
||||
return _mock_response(
|
||||
json.dumps(
|
||||
{
|
||||
"event_description": "修复后的事件",
|
||||
"entities": [],
|
||||
"actions": [],
|
||||
"action_subjects": [],
|
||||
"visible_text": [],
|
||||
"spatial_relations": "",
|
||||
"state_changes": None,
|
||||
}
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
class TestRepairTree:
|
||||
"""repair_tree 核心测试。"""
|
||||
|
||||
def _make_broken_tree(
|
||||
self,
|
||||
tmp_path: Path,
|
||||
) -> tuple[TreeIndex, list[NodeIssue]]:
|
||||
"""构建含一个空 frame_summary 的 L3 节点的测试树。"""
|
||||
frame_path = tmp_path / "frames" / "L1_000_L2_000_L3_000.jpg"
|
||||
frame_path.parent.mkdir(parents=True)
|
||||
frame_path.write_bytes(b"\xff\xd8\xff\xe0fake")
|
||||
|
||||
l3 = L3Node(
|
||||
id="vid_L1_000_L2_000_L3_000",
|
||||
card=L3Card("", [], [], [], "", {}),
|
||||
timestamp=1.0,
|
||||
frame_path="frames/L1_000_L2_000_L3_000.jpg",
|
||||
)
|
||||
l2 = L2Node(
|
||||
id="vid_L1_000_L2_000",
|
||||
card=L2Card("原始事件", [], [], [], [], "", None),
|
||||
time_range=(0.0, 10.0),
|
||||
children=[l3],
|
||||
)
|
||||
l1 = L1Node(
|
||||
id="vid_L1_000",
|
||||
card=L1Card("原始场景", "", [], [], [], [], ""),
|
||||
time_range=(0.0, 10.0),
|
||||
children=[l2],
|
||||
)
|
||||
index = TreeIndex(metadata=IndexMeta("/t.mp4", "video"), roots=[l1])
|
||||
issues = [
|
||||
NodeIssue(
|
||||
"vid_L1_000_L2_000_L3_000",
|
||||
3,
|
||||
"empty_field",
|
||||
"frame_summary 为空",
|
||||
)
|
||||
]
|
||||
return index, issues
|
||||
|
||||
def test_repairs_l3_and_cascades(self, tmp_path: Path) -> None:
|
||||
"""修复 L3 后应级联重生成 L2 和 L1。"""
|
||||
index, issues = self._make_broken_tree(tmp_path)
|
||||
stats = asyncio.run(repair_tree(index, issues, MockVLM(), MockLLM(), tmp_path))
|
||||
assert stats.l3_repaired == 1
|
||||
assert stats.l2_regenerated == 1
|
||||
assert stats.l1_regenerated == 1
|
||||
assert index.roots[0].children[0].children[0].card.frame_summary == "修复后的帧描述"
|
||||
assert index.roots[0].children[0].card.event_description == "修复后的事件"
|
||||
assert index.roots[0].card.scene_summary == "修复后的场景"
|
||||
|
||||
def test_no_issues_no_changes(self) -> None:
|
||||
"""无问题时不进行任何修复。"""
|
||||
l3 = L3Node(
|
||||
id="l1_0_l2_0_l3_0",
|
||||
card=L3Card("正常", [], [], [], "", {}),
|
||||
timestamp=1.0,
|
||||
)
|
||||
l2 = L2Node(
|
||||
id="l1_0_l2_0",
|
||||
card=L2Card("正常事件", [], [], [], [], "", None),
|
||||
time_range=(0.0, 10.0),
|
||||
children=[l3],
|
||||
)
|
||||
l1 = L1Node(
|
||||
id="l1_0",
|
||||
card=L1Card("正常场景", "", [], [], [], [], ""),
|
||||
time_range=(0.0, 10.0),
|
||||
children=[l2],
|
||||
)
|
||||
index = TreeIndex(metadata=IndexMeta("/t.mp4", "video"), roots=[l1])
|
||||
stats = asyncio.run(repair_tree(index, [], MockVLM(), MockLLM(), Path("/tmp")))
|
||||
assert stats.l3_repaired == 0
|
||||
assert stats.l2_regenerated == 0
|
||||
assert stats.l1_regenerated == 0
|
||||
|
||||
def test_stats_dataclass(self) -> None:
|
||||
"""RepairStats 数据类字段验证。"""
|
||||
stats = RepairStats(l3_repaired=2, l2_regenerated=1, l1_regenerated=1)
|
||||
assert stats.l3_repaired == 2
|
||||
assert stats.l2_regenerated == 1
|
||||
assert stats.l1_regenerated == 1
|
||||
|
||||
def test_skips_non_empty_field_issues(self, tmp_path: Path) -> None:
|
||||
"""非 empty_field 类型的 issue 不触发 L3 修复。"""
|
||||
l3 = L3Node(
|
||||
id="l1_0_l2_0_l3_0",
|
||||
card=L3Card("正常描述", [], [], [], "", {}),
|
||||
timestamp=1.0,
|
||||
)
|
||||
l2 = L2Node(
|
||||
id="l1_0_l2_0",
|
||||
card=L2Card("原始事件", [], [], [], [], "", None),
|
||||
time_range=(0.0, 10.0),
|
||||
children=[l3],
|
||||
)
|
||||
l1 = L1Node(
|
||||
id="l1_0",
|
||||
card=L1Card("原始场景", "", [], [], [], [], ""),
|
||||
time_range=(0.0, 10.0),
|
||||
children=[l2],
|
||||
)
|
||||
index = TreeIndex(metadata=IndexMeta("/t.mp4", "video"), roots=[l1])
|
||||
issues = [NodeIssue("l1_0_l2_0_l3_0", 3, "missing_frame", "帧文件不存在")]
|
||||
stats = asyncio.run(repair_tree(index, issues, MockVLM(), MockLLM(), tmp_path))
|
||||
assert stats.l3_repaired == 0
|
||||
assert stats.l2_regenerated == 0
|
||||
|
||||
def test_multiple_l3_under_same_l2(self, tmp_path: Path) -> None:
|
||||
"""同一 L2 下多个 L3 修复后，L2 只重生成一次。"""
|
||||
frame_dir = tmp_path / "frames"
|
||||
frame_dir.mkdir(parents=True)
|
||||
for i in range(2):
|
||||
(frame_dir / f"f{i}.jpg").write_bytes(b"\xff\xd8\xff\xe0fake")
|
||||
|
||||
l3_a = L3Node(
|
||||
id="l1_0_l2_0_l3_0",
|
||||
card=L3Card("", [], [], [], "", {}),
|
||||
timestamp=1.0,
|
||||
frame_path="frames/f0.jpg",
|
||||
)
|
||||
l3_b = L3Node(
|
||||
id="l1_0_l2_0_l3_1",
|
||||
card=L3Card("", [], [], [], "", {}),
|
||||
timestamp=2.0,
|
||||
frame_path="frames/f1.jpg",
|
||||
)
|
||||
l2 = L2Node(
|
||||
id="l1_0_l2_0",
|
||||
card=L2Card("原始事件", [], [], [], [], "", None),
|
||||
time_range=(0.0, 10.0),
|
||||
children=[l3_a, l3_b],
|
||||
)
|
||||
l1 = L1Node(
|
||||
id="l1_0",
|
||||
card=L1Card("原始场景", "", [], [], [], [], ""),
|
||||
time_range=(0.0, 10.0),
|
||||
children=[l2],
|
||||
)
|
||||
index = TreeIndex(metadata=IndexMeta("/t.mp4", "video"), roots=[l1])
|
||||
issues = [
|
||||
NodeIssue("l1_0_l2_0_l3_0", 3, "empty_field", "frame_summary 为空"),
|
||||
NodeIssue("l1_0_l2_0_l3_1", 3, "empty_field", "frame_summary 为空"),
|
||||
]
|
||||
vlm = MockVLM()
|
||||
llm = MockLLM()
|
||||
stats = asyncio.run(repair_tree(index, issues, vlm, llm, tmp_path))
|
||||
assert stats.l3_repaired == 2
|
||||
assert stats.l2_regenerated == 1
|
||||
assert stats.l1_regenerated == 1
|
||||
assert vlm.call_count == 2
|
||||
# LLM 应被调用 2 次：一次 L2 + 一次 L1
|
||||
assert llm.call_count == 2
|
||||
|
||||
def test_missing_frame_file_skips_l3(self, tmp_path: Path) -> None:
|
||||
"""帧文件不存在时跳过该 L3 节点的修复。"""
|
||||
l3 = L3Node(
|
||||
id="l1_0_l2_0_l3_0",
|
||||
card=L3Card("", [], [], [], "", {}),
|
||||
timestamp=1.0,
|
||||
frame_path="frames/nonexistent.jpg",
|
||||
)
|
||||
l2 = L2Node(
|
||||
id="l1_0_l2_0",
|
||||
card=L2Card("原始事件", [], [], [], [], "", None),
|
||||
time_range=(0.0, 10.0),
|
||||
children=[l3],
|
||||
)
|
||||
l1 = L1Node(
|
||||
id="l1_0",
|
||||
card=L1Card("原始场景", "", [], [], [], [], ""),
|
||||
time_range=(0.0, 10.0),
|
||||
children=[l2],
|
||||
)
|
||||
index = TreeIndex(metadata=IndexMeta("/t.mp4", "video"), roots=[l1])
|
||||
issues = [NodeIssue("l1_0_l2_0_l3_0", 3, "empty_field", "frame_summary 为空")]
|
||||
stats = asyncio.run(repair_tree(index, issues, MockVLM(), MockLLM(), tmp_path))
|
||||
# 帧文件不存在 → 跳过 L3 修复 → 无级联
|
||||
assert stats.l3_repaired == 0
|
||||
assert stats.l2_regenerated == 0
|
||||
assert stats.l1_regenerated == 0
|
||||
Executable
+75
@@ -0,0 +1,75 @@
|
||||
#!/usr/bin/env bash
|
||||
# 从 TRM4.zip 迁移资产到 TRM5
|
||||
# 用法: bash tools/migrate_from_trm4.sh /path/to/Video-Tree-TRM4.zip
|
||||
set -euo pipefail
|
||||
|
||||
ZIP_PATH="${1:?用法: bash tools/migrate_from_trm4.sh /path/to/Video-Tree-TRM4.zip}"
|
||||
PROJECT_ROOT="$(cd "$(dirname "$0")/.." && pwd)"
|
||||
TMP_DIR=$(mktemp -d)
|
||||
|
||||
echo "=== TRM4 -> TRM5 迁移 ==="
|
||||
echo "ZIP: $ZIP_PATH"
|
||||
echo "项目根: $PROJECT_ROOT"
|
||||
echo "临时目录: $TMP_DIR"
|
||||
|
||||
# 1. 解压
|
||||
echo "[1/6] 解压 TRM4.zip..."
|
||||
unzip -q "$ZIP_PATH" -d "$TMP_DIR"
|
||||
SRC="$TMP_DIR/Video-Tree-TRM4"
|
||||
|
||||
# 2. 拷贝帧文件 (rsync --ignore-existing)
|
||||
echo "[2/6] 拷贝帧文件..."
|
||||
mkdir -p "$PROJECT_ROOT/store/videos"
|
||||
for vid_dir in "$SRC"/store/videos/*/; do
|
||||
vid=$(basename "$vid_dir")
|
||||
dst="$PROJECT_ROOT/store/videos/$vid"
|
||||
mkdir -p "$dst"
|
||||
if [ -d "$vid_dir/frames" ]; then
|
||||
rsync -a --ignore-existing "$vid_dir/frames/" "$dst/frames/"
|
||||
fi
|
||||
done
|
||||
|
||||
# 3. 拷贝 SRT 字幕
|
||||
echo "[3/6] 拷贝 SRT 字幕..."
|
||||
mkdir -p "$PROJECT_ROOT/data/Video-MME/subtitle"
|
||||
if [ -d "$SRC/data/Video-MME/subtitle" ]; then
|
||||
rsync -a --ignore-existing "$SRC/data/Video-MME/subtitle/" "$PROJECT_ROOT/data/Video-MME/subtitle/"
|
||||
fi
|
||||
|
||||
# 4. 拷贝视频压缩包
|
||||
echo "[4/6] 拷贝视频压缩包..."
|
||||
mkdir -p "$PROJECT_ROOT/data/Video-MME/original_data"
|
||||
if [ -d "$SRC/data/Video-MME/original_data" ]; then
|
||||
rsync -a --ignore-existing "$SRC/data/Video-MME/original_data/" "$PROJECT_ROOT/data/Video-MME/original_data/"
|
||||
fi
|
||||
|
||||
# 5. 拷贝问题 JSON
|
||||
echo "[5/6] 拷贝 Benchmark 问题..."
|
||||
mkdir -p "$PROJECT_ROOT/store/questions"
|
||||
if [ -d "$SRC/store/questions" ]; then
|
||||
rsync -a --ignore-existing "$SRC/store/questions/" "$PROJECT_ROOT/store/questions/"
|
||||
fi
|
||||
|
||||
# 6. 格式转换
|
||||
echo "[6/6] 格式转换 flat -> TreeIndex..."
|
||||
conda run -n Video-Tree-TRM python "$PROJECT_ROOT/tools/convert_flat_to_treeindex.py" \
|
||||
"$SRC/store/videos" "$PROJECT_ROOT/store/videos"
|
||||
|
||||
# 验收
|
||||
echo ""
|
||||
echo "=== 验收检查 ==="
|
||||
VIDEO_COUNT=$(find "$PROJECT_ROOT/store/videos" -name "tree.json" | wc -l)
|
||||
SRT_COUNT=$(find "$PROJECT_ROOT/data/Video-MME/subtitle" -name "*.srt" 2>/dev/null | wc -l)
|
||||
echo "视频树: $VIDEO_COUNT (期望 300)"
|
||||
echo "SRT 字幕: $SRT_COUNT (期望 >=290)"
|
||||
|
||||
# 清理
|
||||
echo "清理临时目录..."
|
||||
rm -rf "$TMP_DIR"
|
||||
|
||||
if [ "$VIDEO_COUNT" -lt 300 ]; then
|
||||
echo "WARNING: 视频树数量不足 300，请检查"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
echo "迁移完成"
|
||||
Reference in New Issue
Block a user