@@ -0,0 +1,632 @@
---
type: plan
node_id: plan:fix-diagnosis-tree-data-link-plan
title: "实现计划: 修复诊断 tree_data 断链 bug"
date: 2026-07-15
---
# 修复诊断 tree_data 断链 bug Implementation Plan
> **For agentic workers:** REQUIRED SUB-SKILL: Use subagent-driven-development to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
**Goal: ** 接通 TRM4→TRM5 迁移时断掉的诊断树加载环，让 `evaluate_span` 拿到真实 ground_truth、error_type 归因不再坍缩。
**Architecture: ** app 层新增树展平器（递归遍历 tree.json 的嵌套 roots → 扁平 `{"nodes":{id:{card,level,time_range}}}` ），在离线诊断（`video_split_cli` ）与训练循环（`runner` ）两个注入点按诊断涉及的 video 加载填充 `tree_data` ； `run_diagnosis` 的静默回退改为缺失即 fail-loud。core 只消费 dict，不碰归因瀑布（算法保真 §4.7#7 ）。
**Tech Stack: ** Python 3.11、pytest、loguru、asyncio；参考 TRM4 `core/harness/diagnose.py:1677` 的 tree_cache 语义。
---
## 设计来源
`research-wiki/designs/fix-diagnosis-tree-data-link.md` （已含 Codex 审查修订）。
## 文件结构映射
| 文件 | 动作 | 责任 |
|------|------|------|
| `app/harness/tree_nodes.py` | 新建 | 树展平器：`load_tree_nodes` + `load_tree_data_for_videos` |
| `core/evolution/diagnose.py` | 改 `:2144-2145` | 视频未覆盖即 raise（
| `app/harness/video_split_cli.py` | 改 `build_diagnosis_deps` (`:262-337` ) + `_execute_real` (`:590-600` ) | 离线注入：wrong_ids→video 加载填充 tree_data |
| `app/harness/runner.py` | 改 `_run_diagnosis` (`:2163-2187` ) | 训练注入：question_ids→video 加载注入 |
| `tests/unit/test_tree_nodes.py` | 新建 | 展平器单测 |
| `tests/integration/test_baseline_diagnosis.py` | 改 `:99` | 更新传 `tree_data={}` 的用例为真实/伪造树 |
| `tests/integration/test_diagnosis_tree_link.py` | 新建 | ground_truth 接通 + 依赖方向 |
## 关键代码事实（Codex 已核验）
- 仅 `L1Node` 有 `to_dict` （ `app/tree/index.py:260` ）；L2/L3 为其内部闭包；输出无 `level` 、L3 用 `timestamp` 无 `time_range` → **不走对象层，直接遍历 json ** 。
- node_id 累积式 `..._L1_000_L2_000_L3_000` → level **按遍历深度赋值 ** ，不解析 node_id。
- `GeneratedQuestion.video_id: str` （ `core/types.py:60` ）；`load_questions_by_id(dir) -> dict[str, GeneratedQuestion]` （ `video_split_cli.py:443` ）。
- `run_diagnosis` else 分支已支持 `{video_id: {...}}` 形态（`diagnose.py:2068-2074` ）。
- `diagnose.py:2145` 的 `td = ...get(vid,{})` 在 `:2148` try 之前 → 在此处 raise **不会**被 `:2159` 的 `except ValueError` （
- store 根 = `Path("store")` ， `store/videos/<vid>/tree.json` （与 `factory.py:85` 一致）。
---
### Task 1: 树展平器 `app/harness/tree_nodes.py`
**Files: **
- Create: `app/harness/tree_nodes.py`
- Test: `tests/unit/test_tree_nodes.py`
- [ ] **Step 1: 写失败测试（正确性 + level + fail-loud） **
``` python
# tests/unit/test_tree_nodes.py
""" 树展平器单测：用真实 store/videos/0RxMZBLeqRI/tree.json 验证展平正确性与 fail-loud。 """
import json
from pathlib import Path
import pytest
from app . harness . tree_nodes import load_tree_data_for_videos , load_tree_nodes
_STORE = Path ( " store " )
_VID = " 0RxMZBLeqRI " # 真实样本，111 节点
def _recursive_count ( tree_json : dict ) - > int :
def walk ( n : dict ) - > int :
return 1 + sum ( walk ( c ) for c in ( n . get ( " children " ) or [ ] ) )
return sum ( walk ( r ) for r in tree_json [ " roots " ] )
def test_load_tree_nodes_flattens_all_nodes ( ) :
result = load_tree_nodes ( _STORE , _VID )
assert set ( result . keys ( ) ) == { " nodes " }
nodes = result [ " nodes " ]
raw = json . loads ( ( _STORE / " videos " / _VID / " tree.json " ) . read_text ( encoding = " utf-8 " ) )
assert len ( nodes ) == _recursive_count ( raw )
sample = next ( iter ( nodes . values ( ) ) )
assert set ( sample . keys ( ) ) == { " card " , " level " , " time_range " }
assert isinstance ( sample [ " card " ] , dict )
def test_level_assigned_by_depth_not_node_id ( ) :
nodes = load_tree_nodes ( _STORE , _VID ) [ " nodes " ]
l1_id = f " { _VID } _L1_000 "
l3_id = f " { _VID } _L1_000_L2_000_L3_000 "
assert nodes [ l1_id ] [ " level " ] == 1
assert nodes [ l3_id ] [ " level " ] == 3 # 若按 node_id 首个 _L\d_ 会误判成 1
def test_missing_tree_raises_file_not_found ( ) :
with pytest . raises ( FileNotFoundError ) :
load_tree_nodes ( _STORE , " __no_such_video__ " )
def test_empty_roots_raises_value_error ( tmp_path ) :
vdir = tmp_path / " videos " / " vX "
vdir . mkdir ( parents = True )
( vdir / " tree.json " ) . write_text ( json . dumps ( { " metadata " : { } , " roots " : [ ] } ) , encoding = " utf-8 " )
with pytest . raises ( ValueError ) :
load_tree_nodes ( tmp_path , " vX " )
def test_load_for_videos_dedups ( ) :
data = load_tree_data_for_videos ( _STORE , [ _VID , _VID ] )
assert set ( data . keys ( ) ) == { _VID }
assert data [ _VID ] [ " nodes " ]
```
- [ ] **Step 2: 运行确认失败 **
Run: `conda run -n Video-Tree-TRM pytest tests/unit/test_tree_nodes.py -q`
Expected: FAIL（ `ModuleNotFoundError: No module named 'app.harness.tree_nodes'` ）
- [ ] **Step 3: 实现展平器 **
``` python
# app/harness/tree_nodes.py
""" 诊断侧树读取适配：把嵌套 tree.json 展平成诊断消费的扁平 nodes dict。
诊断编排（core/evolution/diagnose.py）期望 tree_data 形如
{ " nodes " : { node_id: { card, level, time_range}}}，但 TRM5 建树产物
store/videos/<vid>/tree.json 是嵌套 { " metadata " , " roots " :[...]}。本模块递归展平，
接通 TRM4→TRM5 迁移时断掉的 ground_truth 加载环。
不走 TreeIndex 对象层：仅 L1Node 有 to_dict（
且 to_dict 输出无 level、L3 用 timestamp 无 time_range。直接遍历 json 更省且零改建树模块。
"""
from __future__ import annotations
import json
from pathlib import Path
from typing import Any
def load_tree_nodes ( store_dir : Path , video_id : str ) - > dict [ str , Any ] :
""" 加载单视频 tree.json 并展平成扁平 nodes dict。
参数:
store_dir: store 根目录（含 videos/<video_id>/tree.json）。
video_id: 视频标识。
返回:
{ " nodes " : { node_id: { " card " : dict, " level " : int, " time_range " : list}}}。
异常:
FileNotFoundError: tree.json 不存在（沿用 factory.py fail-loud 先例）。
ValueError: 树无有效 roots、节点缺 id、或展平后 nodes 为空。
关键实现:
level 由遍历深度赋值（root=1/child=2/孙=3），不解析 node_id——node_id 累积式
（
L3 无 time_range，用 timestamp 合成 [t, t]。
"""
tree_path = store_dir / " videos " / video_id / " tree.json "
if not tree_path . exists ( ) :
raise FileNotFoundError ( f " 树索引文件不存在: { tree_path } （诊断需真实树，P5 fail loud） " )
tree = json . loads ( tree_path . read_text ( encoding = " utf-8 " ) )
roots = tree . get ( " roots " )
if not isinstance ( roots , list ) or not roots :
raise ValueError ( f " 树无有效 roots: { tree_path } " )
nodes : dict [ str , Any ] = { }
def _walk ( node : dict [ str , Any ] , level : int ) - > None :
node_id = node . get ( " id " )
if not isinstance ( node_id , str ) or not node_id :
raise ValueError ( f " 节点缺 id: { tree_path } " )
time_range = node . get ( " time_range " )
if time_range is None :
ts = node . get ( " timestamp " )
time_range = [ ts , ts ] if ts is not None else [ 0 , 0 ]
nodes [ node_id ] = {
" card " : node . get ( " card " , { } ) ,
" level " : level ,
" time_range " : time_range ,
}
for child in node . get ( " children " , [ ] ) or [ ] :
_walk ( child , level + 1 )
for root in roots :
_walk ( root , 1 )
if not nodes :
raise ValueError ( f " 展平后 nodes 为空: { tree_path } " )
return { " nodes " : nodes }
def load_tree_data_for_videos ( store_dir : Path , video_ids : list [ str ] ) - > dict [ str , Any ] :
""" 按一组 video_id 去重加载展平树，供诊断按 video 注入。
参数:
store_dir: store 根目录。
video_ids: 视频标识列表（可含重复，内部按首次出现顺序去重）。
返回:
{ video_id: { " nodes " : { ...}}}。
异常:
同 load_tree_nodes（任一视频树缺失/无效即 fail-loud）。
"""
return { vid : load_tree_nodes ( store_dir , vid ) for vid in dict . fromkeys ( video_ids ) }
```
- [ ] **Step 4: 运行确认通过 **
Run: `conda run -n Video-Tree-TRM pytest tests/unit/test_tree_nodes.py -q`
Expected: PASS（ ）
- [ ] **Step 5: Commit **
``` bash
git add app/harness/tree_nodes.py tests/unit/test_tree_nodes.py
git commit -m "feat: add tree.json flattener for diagnosis ground_truth"
```
---
### Task 2: core 视频覆盖 fail-loud（ ）
**Files: **
- Modify: `core/evolution/diagnose.py:2144-2145`
- Modify: `tests/integration/test_baseline_diagnosis.py:99` （更新受影响用例）
- [ ] **Step 1: 写失败测试（缺树 video → raise，不降级） **
在 `tests/integration/test_baseline_diagnosis.py` 追加：
``` python
@pytest.mark.asyncio
async def test_run_diagnosis_raises_when_video_tree_missing ( ) :
""" 诊断视频未被 tree_data 覆盖时 fail-loud（不静默回退、不走 judge 降级）。 """
from core . evolution . diagnose import run_diagnosis
q = _make_one_wrong_question ( video_id = " vMISS " , question_id = " vMISS-1 " )
with pytest . raises ( ValueError , match = " 诊断视频树未覆盖 " ) :
await run_diagnosis (
run_id = " infer_adhoc " ,
questions = [ q ] ,
tree_data = { " vOTHER " : { " nodes " : { } } } , # 故意不含 vMISS
llm = _FakeLLM ( ) ,
run_log = _fake_run_log_with_one_wrong ( q ) ,
skill_store = _FakeSkillStore ( ) ,
prompts = _fake_diagnose_prompts ( ) ,
concurrency = 1 ,
question_ids = [ " vMISS-1 " ] ,
)
```
> helper（
- [ ] **Step 2: 运行确认失败 **
Run: `conda run -n Video-Tree-TRM pytest tests/integration/test_baseline_diagnosis.py::test_run_diagnosis_raises_when_video_tree_missing -q`
Expected: FAIL（当前静默回退 `{}` ，不抛异常）
- [ ] **Step 3: 改 core 加 fail-loud **
`core/evolution/diagnose.py` 的 `_process_question` ，把 `:2144-2145` 的：
``` python
vid = prediction . get ( " video_id " , " " )
td = tree_data_by_video . get ( vid , { } )
```
改为（位置在 `:2148` 的 `try` 之前，故不被 `:2159` 的 `except ValueError` 吞）：
``` python
vid = prediction . get ( " video_id " , " " )
if vid not in tree_data_by_video :
# P5 fail-loud：诊断需真实树，调用方须为每个诊断视频加载 tree_data；
# 静默回退空树会让 ground_truth 恒空、error_type 归因坍缩（本次修复的根因）。
raise ValueError (
f " 诊断视频树未覆盖: video_id= { vid !r} 不在注入的 tree_data 中 "
" （调用方须为每个诊断视频加载树，P5 fail loud） "
)
td = tree_data_by_video [ vid ]
```
- [ ] **Step 4: 更新既有传 `tree_data={}` 的三处用例 **
`tests/integration/test_baseline_diagnosis.py` 有**三处** `tree_data={}` （ `:99` / `:224` / `:311` ，形参分别在 `:66` / `:197` / `:283` ）。逐处判断：
- 若该用例**真诊断题**（ `wrong_ids` 非空、进 `run_diagnosis` ）→ 改为覆盖其诊断 video 的伪造树：
```python
tree_data={"<该用例的 video_id>": {"nodes": {"<node_id>": {"card": {}, "level": 1, "time_range": [0, 0]}}}},
` ``
（ video_id`/` node_id` 填该用例 prediction 实际用的值。）
- 若该用例期望**"无题诊断"早返回**（ wrong_ids=[]`，不进 ` run_diagnosis`）→ ` tree_data={}` 可保留，并在该用例加一行注释说明豁免原因。
逐处核对：读每个用例构造的 prediction 是否 ` correct=0` 且被诊断——是则改树，否则注释豁免。
- [ ] **Step 4b: 全仓兜底扫描其它 ` tree_data={}` 调用点**
Run: ` conda run -n Video-Tree-TRM grep -rn "tree_data={}\|tree_data = {}" tests/ app/`
对每个命中判断：进 ` run_diagnosis` 且诊断非空题的必须提供覆盖树；dry-run ` fake_deps`（ video_split_cli.py` 内，` wrong_ids=[]` 早返回）豁免。确保 core fail-loud 不误伤既有用例。
- [ ] **Step 5: 运行确认通过**
Run: ` conda run -n Video-Tree-TRM pytest tests/integration/test_baseline_diagnosis.py -q`
Expected: PASS
- [ ] **Step 6: Commit**
` ``bash
git add core/evolution/diagnose.py tests/integration/test_baseline_diagnosis.py
git commit -m "fix: fail loud when diagnosis video tree not covered (algo #7 input)"
` ``
---
### Task 3: 离线注入（` video_split_cli.py`）
**Files:**
- Modify: ` app/harness/video_split_cli.py`（新增 ` _DEFAULT_STORE_DIR` + ` --store-dir` CLI、` _resolve_paths` 返回 store_dir、改 ` build_diagnosis_deps` 签名与 tree_data、` _execute_real` 传 store_dir/video_ids、删模块顶层假注释 ` :19-21`）
- Modify: ` tests/unit/test_video_split_cli.py:269-273` 与 ` :290-292`（两处旧调用补 ` store_dir`/` video_ids`，否则改签名后先抛 TypeError 而非期望的 SystemExit）
- Test: ` tests/unit/test_video_split_cli_tree_inject.py`（新建）
- [ ] **Step 1: 写失败测试（build_diagnosis_deps 填充真实树）**
` ``python
# tests/unit/test_video_split_cli_tree_inject.py
"""离线诊断注入：build_diagnosis_deps 按 video_ids 填充非空 tree_data。"""
from pathlib import Path
from unittest.mock import patch
from app.harness.video_split_cli import build_diagnosis_deps
def test_build_diagnosis_deps_loads_tree_for_videos():
with patch("app.harness.video_split_cli._DiagLLMSettings") as S, \
patch("adapters.llm.GovernedLLMClient"), \
patch("adapters.telemetry.SQLiteTelemetryRecorder"), \
patch("app.harness.video_split_cli._build_redis_cache", return_value=None):
s = S.return_value
s.search_llm_model = "deepseek-v4-pro"
s.search_llm_base_url = "http://x"
s.search_llm_api_key = "k"
s.llm_circuit_breaker_threshold = 32
s.llm_circuit_breaker_cooldown = 60
s.llm_timeout = s.llm_ttft_timeout = s.llm_inter_token_timeout = 60
s.llm_max_retries = 1
s.llm_retry_base_delay = s.llm_retry_max_delay = 1
deps = build_diagnosis_deps(
harness_db=Path("workspaces/default/harness.db"),
store_dir=Path("store"),
video_ids=["0RxMZBLeqRI"],
concurrency=1,
expected_model="deepseek-v4-pro",
)
assert "0RxMZBLeqRI" in deps.tree_data
assert deps.tree_data["0RxMZBLeqRI"]["nodes"]
` ``
> ` GovernedLLMClient` / ` SQLiteTelemetryRecorder` 在 ` build_diagnosis_deps` 内是函数级 import， adapters.llm` / ` adapters.telemetry`）。测试目的仅验证 ` deps.tree_data` 被真实树填充；若装配桩不足以走到 return，可进一步 patch ` RunLogImpl`/` VersionedSkillStore`。
- [ ] **Step 2: 运行确认失败**
Run: ` conda run -n Video-Tree-TRM pytest tests/unit/test_video_split_cli_tree_inject.py -q`
Expected: FAIL（当前 ` build_diagnosis_deps` 无 ` store_dir`/` video_ids` 参数 → ` TypeError`）
- [ ] **Step 3: 加常量 + ` --store-dir` + ` _resolve_paths` + 删模块假注释 + 改签名 + 填 tree_data**
(a) ` app/harness/video_split_cli.py` 路径常量区（` :65-67` 附近）新增：
` ``python
_DEFAULT_STORE_DIR = Path("store") # tree.json 在 store/videos/<vid>/
` ``
(b) argparse（ :732` ` --out-dir` 之后）新增：
` ``python
parser.add_argument("--store-dir", type=Path, default=None, dest="store_dir")
` ``
(c) ` _resolve_paths`（ :582-587`）改为返回 4 元组（含 store_dir）：
` ``python
def _resolve_paths(args: argparse.Namespace) -> tuple[Path, Path, Path, Path]:
"""解析 harness_db / questions_dir / out_dir / store_dir（
harness_db = args.harness_db or _DEFAULT_HARNESS_DB
questions_dir = args.questions_dir or _DEFAULT_QUESTIONS_DIR
out_dir = args.out_dir or _DEFAULT_OUT_DIR
store_dir = args.store_dir or _DEFAULT_STORE_DIR
return harness_db, questions_dir, out_dir, store_dir
` ``
(d) 删模块顶层假注释：` app/harness/video_split_cli.py:19-21` 把 “+ tree_data={}（由诊断管线内部按需加载）” 改为 “+ tree_data 按 wrong_ids 涉及 video 预加载（store/videos/<vid>/tree.json 展平）”。
(e) ` build_diagnosis_deps` 签名（` :262-264`）改为：
` ``python
def build_diagnosis_deps(
*,
harness_db: Path,
store_dir: Path,
video_ids: list[str],
concurrency: int,
expected_model: str,
) -> DiagnosisDeps:
` ``
函数末尾 ` return DiagnosisDeps(...)`（ :330-337`）改为按 video 加载（并删 docstring 里"tree_data={} 由诊断管线内部按需加载"假注释）：
` ``python
from app.harness.tree_nodes import load_tree_data_for_videos
return DiagnosisDeps(
run_log=RunLogImpl(str(harness_db)),
llm=llm,
skill_store=VersionedSkillStore(_diagnosis_skills_dir()),
prompts=_load_diagnose_prompts(),
tree_data=load_tree_data_for_videos(store_dir, video_ids),
concurrency=concurrency,
)
` ``
- [ ] **Step 4: ` _execute_real` 解包 store_dir 并算 video_ids 传入**
` app/harness/video_split_cli.py:592`（解包改 4 元组）+ ` :595-600`：
` ``python
harness_db, questions_dir, out_dir, store_dir = _resolve_paths(args)
if not harness_db.exists():
raise SystemExit(f"harness.db 不存在: {harness_db}（ ）
canonical_preds = load_canonical_predictions(harness_db, config.baseline_run_id)
wrong_ids = select_diagnosable_wrong_ids(canonical_preds)
questions = load_questions_by_id(questions_dir)
video_ids = [questions[qid].video_id for qid in wrong_ids]
deps = build_diagnosis_deps(
harness_db=harness_db,
store_dir=store_dir,
video_ids=video_ids,
concurrency=args.concurrency,
expected_model=config.model,
)
` ``
> 全仓其它 ` _resolve_paths(args)` 解包处（如 dry-run ` _execute_dry` 路径若有）同步改 4 元组解包，避免 ` ValueError: too many values to unpack`。先 ` grep -n "_resolve_paths(args)" app/harness/video_split_cli.py` 逐处核对。
- [ ] **Step 5: 更新受签名影响的既有单测**
` tests/unit/test_video_split_cli.py:269-273` 与 ` :290-292` 两处 ` cli.build_diagnosis_deps(...)` 调用补必填参数（这俩测试验的是**凭证/模型漂移 fail-loud（ ） video_ids` 传空即可）：
` ``python
cli.build_diagnosis_deps(
harness_db=tmp_path / "h.db",
store_dir=tmp_path,
video_ids=[],
concurrency=2,
expected_model="deepseek-v4-pro",
)
` ``
（两处调用都照此加 ` store_dir=tmp_path, video_ids=[]`。）
- [ ] **Step 6: 运行确认通过 + 回归**
Run: ` conda run -n Video-Tree-TRM pytest tests/unit/test_video_split_cli_tree_inject.py tests/unit/test_video_split_cli.py tests/unit/test_generate_questions.py -q`
Expected: PASS
- [ ] **Step 7: Commit**
` ``bash
git add app/harness/video_split_cli.py tests/unit/test_video_split_cli_tree_inject.py tests/unit/test_video_split_cli.py
git commit -m "fix: load real tree_data for offline diagnosis (video_split_cli)"
` ``
---
### Task 4: 训练注入（` runner._run_diagnosis`）
**Files:**
- Modify: ` app/harness/runner.py:2163-2187`
- Test: ` tests/unit/test_runner_diag_tree_inject.py`
- [ ] **Step 1: 写失败测试（_run_diagnosis 注入非空树）**
` ``python
# tests/unit/test_runner_diag_tree_inject.py
"""训练循环诊断注入：_run_diagnosis 按 batch question_ids 加载真实树注入 run_diagnosis。"""
from unittest.mock import AsyncMock, patch
import pytest
@pytest.mark.asyncio
async def test_run_diagnosis_injects_tree_data(runner_with_real_store):
"""question_ids 对应的 video 树被加载并作为 tree_data 传入 run_diagnosis。"""
captured = {}
async def _fake_run_diagnosis(**kwargs):
captured["tree_data"] = kwargs["tree_data"]
return _empty_diagnosis_result()
with patch("core.evolution.diagnose.run_diagnosis", new=AsyncMock(side_effect=_fake_run_diagnosis)):
await runner_with_real_store._run_diagnosis("infer_adhoc", question_ids=["604-2"])
assert "0RxMZBLeqRI" in captured["tree_data"] # 604-2 属于 0RxMZBLeqRI
assert captured["tree_data"]["0RxMZBLeqRI"]["nodes"]
` ``
> ` runner_with_real_store` fixture：构造 ` self._config.store_dir="store"`、` self._paths.questions_dir` 指向含 604-2 的真实 benchmark 的 runner（复用该测试目录已有 runner helper；若无，最小构造使 ` load_benchmark` 能取到 604-2）。` _empty_diagnosis_result()`：返回 ` DiagnosisResult` 空壳（error_attributions=[]、infra=[]、degraded=[]）。` _run_diagnosis` 内 ` run_diagnosis` 为函数级 import， core.evolution.diagnose.run_diagnosis`。
- [ ] **Step 2: 运行确认失败**
Run: ` conda run -n Video-Tree-TRM pytest tests/unit/test_runner_diag_tree_inject.py -q`
Expected: FAIL（当前 ` tree_data={}` → captured 不含 ` 0RxMZBLeqRI`）
- [ ] **Step 3: 改 ` _run_diagnosis` 注入树**
` app/harness/runner.py:2172-2187`，在 ` questions = load_benchmark(...)` 后、` run_diagnosis(...)` 调用处：
` ``python
questions = load_benchmark(self._paths.questions_dir)
run_log = RunLogImpl(str(self._paths.db_path))
skill_store = VersionedSkillStore(self._paths.skills_dir)
diagnose_prompts = self._load_diagnose_prompts()
from app.harness.tree_nodes import load_tree_data_for_videos
if question_ids is not None:
qid_set = set(question_ids)
video_ids = [q.video_id for q in questions if q.question_id in qid_set]
else:
video_ids = [q.video_id for q in questions]
tree_data = load_tree_data_for_videos(Path(self._config.store_dir), video_ids)
return await run_diagnosis(
run_id=run_id,
questions=questions,
tree_data=tree_data,
llm=self._llm,
run_log=run_log,
skill_store=skill_store,
prompts=diagnose_prompts,
concurrency=self._config.concurrency,
question_ids=question_ids,
)
` ``
（删 ` tree_data={}, # tree_data 由诊断管线内部按需加载` 假注释；确认文件顶部已 ` from pathlib import Path`，否则补 import。）
- [ ] **Step 4: 运行确认通过**
Run: ` conda run -n Video-Tree-TRM pytest tests/unit/test_runner_diag_tree_inject.py -q`
Expected: PASS
- [ ] **Step 5: Commit**
` ``bash
git add app/harness/runner.py tests/unit/test_runner_diag_tree_inject.py
git commit -m "fix: load real tree_data for training-loop diagnosis (runner)"
` ``
---
### Task 5: 集成验证 ground_truth 接通 + 依赖方向
**Files:**
- Create: ` tests/integration/test_diagnosis_tree_link.py`
- [ ] **Step 1: 写 integration 测试（ground_truth 非空 + 依赖方向）**
` ``python
# tests/integration/test_diagnosis_tree_link.py
"""集成验证：真实树注入后 evaluate_span 收到非空 ground_truth；
from pathlib import Path
from app.harness.tree_nodes import load_tree_nodes
from core.evolution.diagnose import _get_ground_truth_for_trace
def test_ground_truth_nonempty_with_real_tree():
"""对真实 T2 样本 604-2（
td = load_tree_nodes(Path("store"), "0RxMZBLeqRI")
node_id = "0RxMZBLeqRI_L1_000" # 该视频真实存在的节点
gt = _get_ground_truth_for_trace(td, "view_node", {"node_id": node_id})
assert gt and gt != "{}" # 拿到该节点 card 的 JSON，非空
def test_core_diagnose_does_not_import_app():
"""算法保真 + 依赖方向：core/evolution/diagnose.py 不 import app。"""
src = Path("core/evolution/diagnose.py").read_text(encoding="utf-8")
assert "import app." not in src
assert "from app." not in src
` ``
- [ ] **Step 2: 运行确认通过**
Run: ` conda run -n Video-Tree-TRM pytest tests/integration/test_diagnosis_tree_link.py -q`
Expected: PASS
- [ ] **Step 3: 全量回归**
Run: ` conda run -n Video-Tree-TRM pytest tests/ -q`
Expected: PASS（无回归；诊断相关用例因 core fail-loud 需补树的已在 Task 2 Step 4 处理）
- [ ] **Step 4: Commit**
` ``bash
git add tests/integration/test_diagnosis_tree_link.py
git commit -m "test: integration for diagnosis tree_data link + core dep direction"
` ``
---
## 重跑与重冻衔接（代码计划外的运行步骤）
代码合入后 git short SHA 变 → ` diag_fingerprint` 变 → 需全量重跑：
1. **重跑诊断 + 重冻切分**（一条命令走完两阶段）：
` CUDA_VISIBLE_DEVICES=0 CONCURRENCY=12 bash scripts/build_video_split.sh`
2. **实测校验 tier**：重跑后查新 fingerprint 的 ` baseline_diagnosis`，确认 ` T2≈82 / T1≈152`（缓存命中预期）；偏差需归因（设计 §6：C3 异常吞并等非 tree_data 不稳定源）。
3. **观察 error_type 恢复多值**：确认 ` error_type` 不再 100% extraction_failure、` evolution_target` 不再全 tool（软验收，充分性依赖 judge）。
4. **接受 pools.json 成员变化**：
## 算法保真校验（§4.7）
| 算法 | 是否涉及 | 结论 |
|------|---------|------|
| #7 诊断瀑布 | 是（仅接通输入） | **不改** ` attribute_error`（ diagnose.py:910-941`）、severity 函数、defect/lapse 判定；Task 2 仅在 ` _process_question` 加 fail-loud 输入护栏。参考 TRM4 ` core/harness/diagnose.py:1677` tree_cache 语义对齐 ground_truth。 |
| #12 训练循环编排 | 是（仅换 tree_data 来源） | ` runner._run_diagnosis` 只把 ` tree_data={}` 换成真实加载，不改三级嵌套/慢更新/断点续训。 |
| 其余 11 项 | 否 | 不涉及。 |
## 验收标准
- 5 个 Task 全绿；` pytest tests/` 无回归。
- ` evaluate_span`/` _get_ground_truth_for_trace` 在真实树下拿到非空 ground_truth（
- ` core/evolution/diagnose.py` 不 import app（依赖方向）。
- 两**生产注入点**（离线 ` build_diagnosis_deps` + 训练 ` _run_diagnosis`）均加载真实树。允许保留 ` tree_data={}` 的**豁免场景**： fake_deps`（ wrong_ids=[]` 早返回）、以及测试里走"无题诊断早返回"路径的用例（须带注释说明）。Step 4b 的 grep 兜底确保无遗漏的会真正进 ` run_diagnosis` 的空树调用。
