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修复看板日志不可见：自动选择正确任务数据源（多工作区） #117

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修复看板日志不可见：自动选择正确任务数据源（多工作区） #117

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87 changes: 78 additions & 9 deletions dashboard/server.py
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Original file line number Diff line number Diff line change
Expand Up @@ -38,6 +38,7 @@
DIST = BASE / 'dist' # React 构建产物 (npm run build)
DATA = BASE.parent / "data"
SCRIPTS = BASE.parent / 'scripts'
_ACTIVE_TASK_DATA_DIR = None

# 静态资源 MIME 类型
_MIME_TYPES = {
Expand Down Expand Up @@ -82,21 +83,84 @@ def now_iso():
return datetime.datetime.now(datetime.timezone.utc).isoformat().replace('+00:00', 'Z')


def load_tasks():
return atomic_json_read(DATA / 'tasks_source.json', [])
def _iter_task_data_dirs():
"""返回可用的任务数据目录候选（优先 workspace，其次本地 data）。"""
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Copilot AI Mar 11, 2026

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_iter_task_data_dirs() 的 docstring 说“优先 workspace，其次本地 data”，但当前实现 dirs = [DATA] 后再 append workspace；在打分相同(或不存在 tasks_source 时回退)的情况下会更倾向选择本地 DATA，和说明不一致。建议要么调整候选顺序/加显式 tie-breaker，要么修正文档描述以匹配实际策略。

Suggested change
"""返回可用的任务数据目录候选（优先 workspace，其次本地 data）。"""
"""返回可用的任务数据目录候选（优先本地 data，其次 workspace）。"""

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dirs = [DATA]
oclaw_home = pathlib.Path.home() / '.openclaw'
for p in sorted(oclaw_home.glob('workspace-*/data')):
Comment on lines +89 to +90
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这里重新计算了 oclaw_home = pathlib.Path.home() / '.openclaw'，而文件顶部已经有可复用且便于测试/patch 的 OCLAW_HOME 常量。建议直接使用 OCLAW_HOME，以免后续需要在测试或部署中重定向 OpenClaw 目录时出现行为不一致。

Suggested change
oclaw_home = pathlib.Path.home() / '.openclaw'
for p in sorted(oclaw_home.glob('workspace-*/data')):
for p in sorted(OCLAW_HOME.glob('workspace-*/data')):

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if p.is_dir():
dirs.append(p)
return dirs


def save_tasks(tasks):
atomic_json_write(DATA / 'tasks_source.json', tasks)
# Trigger refresh (异步，不阻塞，避免僵尸进程)
def _task_source_score(task_file: pathlib.Path):
"""给任务源打分：优先非 demo 任务，其次任务数，再按文件更新时间。"""
try:
tasks = atomic_json_read(task_file, [])
except Exception:
tasks = []
if not isinstance(tasks, list):
tasks = []
non_demo = 0
for t in tasks:
tid = str((t or {}).get('id', ''))
if tid and not tid.startswith('JJC-DEMO'):
non_demo += 1
try:
mtime = task_file.stat().st_mtime
except Exception:
mtime = 0
return (1 if non_demo > 0 else 0, non_demo, len(tasks), mtime)


def get_task_data_dir():
"""自动选择当前任务数据目录，并缓存结果以保持一次服务期内稳定。"""
global _ACTIVE_TASK_DATA_DIR
if _ACTIVE_TASK_DATA_DIR and _ACTIVE_TASK_DATA_DIR.is_dir():
return _ACTIVE_TASK_DATA_DIR

best_dir = DATA
best_score = (-1, -1, -1, -1)
for d in _iter_task_data_dirs():
tf = d / 'tasks_source.json'
Comment on lines +116 to +125
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新增的数据目录自动探测会读取真实用户目录 ~/.openclaw/workspace-*/data，这会让现有的 tests/test_server.py 通过 patch srv.DATA 的方式无法完全隔离测试环境（可能被本机 workspace 的 tasks_source.json“抢走”数据源），导致测试与本地环境耦合。建议补充/调整测试覆盖：在测试里创建 tasks_source.json 并验证 get_task_data_dir() 的选择逻辑可控（或提供可注入/可禁用 workspace 探测的开关）。

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if not tf.exists():
continue
score = _task_source_score(tf)
if score > best_score:
best_score = score
best_dir = d

Comment on lines +119 to +132
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get_task_data_dir() 一旦把 _ACTIVE_TASK_DATA_DIR 缓存成某个目录，就只检查 is_dir() 并直接返回；如果服务启动时没有任何候选包含 tasks_source.json（或后续才在 workspace 生成），缓存会永久锁定到默认 DATA，导致多工作区场景下仍可能读错数据源。建议缓存前至少要求目录内存在 tasks_source.json，或在缓存命中时也验证该文件仍存在/必要时重新探测。

Suggested change
if _ACTIVE_TASK_DATA_DIR and _ACTIVE_TASK_DATA_DIR.is_dir():
return _ACTIVE_TASK_DATA_DIR
best_dir = DATA
best_score = (-1, -1, -1, -1)
for d in _iter_task_data_dirs():
tf = d / 'tasks_source.json'
if not tf.exists():
continue
score = _task_source_score(tf)
if score > best_score:
best_score = score
best_dir = d
# 缓存命中时，既要求目录存在，也要求其中仍有 tasks_source.json
if _ACTIVE_TASK_DATA_DIR and _ACTIVE_TASK_DATA_DIR.is_dir():
if (_ACTIVE_TASK_DATA_DIR / 'tasks_source.json').exists():
return _ACTIVE_TASK_DATA_DIR
# 若缓存目录已不再包含任务源文件，则丢弃缓存并重新探测
_ACTIVE_TASK_DATA_DIR = None
best_dir = DATA
best_score = None
for d in _iter_task_data_dirs():
tf = d / 'tasks_source.json'
if not tf.exists():
continue
score = _task_source_score(tf)
if best_score is None or score > best_score:
best_score = score
best_dir = d
# 仅在找到至少一个包含 tasks_source.json 的目录时才缓存；
# 否则返回默认 DATA，但不缓存，以便后续新建 workspace 时能重新探测。
if best_score is None:
log.info(f'任务数据源: 默认 DATA（未找到 tasks_source.json）')
return best_dir

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_ACTIVE_TASK_DATA_DIR = best_dir
log.info(f'任务数据源: {_ACTIVE_TASK_DATA_DIR}')
return _ACTIVE_TASK_DATA_DIR


def _refresh_live_data_async(task_data_dir: pathlib.Path):
"""触发对应数据目录的 live_status 刷新脚本。"""
script = task_data_dir.parent / 'scripts' / 'refresh_live_data.py'
if not script.exists():
script = SCRIPTS / 'refresh_live_data.py'

def _refresh():
try:
subprocess.run(['python3', str(SCRIPTS / 'refresh_live_data.py')], timeout=30)
subprocess.run(['python3', str(script)], timeout=30)
Comment on lines +138 to +146
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_refresh_live_data_async() 在 workspace 目录下找不到脚本时会回退到仓库 scripts/refresh_live_data.py；但该脚本内部写死使用自身所在目录的 DATA = BASE / 'data'（见 scripts/refresh_live_data.py），会把 live_status.json 写回仓库 data，而不是当前选中的 task_data_dir。这会造成 save_tasks 之后看板仍读取不到最新 live_status。建议让刷新脚本支持传入 dataDir（参数或环境变量），或在回退时显式传递/切换到能写入 task_data_dir 的实现。

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except Exception as e:
log.warning(f'refresh_live_data.py 触发失败: {e}')

threading.Thread(target=_refresh, daemon=True).start()


def load_tasks():
task_data_dir = get_task_data_dir()
return atomic_json_read(task_data_dir / 'tasks_source.json', [])


def save_tasks(tasks):
task_data_dir = get_task_data_dir()
atomic_json_write(task_data_dir / 'tasks_source.json', tasks)
_refresh_live_data_async(task_data_dir)


def handle_task_action(task_id, action, reason):
"""Stop/cancel/resume a task from the dashboard."""
tasks = load_tasks()
Expand Down Expand Up @@ -2124,12 +2188,17 @@ def do_GET(self):
if p in ('', '/dashboard', '/dashboard.html'):
self.send_file(DIST / 'index.html')
elif p == '/healthz':
checks = {'dataDir': DATA.is_dir(), 'tasksReadable': (DATA / 'tasks_source.json').exists()}
checks['dataWritable'] = os.access(str(DATA), os.W_OK)
task_data_dir = get_task_data_dir()
checks = {
'dataDir': task_data_dir.is_dir(),
'tasksReadable': (task_data_dir / 'tasks_source.json').exists(),
}
checks['dataWritable'] = os.access(str(task_data_dir), os.W_OK)
all_ok = all(checks.values())
self.send_json({'status': 'ok' if all_ok else 'degraded', 'ts': now_iso(), 'checks': checks})
elif p == '/api/live-status':
self.send_json(read_json(DATA / 'live_status.json'))
task_data_dir = get_task_data_dir()
self.send_json(read_json(task_data_dir / 'live_status.json'))
elif p == '/api/agent-config':
self.send_json(read_json(DATA / 'agent_config.json'))
elif p == '/api/model-change-log':
Expand Down
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