feat(agent): 工具结果UI显示层取消500字硬截——params可配上限(默认50000≈完整显示)+超限显式告知(2026-09-15用户指令:显示完整信息)。显示层与回填层(12000防爆门禁)分离,resolve_max_chars提取共享_resolve_param_int,新增cap_display_result/resolve_display_max_chars(params键tool_result_display_max_chars)
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ymq
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@ -266,11 +266,14 @@ class AgentExecutor:
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result = await self._execute_tool(pending_tool, pending_params)
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if not result.startswith("未知工具") and not result.startswith("ERROR"):
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self._tool_call_count += 1
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yield json.dumps({"type": "tool_result", "tool": pending_tool, "result": result[:500]}, ensure_ascii=False) + "\n"
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# 显示层上限（2026-09-15 用户要求完整显示，替代旧硬截 [:500]）：
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# 默认 50000 字符 = 正常工具输出完整显示；超限显式告知（绝不静默截断）。
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from .result_cap import cap_tool_result, cap_display_result, resolve_max_chars, resolve_display_max_chars
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yield json.dumps({"type": "tool_result", "tool": pending_tool,
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"result": cap_display_result(result, await resolve_display_max_chars())}, ensure_ascii=False) + "\n"
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# 回填上限（2026-09-11）：工具结果全文回填会撑爆上下文（商机产线实测
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# 8 次数据工具 ~78K token → 压缩摘要自身超时 → 会话零产出）。
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# 截断显式告知 + 给缩小范围指引，让 LLM 自己改策略。
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from .result_cap import cap_tool_result, resolve_max_chars
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_capped, _ = cap_tool_result(result, await resolve_max_chars())
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self._msgs.append({"role": "tool", "tool_call_id": fake_id, "content": _capped})
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# 不 return，继续进入 Tool Loop，让 LLM 基于工具结果继续后续步骤
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@ -411,8 +414,11 @@ class AgentExecutor:
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await self._save_turn(user_input, f"[提问] {question}")
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return
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# 显示层上限（同 Step 4.5，默认 50000 = 完整显示；超限显式告知）
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from .result_cap import cap_display_result, resolve_display_max_chars
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yield json.dumps({
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"type": "tool_result", "tool": tool_name, "result": result[:500],
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"type": "tool_result", "tool": tool_name,
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"result": cap_display_result(result, await resolve_display_max_chars()),
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}, ensure_ascii=False) + "\n"
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# 原生回填：role=tool + tool_call_id
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@ -515,9 +521,11 @@ class AgentExecutor:
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await self._save_turn(user_input, f"[提问] {question}")
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return
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# 显示层上限（同 native 路径，默认 50000 = 完整显示；超限显式告知）
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from .result_cap import cap_display_result, resolve_display_max_chars
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yield json.dumps({
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"type": "tool_result", "tool": tool_name,
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"result": result[:500],
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"result": cap_display_result(result, await resolve_display_max_chars()),
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}, ensure_ascii=False) + "\n"
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# 反馈给 LLM（关键：不存原始 tool_call JSON）
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@ -28,6 +28,51 @@ _PARAM_KEY = "tool_result_max_chars"
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# 进程内缓存（None = 未解析，惰性读 params；invalidate_cache() 清除）
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_cached_max: Optional[int] = None
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# ── UI 显示层上限（2026-09-15，用户要求「显示完整信息，不要裁剪」）──
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# 历史行为：agent_loop_v2 yield tool_result 事件时硬截 result[:500] 且无提示
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# （静默截断，违反 file_read 的「绝不静默截断」纪律），前端看到半截输出。
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# 显示层与回填层是两条独立通道：显示只影响人眼，不进模型上下文，
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# 因此上限可以远高于回填上限。默认 50000 字符覆盖所有正常工具输出
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# （load_skill 全文 / diagnose_project / read_file 分页 ≈ 数千~3万字符），
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# 等于完整显示；只兜底 run_command 输出数 MB 的病态情况（防 NDJSON
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# 流 + 前端 MdWidget 渲染卡死）。要完全不限：params 表设大值即可，无需改码。
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DEFAULT_DISPLAY_MAX_CHARS = 50000
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_PARAM_DISPLAY_KEY = "tool_result_display_max_chars"
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_cached_display_max: Optional[int] = None
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async def _resolve_param_int(param_key: str, default: int, floor: int, cache_attr: str, sor=None) -> int:
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"""从 params 表读整型配置（进程内缓存；读失败一律兜底常量，绝不打断主循环）。
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sor 非 None 时复用调用方现成连接（v1 agent_loop 路径）；否则自开短连接。
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"""
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cached = globals().get(cache_attr)
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if cached is not None:
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return cached
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val = default
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try:
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from .workspace import get_param
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if sor is not None:
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raw = await get_param(sor, param_key, "")
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else:
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from sqlor.dbpools import DBPools
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db = DBPools()
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if not db.databases:
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from appPublic.jsonConfig import getConfig
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cfg = getConfig()
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if cfg and cfg.databases:
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db.databases = cfg.databases
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async with db.sqlorContext("pipeline") as _sor:
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raw = await get_param(_sor, param_key, "")
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await _sor.sqlExe("COMMIT", {})
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if raw not in (None, ""):
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val = max(floor, int(float(raw)))
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except Exception as e:
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logger.debug("resolve %s fallback to default: %s", param_key, str(e)[:120])
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val = default
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globals()[cache_attr] = val
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return val
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async def resolve_max_chars(sor=None):
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"""取回填上限（params 表优先，失败/未配置用常量兜底，进程内缓存）。
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@ -39,29 +84,18 @@ async def resolve_max_chars(sor=None):
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global _cached_max
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if _cached_max is not None:
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return _cached_max
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val = DEFAULT_MAX_CHARS
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try:
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from .workspace import get_param
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if sor is not None:
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raw = await get_param(sor, _PARAM_KEY, "")
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else:
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from sqlor.dbpools import DBPools
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db = DBPools()
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if not db.databases:
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from appPublic.jsonConfig import getConfig
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cfg = getConfig()
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if cfg and cfg.databases:
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db.databases = cfg.databases
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async with db.sqlorContext("pipeline") as _sor:
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raw = await get_param(_sor, _PARAM_KEY, "")
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await _sor.sqlExe("COMMIT", {})
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if raw not in (None, ""):
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val = max(1000, int(float(raw)))
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except Exception as e:
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logger.debug("resolve_max_chars fallback to default: %s", str(e)[:120])
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val = DEFAULT_MAX_CHARS
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_cached_max = val
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return val
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_cached_max = await _resolve_param_int(_PARAM_KEY, DEFAULT_MAX_CHARS, 1000, "_cached_max", sor)
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return _cached_max
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async def resolve_display_max_chars():
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"""取 UI 显示层上限（params.tool_result_display_max_chars，默认 50000）。"""
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global _cached_display_max
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if _cached_display_max is not None:
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return _cached_display_max
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_cached_display_max = await _resolve_param_int(
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_PARAM_DISPLAY_KEY, DEFAULT_DISPLAY_MAX_CHARS, 500, "_cached_display_max")
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return _cached_display_max
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def cap_tool_result(result, max_chars=None):
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@ -87,7 +121,28 @@ def cap_tool_result(result, max_chars=None):
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return text[:limit] + notice, True
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def cap_display_result(result, max_chars=None):
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"""UI 显示层截断（同步；max_chars=None 用显示层常量兜底）。
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与 cap_tool_result（模型回填层）是两条独立通道：这里只影响前端展示，
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不进模型上下文。截断时显式告知（绝不静默截断），正常工具输出
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（<50000 字符）原样完整显示。
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"""
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text = result if isinstance(result, str) else str(result)
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limit = int(max_chars) if max_chars else DEFAULT_DISPLAY_MAX_CHARS
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total = len(text)
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if total <= limit:
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return text
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notice = (
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"\n\n…（输出过长，界面仅显示前 %d 字符，全文共 %d 字符。"
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"模型收到的内容不受此显示限制影响；上限可用 params.%s 调整）"
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% (limit, total, _PARAM_DISPLAY_KEY)
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)
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return text[:limit] + notice
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def invalidate_cache():
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"""params 变更后让缓存失效（部署/调参后无需重启进程）。"""
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global _cached_max
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global _cached_max, _cached_display_max
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_cached_max = None
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_cached_display_max = None
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