mirror of
https://github.com/jxxghp/MoviePilot.git
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refactor(agent): move feedback issue flow into skill scripts
This commit is contained in:
jxxghp
@@ -92,25 +92,12 @@ class AskUserChoiceTool(MoviePilotTool):
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def _blocked_by_feedback_quality_gate(self) -> bool:
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"""反馈 Issue 质量门槛拒绝后，禁止继续发按钮引导改写。
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这是对 ``feedback-issue`` skill 的工具层兜底：模型可能在
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``submit_feedback_issue`` 返回 ``rejected_quality`` 后仍调用本工具，
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试图让用户选择“提供真实问题描述重新提交”。这会把测试 / 占位内容
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的拒绝结果变成绕过指导，因此同一轮 tool context 中直接拦截。
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这是对 ``feedback-issue`` skill 的历史兜底：如果同一轮上下文已经
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标记反馈内容被质量门槛拒绝，就不能再用按钮诱导用户把测试 / 占位
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内容改写成“真实问题”。
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"""
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return bool(self._agent_context.get("feedback_issue_rejected_quality"))
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def _blocked_by_pending_feedback_confirmation(self) -> bool:
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"""已经发出 ``prepare_feedback_issue`` 的预览按钮后，禁止再叠一层选择。
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Why: Issue #5807 实测中 deepseek 在 prepare 之后又自作主张调
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``ask_user_choice``，给用户发了第二个「确认提交 ISSUE」按钮。
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两条按钮 → 两次 callback → agent 走两轮 → 同一条成功文案被发 3 次。
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从工具层硬拦：发现 ``reply_mode=feedback_issue_confirmation`` 直接拒绝。
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"""
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return (
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self._agent_context.get("reply_mode") == "feedback_issue_confirmation"
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)
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async def run(
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self,
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message: str,
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@@ -129,18 +116,6 @@ class AskUserChoiceTool(MoviePilotTool):
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"请直接结束本次反馈流程。"
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)
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if self._blocked_by_pending_feedback_confirmation():
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logger.warning(
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"ask_user_choice blocked while feedback issue preview pending: "
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"session_id=%s",
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self._session_id,
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)
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return (
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"prepare_feedback_issue 已经发出确认按钮并在等待用户点击，"
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"不允许再叠加 ask_user_choice。请直接结束本轮，等待用户在"
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"现有按钮上点选。"
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)
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if not self._channel or not self._source:
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return "当前不在可回传消息的会话中，无法发起按钮选择"
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@@ -1,453 +0,0 @@
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"""收集反馈 Issue 提交前需要附带的本地诊断日志。"""
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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 datetime import datetime, timedelta
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from pathlib import Path
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from typing import Optional, Type
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from pydantic import BaseModel, Field
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from app.agent.tools.base import MoviePilotTool
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from app.agent.tools.impl.feedback_issue_state import feedback_issue_state_store
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from app.agent.tools.impl.submit_feedback_issue import SubmitFeedbackIssueTool
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from app.core.config import settings
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from app.log import logger
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_MAX_READ_BYTES = 512 * 1024
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_MAX_DIAGNOSTIC_LOG_CHARS = 6 * 1024
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# 默认时间窗：仅收集最近 30 分钟的日志。
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# Why: 用户说「今天 TMDB 一直在报错」时，期望看到的是这次会话前后真实
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# 触发的报错，而不是几天前历史日志里所有出现 "TMDB" 的行。Issue #5806
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# 实战中就发生了：关键词命中了几天前的测试日志，日志段完全对不上当前问题。
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_DEFAULT_TIME_WINDOW_MINUTES = 30
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_MIN_TIME_WINDOW_MINUTES = 5
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_MAX_TIME_WINDOW_MINUTES = 24 * 60
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# MoviePilot 主日志行首格式：``【LEVEL】YYYY-MM-DD HH:MM:SS,ms - module - msg``
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# 用第一个时间戳判断行属于哪一刻；匹配不到时把行算到「无法判断时间」桶，
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# 默认保留（行内可能是 Traceback 续行，不能丢）。
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_LOG_TIMESTAMP_RE = re.compile(r"(\d{4}-\d{2}-\d{2}\s\d{2}:\d{2}:\d{2})")
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_LOG_TIMESTAMP_FORMAT = "%Y-%m-%d %H:%M:%S"
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# 提取日志行的源模块名，用于过滤"Agent 自身 meta-noise"。
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_LOG_MODULE_RE = re.compile(
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r"^【[^】]+】\d{4}-\d{2}-\d{2}\s\d{2}:\d{2}:\d{2},\d+\s+-\s+([^\s][^\-]*?)\s+-\s+"
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)
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# 这些模块产出的日志属于 Agent 自身运行 / 框架内务，对用户面故障定位毫无
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# 价值——反而经常把诊断段污染成"反馈流程的回声"：tool args dump 里塞着
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# ``database / 推荐 / 豆包`` 等关键字，让 keyword 过滤命中一堆 noise，
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# 真正的 RateLimitError / Traceback 反而被挤掉（参见 #5808 实战）。
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#
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# 包含两类：
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# 1) 反馈流程自己的工具与框架（绝对要排除，否则永远在自我反射）
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# 2) 通用 Agent 框架噪音：tool dispatch / event bus / streaming callback /
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# 通知发送 / activity log 等
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_META_NOISE_MODULES = frozenset({
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# 反馈流程
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"collect_feedback_diagnostics.py",
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"prepare_feedback_issue.py",
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"submit_feedback_issue.py",
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"ask_user_choice.py",
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# Agent 框架
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"base.py", # tool framework: Executing tool / Tool ... executed
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"agent", # agent runtime: Agent推理 / 流式输出
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"factory.py", # tool factory creation
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"callback", # streaming callback
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"prompt", # 提示词加载
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"memory.py", # 会话记忆
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"activity_log.py", # activity 日志
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# 消息/事件总线（往往把 issue 预览全文 dump 进日志）
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"message.py",
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"event.py",
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"chain", # chain - 请求系统模块执行：xxx
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# 渠道适配层噪音
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"discord",
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"telegram",
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"telegram.py",
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# 命令执行（agent 自己跑过的 shell 命令 echo）
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"execute_command.py",
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})
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# 不允许使用的模糊关键词：通用到几乎每条 log 都会命中、对定位本次问题
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# 没有价值。当 keyword 列表只剩这些时退回到「按时间窗口取尾部」。
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_VAGUE_KEYWORDS = frozenset({
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"错误", "异常", "失败", "error", "exception", "failed", "warn", "warning",
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"日志", "问题", "bug", "log", "logs",
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})
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# 入口意图门：``original_user_request`` 里必须能同时命中"动作"+"目标"，
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# 工具才允许进入反馈流程。Agent 在用户随口提到「报错」「不工作」时自作
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# 主张调用本工具，就会被这里硬挡住——把反馈通道留给真正想给上游提
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# Issue 的请求。
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#
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# 当前威胁模型是「模型过度归因到 upstream bug」，不是「对抗性绕过」；
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# 用户用近义词意图明显时（如「能不能给上游提 issue」），SKILL.md 引导
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# Agent 在原话里至少保留 ``反馈/提交/上游/issue`` 之一；如果保留不下来，
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# Agent 应该回退到本地诊断而不是强行触发反馈。
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#
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# 第一组动作词（必须出现至少一个）：
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_FEEDBACK_VERB_PHRASES: tuple[str, ...] = (
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"反馈", "提交", "上报", "汇报",
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"提 issue", "提issue", "提 bug", "提bug",
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"报 bug", "报bug", "报告 bug", "报告bug",
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"新建 issue", "新建issue", "开 issue", "开issue",
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"让上游", "给上游",
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"file an issue", "report a bug", "open an upstream issue",
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"submit an issue", "raise an issue", "report this upstream",
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"report upstream",
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)
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# 第二组目标词（动作命中后再校验目标存在）：英文 phrase 自带目标可绕过这里。
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_FEEDBACK_TARGET_TOKENS: tuple[str, ...] = (
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"issue", "bug", "问题", "错误报告",
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"上游", "mp", "moviepilot",
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)
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# 自带目标语义的完整短语：命中后直接放行，不再校验目标词。
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_FEEDBACK_STANDALONE_PHRASES: tuple[str, ...] = (
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"file an issue", "report a bug", "open an upstream issue",
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"submit an issue", "raise an issue", "report this upstream",
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"report upstream",
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"新建 issue", "新建issue", "开 issue", "开issue",
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"提 issue", "提issue", "提 bug", "提bug",
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"报 bug", "报bug", "报告 bug", "报告bug",
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"让上游", "给上游",
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)
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# 中文里常见"动词 + 量词/介词 + 目标"模式，用正则承接（最多容忍 6 字符
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# 间隔，覆盖"给 MP 提个 bug"、"反馈这个问题"、"报告一个 issue"）：
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_FEEDBACK_REGEX_PATTERNS: tuple[re.Pattern, ...] = (
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re.compile(r"提.{0,6}(bug|issue|问题|错误报告)", re.IGNORECASE),
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re.compile(r"报.{0,6}(bug|issue|错误报告)", re.IGNORECASE),
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re.compile(r"反馈.{0,8}(issue|bug|问题|上游|错误)", re.IGNORECASE),
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re.compile(r"开.{0,4}(issue|bug)", re.IGNORECASE),
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re.compile(r"上报.{0,6}(bug|issue|问题|错误)", re.IGNORECASE),
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)
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class CollectFeedbackDiagnosticsInput(BaseModel):
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"""反馈诊断日志收集工具输入。"""
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explanation: str = Field(
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...,
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description="Clear explanation of why diagnostic logs are being collected before filing feedback",
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)
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original_user_request: str = Field(
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...,
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description="The user's original bug report text that triggered diagnostics collection",
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)
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keywords: Optional[list[str]] = Field(
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default=None,
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description=(
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"Short keywords to filter logs. Should be SPECIFIC tokens: media title, "
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"plugin id, exception class name, downloader name, etc. Vague terms like "
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"'错误'/'异常'/'失败'/'error' are ignored because they match almost every log line."
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),
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)
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max_lines: int = Field(
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default=80,
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description="Maximum matched log lines to return; default 80",
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)
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time_window_minutes: int = Field(
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default=_DEFAULT_TIME_WINDOW_MINUTES,
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description=(
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"Only include log lines whose timestamp falls within the last N minutes "
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"(default 30, range 5-1440). Older lines are dropped regardless of keyword "
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"match so the diagnostic snapshot reflects the current incident, not "
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"historical noise."
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),
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)
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class CollectFeedbackDiagnosticsTool(MoviePilotTool):
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"""收集并缓存反馈 Issue 用的日志片段。"""
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name: str = "collect_feedback_diagnostics"
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description: str = (
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"Collect recent local MoviePilot logs before preparing or submitting a feedback issue. "
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"This tool reads config/logs/moviepilot.log and plugin logs, filters by user-provided "
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"keywords when available, redacts common secrets, and stores a diagnostics_id that "
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"submit_feedback_issue requires. Use it before prepare_feedback_issue."
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)
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args_schema: Type[BaseModel] = CollectFeedbackDiagnosticsInput
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require_admin: bool = True
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def get_tool_message(self, **kwargs) -> Optional[str]:
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"""侧边消息：告知用户正在读取本地日志辅助反馈。"""
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return "收集反馈诊断日志"
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@staticmethod
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def _read_tail(path: Path) -> str:
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"""读取日志文件尾部，避免大日志一次性进入内存。"""
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try:
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size = path.stat().st_size
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with path.open("rb") as file_obj:
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if size > _MAX_READ_BYTES:
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file_obj.seek(size - _MAX_READ_BYTES)
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return file_obj.read().decode("utf-8", errors="replace")
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except OSError as err:
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logger.debug("读取反馈诊断日志失败: %s %s", path, err)
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return ""
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@staticmethod
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def _candidate_log_files() -> list[Path]:
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"""返回反馈诊断可读取的日志文件列表。"""
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files = [settings.LOG_PATH / "moviepilot.log"]
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plugin_log_dir = settings.LOG_PATH / "plugins"
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if plugin_log_dir.exists():
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files.extend(sorted(plugin_log_dir.rglob("*.log")))
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return [path for path in files if path.exists() and path.is_file()]
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@staticmethod
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def _normalize_keywords(
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original_user_request: str,
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keywords: Optional[list[str]],
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) -> list[str]:
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"""合并用户原话和显式关键词，生成保守的日志过滤词。
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Issue #5806 教训：把 "错误 / 异常 / 失败 / TMDB" 这种通用词当关键词
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会让几乎所有日志行命中，过滤等于没过滤。这里只保留**显式且足够具体**
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（≥2 字符且不在 ``_VAGUE_KEYWORDS`` 里）的关键词。"""
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normalized: list[str] = []
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for item in keywords or []:
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item = str(item or "").strip()
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if len(item) < 2:
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continue
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if item.lower() in _VAGUE_KEYWORDS:
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continue
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if item not in normalized:
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normalized.append(item)
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return normalized
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@staticmethod
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def _has_explicit_feedback_intent(original_user_request: str) -> bool:
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"""判断用户原话里是否出现了"明确要求提 Issue"的意图。
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Why: Agent 在 deepseek 这类强模型里会主动归因——用户只说"TMDB 报
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错"或"下载没动"，Agent 就跳过本地诊断、直接进入反馈流程。本工具
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是反馈流程的入口，硬挡一道意图门，迫使 Agent 回到 SKILL.md Step 0
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要求的"先排查、再反馈"路径。
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判定规则（先放行更具体的、再回落到组合）：
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1. 命中 ``_FEEDBACK_STANDALONE_PHRASES`` 任一短语 → 放行。
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这些短语已经把"动作 + 目标"打包在一起（如 ``提 issue``、
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``file an issue``），无需再二次校验。
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2. 同时命中一个 ``_FEEDBACK_VERB_PHRASES`` 动作词和一个
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``_FEEDBACK_TARGET_TOKENS`` 目标词 → 放行。能覆盖"反馈这个
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问题"、"提交个 bug"、"把这个反馈给上游"等自然中文。
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3. 否则视为没有明确意图，拒绝。
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"""
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if not original_user_request:
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return False
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normalized = original_user_request.lower().strip()
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if any(phrase in normalized for phrase in _FEEDBACK_STANDALONE_PHRASES):
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return True
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if any(p.search(normalized) for p in _FEEDBACK_REGEX_PATTERNS):
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return True
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has_verb = any(phrase in normalized for phrase in _FEEDBACK_VERB_PHRASES)
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has_target = any(token in normalized for token in _FEEDBACK_TARGET_TOKENS)
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return has_verb and has_target
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@staticmethod
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def _normalize_window(time_window_minutes: int) -> int:
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"""把传入的时间窗 clamp 到 [5, 1440] 区间。"""
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try:
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window = int(time_window_minutes or _DEFAULT_TIME_WINDOW_MINUTES)
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except (TypeError, ValueError):
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window = _DEFAULT_TIME_WINDOW_MINUTES
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return max(_MIN_TIME_WINDOW_MINUTES, min(_MAX_TIME_WINDOW_MINUTES, window))
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@staticmethod
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def _parse_line_timestamp(line: str) -> Optional[datetime]:
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"""从一行日志开头提取时间戳；提取不到返回 None。"""
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match = _LOG_TIMESTAMP_RE.search(line[:64])
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if not match:
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return None
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try:
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return datetime.strptime(match.group(1), _LOG_TIMESTAMP_FORMAT)
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except ValueError:
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return None
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@staticmethod
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def _is_meta_noise(line: str) -> bool:
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"""判断一行日志是否来自"Agent 自身 meta-noise"模块。
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命中即排除。续行（无模块名）由调用方按"跟随父行"语义处理。
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"""
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match = _LOG_MODULE_RE.match(line)
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if not match:
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return False
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return match.group(1).strip() in _META_NOISE_MODULES
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@classmethod
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def _filter_lines(
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||||
cls,
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||||
text: str,
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||||
keywords: list[str],
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||||
max_lines: int,
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||||
window_start: datetime,
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||||
) -> list[str]:
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||||
"""按时间窗 + 关键词筛日志。
|
||||
|
||||
- 行能解析到时间戳：在 ``window_start`` 之前的丢弃；之后的进入候选。
|
||||
- 行解析不到时间戳（Traceback 续行等）：跟随**最近一条已知时间戳行**
|
||||
的归属，没有上下文时按"近期"对待，避免把异常堆栈截断。
|
||||
- 在候选行里再按关键词过滤；无关键词或全部行都不命中时退回到时间
|
||||
窗内的尾部行，保证返回有意义的内容而不是空集。
|
||||
"""
|
||||
candidates: list[str] = []
|
||||
last_seen_in_window: Optional[bool] = None
|
||||
last_seen_was_meta: bool = False
|
||||
for line in text.splitlines():
|
||||
if not line.strip():
|
||||
continue
|
||||
ts = cls._parse_line_timestamp(line)
|
||||
if ts is not None:
|
||||
in_window = ts >= window_start
|
||||
# Meta-noise 行（agent/tool framework 自己的日志）即便落在窗口
|
||||
# 内也直接丢；它们对用户面故障定位没有价值，反而会因为带有
|
||||
# ``database / 推荐 / 豆包`` 之类关键字让诊断段灌满 noise。
|
||||
is_meta = cls._is_meta_noise(line)
|
||||
last_seen_was_meta = is_meta
|
||||
last_seen_in_window = in_window and not is_meta
|
||||
if in_window and not is_meta:
|
||||
candidates.append(line)
|
||||
else:
|
||||
# 续行：跟随上一条时间戳行的去留（meta-noise 父行的续行也丢）
|
||||
if last_seen_in_window and not last_seen_was_meta:
|
||||
candidates.append(line)
|
||||
|
||||
if not candidates:
|
||||
return []
|
||||
if keywords:
|
||||
lowered_keywords = [item.lower() for item in keywords]
|
||||
# 关键字过滤需要按"时间戳行块"为单位：命中的 ERROR 行带着它的
|
||||
# Traceback 续行一起保留，避免把异常堆栈截掉一半反而更难定位。
|
||||
matched: list[str] = []
|
||||
keep_block = False
|
||||
for line in candidates:
|
||||
has_ts = cls._parse_line_timestamp(line) is not None
|
||||
if has_ts:
|
||||
keep_block = any(kw in line.lower() for kw in lowered_keywords)
|
||||
if keep_block:
|
||||
matched.append(line)
|
||||
elif keep_block:
|
||||
matched.append(line)
|
||||
if matched:
|
||||
return matched[-max_lines:]
|
||||
return candidates[-max_lines:]
|
||||
|
||||
async def run(
|
||||
self,
|
||||
original_user_request: str,
|
||||
keywords: Optional[list[str]] = None,
|
||||
max_lines: int = 80,
|
||||
time_window_minutes: int = _DEFAULT_TIME_WINDOW_MINUTES,
|
||||
**kwargs,
|
||||
) -> str:
|
||||
"""读取、筛选、脱敏并缓存本次反馈相关日志。
|
||||
|
||||
Issue #5806 暴露的两个数据准确性问题在这里一并修：
|
||||
1. 时间窗：默认只看最近 30 分钟，杜绝历史无关日志混入。
|
||||
2. 关键词过滤收紧：剔除"错误/异常/失败"等几乎每行都命中的通用词。
|
||||
|
||||
反馈入口意图门（用户反馈）：``original_user_request`` 里必须有
|
||||
明确"我要提 Issue / 反馈 issue / file an issue"之类的短语；
|
||||
Agent 自作主张把"TMDB 报错"理解成"反馈" 时直接拒绝，引导回归
|
||||
本地诊断路径，避免给上游刷 Issue。
|
||||
"""
|
||||
if not self._has_explicit_feedback_intent(original_user_request):
|
||||
logger.info(
|
||||
"collect_feedback_diagnostics 拒绝：原始请求里没有明确"
|
||||
"反馈意图。原话=%r",
|
||||
(original_user_request or "")[:120],
|
||||
)
|
||||
return json.dumps(
|
||||
{
|
||||
"success": False,
|
||||
"reason": "no_explicit_feedback_intent",
|
||||
"message": (
|
||||
"用户原话里没有明确要求向上游反馈 Issue 的短语，"
|
||||
"不应直接进入反馈流程。请回到常规诊断路径，使用"
|
||||
"query_subscribes / query_download_tasks / "
|
||||
"query_logs / test_site 等工具先排查；仅当用户"
|
||||
"在排查后明确要求把问题转给上游（例如说出 "
|
||||
"「反馈 issue / 提 issue / 报 bug / 让上游修一下」"
|
||||
"之类的原话），才能再次调用本工具。"
|
||||
),
|
||||
},
|
||||
ensure_ascii=False,
|
||||
indent=2,
|
||||
)
|
||||
|
||||
try:
|
||||
normalized_max_lines = min(max(int(max_lines or 80), 20), 200)
|
||||
except (TypeError, ValueError):
|
||||
normalized_max_lines = 80
|
||||
|
||||
window_minutes = self._normalize_window(time_window_minutes)
|
||||
window_start = datetime.now() - timedelta(minutes=window_minutes)
|
||||
normalized_keywords = self._normalize_keywords(original_user_request, keywords)
|
||||
collected: list[str] = []
|
||||
source_files: list[str] = []
|
||||
|
||||
log_files = await self.run_blocking("default", self._candidate_log_files)
|
||||
for path in log_files:
|
||||
text = await self.run_blocking("default", self._read_tail, path)
|
||||
if not text:
|
||||
continue
|
||||
lines = self._filter_lines(
|
||||
text, normalized_keywords, normalized_max_lines, window_start
|
||||
)
|
||||
if not lines:
|
||||
continue
|
||||
source_files.append(str(path))
|
||||
collected.append(f"### {path.name}\n" + "\n".join(lines))
|
||||
|
||||
raw_logs = "\n\n".join(collected)
|
||||
logs = SubmitFeedbackIssueTool._sanitize_logs(raw_logs, _MAX_DIAGNOSTIC_LOG_CHARS)
|
||||
found = bool(logs.strip())
|
||||
|
||||
record = feedback_issue_state_store.create_diagnostics(
|
||||
session_id=self._session_id,
|
||||
user_id=self._user_id,
|
||||
username=self._username,
|
||||
logs=logs,
|
||||
source_files=source_files,
|
||||
found=found,
|
||||
)
|
||||
self._agent_context["feedback_issue_diagnostics_id"] = record.diagnostics_id
|
||||
|
||||
# 关键：不要把 ``logs`` 内容回传给 LLM。日志可达 6KB，回传后 LLM
|
||||
# 还会在下一步把它原样塞进 prepare_feedback_issue 的入参里二次
|
||||
# transit，导致 26B/V3 等模型每轮要 ingest+emit 数 KB 文本，响应延
|
||||
# 迟从秒级飙到分钟级（曾观察到 collect 返回 7.7KB → 下一轮 prepare
|
||||
# 入参 logs 字段又重复一份）。日志全程只通过 ``diagnostics_id``
|
||||
# 在服务端的 ``feedback_issue_state_store`` 流转，模型只看到摘要。
|
||||
log_bytes = len(record.logs.encode("utf-8", errors="replace"))
|
||||
log_lines = len(record.logs.splitlines()) if record.logs else 0
|
||||
return json.dumps(
|
||||
{
|
||||
"success": True,
|
||||
"diagnostics_id": record.diagnostics_id,
|
||||
"found": record.found,
|
||||
"source_files": record.source_files,
|
||||
"log_bytes": log_bytes,
|
||||
"log_lines": log_lines,
|
||||
"message": (
|
||||
"已收集并缓存反馈诊断日志。"
|
||||
if found
|
||||
else "已完成诊断日志收集，但未找到明显相关日志。"
|
||||
) + (
|
||||
"日志已通过 diagnostics_id 缓存在服务端，"
|
||||
"后续 prepare_feedback_issue / submit_feedback_issue "
|
||||
"只需传入 diagnostics_id，**不要**再把日志正文当参数传回。"
|
||||
),
|
||||
},
|
||||
ensure_ascii=False,
|
||||
indent=2,
|
||||
)
|
||||
@@ -1,261 +0,0 @@
|
||||
"""反馈 Issue 流程的短期服务端状态。
|
||||
|
||||
这里保存两类只应由工具写入的状态：
|
||||
- 诊断日志收集结果：证明 Agent 在提交前尝试读取过本地日志。
|
||||
- 用户确认结果：证明用户通过按钮确认过某份预览草稿。
|
||||
|
||||
状态只保存在当前进程内，重启后失效；这符合反馈提交这种交互式流程的预期，
|
||||
也避免把一次性确认 token 持久化到数据库。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import hashlib
|
||||
import time
|
||||
import uuid
|
||||
from dataclasses import dataclass
|
||||
from threading import Lock
|
||||
from typing import Optional
|
||||
|
||||
|
||||
FEEDBACK_CONFIRM_VALUE_PREFIX = "__feedback_issue_confirm__:"
|
||||
_STATE_TTL_SECONDS = 60 * 60
|
||||
|
||||
|
||||
@dataclass
|
||||
class FeedbackDiagnosticsRecord:
|
||||
"""一次反馈诊断日志收集结果。"""
|
||||
|
||||
diagnostics_id: str
|
||||
session_id: str
|
||||
user_id: str
|
||||
username: Optional[str]
|
||||
logs: str
|
||||
source_files: list[str]
|
||||
found: bool
|
||||
created_at: float
|
||||
|
||||
|
||||
@dataclass
|
||||
class FeedbackConfirmationRecord:
|
||||
"""一次反馈 Issue 预览确认状态。"""
|
||||
|
||||
confirmation_token: str
|
||||
session_id: str
|
||||
user_id: str
|
||||
username: Optional[str]
|
||||
draft_hash: str
|
||||
diagnostics_id: str
|
||||
created_at: float
|
||||
confirmed_at: Optional[float] = None
|
||||
|
||||
|
||||
def build_feedback_draft_hash(
|
||||
*,
|
||||
title: str,
|
||||
version: str,
|
||||
environment: str,
|
||||
issue_type: str,
|
||||
description: str,
|
||||
original_user_request: str,
|
||||
logs: Optional[str],
|
||||
diagnostics_id: str,
|
||||
) -> str:
|
||||
"""为用户确认的 Issue 草稿生成稳定摘要。"""
|
||||
parts = (
|
||||
title.strip(),
|
||||
version.strip(),
|
||||
environment.strip(),
|
||||
issue_type.strip(),
|
||||
description.strip(),
|
||||
original_user_request.strip(),
|
||||
(logs or "").strip(),
|
||||
diagnostics_id.strip(),
|
||||
)
|
||||
return hashlib.sha256("\x00".join(parts).encode("utf-8", errors="replace")).hexdigest()
|
||||
|
||||
|
||||
class FeedbackIssueStateStore:
|
||||
"""管理反馈 Issue 流程的进程内短期状态。"""
|
||||
|
||||
def __init__(self) -> None:
|
||||
self._diagnostics: dict[str, FeedbackDiagnosticsRecord] = {}
|
||||
self._confirmations: dict[str, FeedbackConfirmationRecord] = {}
|
||||
self._lock = Lock()
|
||||
|
||||
def _cleanup_locked(self) -> None:
|
||||
expire_before = time.time() - _STATE_TTL_SECONDS
|
||||
for diagnostics_id, record in list(self._diagnostics.items()):
|
||||
if record.created_at < expire_before:
|
||||
self._diagnostics.pop(diagnostics_id, None)
|
||||
for token, record in list(self._confirmations.items()):
|
||||
if record.created_at < expire_before:
|
||||
self._confirmations.pop(token, None)
|
||||
|
||||
def create_diagnostics(
|
||||
self,
|
||||
*,
|
||||
session_id: str,
|
||||
user_id: str,
|
||||
username: Optional[str],
|
||||
logs: str,
|
||||
source_files: list[str],
|
||||
found: bool,
|
||||
) -> FeedbackDiagnosticsRecord:
|
||||
"""登记一次日志收集结果。"""
|
||||
with self._lock:
|
||||
self._cleanup_locked()
|
||||
diagnostics_id = uuid.uuid4().hex[:12]
|
||||
while diagnostics_id in self._diagnostics:
|
||||
diagnostics_id = uuid.uuid4().hex[:12]
|
||||
record = FeedbackDiagnosticsRecord(
|
||||
diagnostics_id=diagnostics_id,
|
||||
session_id=session_id,
|
||||
user_id=str(user_id),
|
||||
username=username,
|
||||
logs=logs,
|
||||
source_files=source_files,
|
||||
found=found,
|
||||
created_at=time.time(),
|
||||
)
|
||||
self._diagnostics[diagnostics_id] = record
|
||||
return record
|
||||
|
||||
def get_diagnostics(
|
||||
self,
|
||||
diagnostics_id: str,
|
||||
*,
|
||||
session_id: str,
|
||||
user_id: str,
|
||||
) -> Optional[FeedbackDiagnosticsRecord]:
|
||||
"""按会话和用户读取诊断结果，防止跨用户复用。"""
|
||||
with self._lock:
|
||||
self._cleanup_locked()
|
||||
record = self._diagnostics.get(diagnostics_id)
|
||||
if not record:
|
||||
return None
|
||||
if record.session_id != session_id or record.user_id != str(user_id):
|
||||
return None
|
||||
return record
|
||||
|
||||
def find_active_confirmation(
|
||||
self,
|
||||
*,
|
||||
session_id: str,
|
||||
user_id: str,
|
||||
) -> Optional[FeedbackConfirmationRecord]:
|
||||
"""查找当前会话/用户尚未消费、且未点击确认的预览 token。
|
||||
|
||||
prepare_feedback_issue 会用它判断「上一份预览还挂着，不该再发一份」，
|
||||
避免 #5806 实测里发了两次同样的确认按钮、用户点了两次的情况。"""
|
||||
with self._lock:
|
||||
self._cleanup_locked()
|
||||
for record in self._confirmations.values():
|
||||
if (
|
||||
record.session_id == session_id
|
||||
and record.user_id == str(user_id)
|
||||
and record.confirmed_at is None
|
||||
):
|
||||
return record
|
||||
return None
|
||||
|
||||
def invalidate_active_confirmations(
|
||||
self,
|
||||
*,
|
||||
session_id: str,
|
||||
user_id: str,
|
||||
) -> int:
|
||||
"""作废当前会话所有未确认的预览 token，返回作废数量。
|
||||
|
||||
用户在 prepare 之后修改草稿、重新调 prepare 时调用；旧 token 失效
|
||||
后即便残留消息里的按钮被点击，``mark_confirmed`` 也会因找不到记录
|
||||
而返回 False，避免脏数据驱动提交。"""
|
||||
with self._lock:
|
||||
self._cleanup_locked()
|
||||
to_drop = [
|
||||
token
|
||||
for token, record in self._confirmations.items()
|
||||
if record.session_id == session_id
|
||||
and record.user_id == str(user_id)
|
||||
and record.confirmed_at is None
|
||||
]
|
||||
for token in to_drop:
|
||||
self._confirmations.pop(token, None)
|
||||
return len(to_drop)
|
||||
|
||||
def create_confirmation(
|
||||
self,
|
||||
*,
|
||||
session_id: str,
|
||||
user_id: str,
|
||||
username: Optional[str],
|
||||
draft_hash: str,
|
||||
diagnostics_id: str,
|
||||
) -> FeedbackConfirmationRecord:
|
||||
"""创建待用户点击确认的草稿 token。"""
|
||||
with self._lock:
|
||||
self._cleanup_locked()
|
||||
token = uuid.uuid4().hex
|
||||
while token in self._confirmations:
|
||||
token = uuid.uuid4().hex
|
||||
record = FeedbackConfirmationRecord(
|
||||
confirmation_token=token,
|
||||
session_id=session_id,
|
||||
user_id=str(user_id),
|
||||
username=username,
|
||||
draft_hash=draft_hash,
|
||||
diagnostics_id=diagnostics_id,
|
||||
created_at=time.time(),
|
||||
)
|
||||
self._confirmations[token] = record
|
||||
return record
|
||||
|
||||
def mark_confirmed(
|
||||
self,
|
||||
token: str,
|
||||
*,
|
||||
session_id: str,
|
||||
user_id: str,
|
||||
) -> bool:
|
||||
"""按钮回调命中时，把 token 标记为已由用户确认。"""
|
||||
with self._lock:
|
||||
self._cleanup_locked()
|
||||
record = self._confirmations.get(token)
|
||||
if not record:
|
||||
return False
|
||||
if record.session_id != session_id or record.user_id != str(user_id):
|
||||
return False
|
||||
record.confirmed_at = time.time()
|
||||
return True
|
||||
|
||||
def consume_confirmed(
|
||||
self,
|
||||
token: str,
|
||||
*,
|
||||
session_id: str,
|
||||
user_id: str,
|
||||
draft_hash: str,
|
||||
) -> Optional[FeedbackConfirmationRecord]:
|
||||
"""消费一次已确认 token；内容摘要不一致时拒绝。"""
|
||||
with self._lock:
|
||||
self._cleanup_locked()
|
||||
record = self._confirmations.get(token)
|
||||
if not record:
|
||||
return None
|
||||
if (
|
||||
record.session_id != session_id
|
||||
or record.user_id != str(user_id)
|
||||
or record.draft_hash != draft_hash
|
||||
or record.confirmed_at is None
|
||||
):
|
||||
return None
|
||||
return self._confirmations.pop(token, None)
|
||||
|
||||
def clear(self) -> None:
|
||||
"""测试和重置场景使用：清空所有短期状态。"""
|
||||
with self._lock:
|
||||
self._diagnostics.clear()
|
||||
self._confirmations.clear()
|
||||
|
||||
|
||||
feedback_issue_state_store = FeedbackIssueStateStore()
|
||||
@@ -1,285 +0,0 @@
|
||||
"""生成反馈 Issue 预览并要求用户按钮确认。"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from typing import Optional, Type
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from app.agent.tools.base import MoviePilotTool, ToolChain
|
||||
from app.agent.tools.impl.feedback_issue_state import (
|
||||
FEEDBACK_CONFIRM_VALUE_PREFIX,
|
||||
build_feedback_draft_hash,
|
||||
feedback_issue_state_store,
|
||||
)
|
||||
from app.agent.tools.impl.submit_feedback_issue import (
|
||||
ALLOWED_ENVIRONMENTS,
|
||||
ALLOWED_ISSUE_TYPES,
|
||||
MAX_TITLE_CHARS,
|
||||
SubmitFeedbackIssueTool,
|
||||
)
|
||||
from app.helper.interaction import AgentInteractionOption, agent_interaction_manager
|
||||
from app.log import logger
|
||||
from app.schemas import Notification, NotificationType
|
||||
from app.schemas.message import ChannelCapabilityManager
|
||||
from app.schemas.types import MessageChannel
|
||||
|
||||
|
||||
class PrepareFeedbackIssueInput(BaseModel):
|
||||
"""反馈 Issue 预览确认工具输入。"""
|
||||
|
||||
explanation: str = Field(
|
||||
...,
|
||||
description="Clear explanation of why a feedback issue preview is being prepared",
|
||||
)
|
||||
title: str = Field(..., description="Issue title following `[错误报告]: <短描述>`")
|
||||
version: str = Field(..., description="Current MoviePilot version")
|
||||
environment: str = Field(..., description="Exactly Docker or Windows")
|
||||
issue_type: str = Field(..., description="主程序运行问题 / 插件问题 / 其他问题")
|
||||
description: str = Field(..., description="Structured issue description")
|
||||
original_user_request: str = Field(..., description="Verbatim original user request")
|
||||
diagnostics_id: str = Field(
|
||||
...,
|
||||
description=(
|
||||
"diagnostics_id returned by collect_feedback_diagnostics. Logs are loaded from "
|
||||
"the server-side state store via this id — do NOT pass the log text itself."
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
class PrepareFeedbackIssueTool(MoviePilotTool):
|
||||
"""发送 Issue 草稿预览，并创建只能由按钮回调确认的 token。"""
|
||||
|
||||
name: str = "prepare_feedback_issue"
|
||||
sends_message: bool = True
|
||||
description: str = (
|
||||
"Prepare a feedback issue preview and ask the user to confirm via buttons. "
|
||||
"Must be called after collect_feedback_diagnostics and before submit_feedback_issue. "
|
||||
"Returns a confirmation_token, but submit_feedback_issue will only accept it after "
|
||||
"the user actually clicks the confirmation button."
|
||||
)
|
||||
args_schema: Type[BaseModel] = PrepareFeedbackIssueInput
|
||||
require_admin: bool = True
|
||||
|
||||
def get_tool_message(self, **kwargs) -> Optional[str]:
|
||||
"""侧边消息：告知用户正在生成提交预览。"""
|
||||
return "生成问题反馈预览并等待确认"
|
||||
|
||||
@staticmethod
|
||||
def _truncate_button_text(text: str, max_length: int) -> str:
|
||||
"""按渠道限制裁剪按钮文案。"""
|
||||
if max_length <= 0 or len(text) <= max_length:
|
||||
return text
|
||||
if max_length <= 3:
|
||||
return text[:max_length]
|
||||
return text[: max_length - 3] + "..."
|
||||
|
||||
@staticmethod
|
||||
def _result_payload(**fields) -> str:
|
||||
"""统一 JSON 返回，便于 Agent 按字段继续下一步。"""
|
||||
return json.dumps(fields, ensure_ascii=False, indent=2)
|
||||
|
||||
async def run(
|
||||
self,
|
||||
title: str,
|
||||
version: str,
|
||||
environment: str,
|
||||
issue_type: str,
|
||||
description: str,
|
||||
original_user_request: str,
|
||||
diagnostics_id: str,
|
||||
**kwargs,
|
||||
) -> str:
|
||||
"""校验草稿、发送预览按钮，并缓存待确认 token。"""
|
||||
if not self._channel or not self._source:
|
||||
return self._result_payload(
|
||||
success=False,
|
||||
reason="no_channel",
|
||||
message="当前不在可回传消息的会话中，无法发送 Issue 预览确认按钮。",
|
||||
)
|
||||
try:
|
||||
channel = MessageChannel(self._channel)
|
||||
except ValueError:
|
||||
return self._result_payload(
|
||||
success=False,
|
||||
reason="unsupported_channel",
|
||||
message=f"不支持的消息渠道: {self._channel}",
|
||||
)
|
||||
if not (
|
||||
ChannelCapabilityManager.supports_buttons(channel)
|
||||
and ChannelCapabilityManager.supports_callbacks(channel)
|
||||
):
|
||||
return self._result_payload(
|
||||
success=False,
|
||||
reason="buttons_unsupported",
|
||||
message=f"当前渠道 {channel.value} 不支持按钮确认，不能自动提交反馈 Issue。",
|
||||
)
|
||||
|
||||
diagnostics = feedback_issue_state_store.get_diagnostics(
|
||||
diagnostics_id,
|
||||
session_id=self._session_id,
|
||||
user_id=self._user_id,
|
||||
)
|
||||
if not diagnostics:
|
||||
return self._result_payload(
|
||||
success=False,
|
||||
reason="diagnostics_missing",
|
||||
message="缺少有效的诊断日志收集记录，请先调用 collect_feedback_diagnostics。",
|
||||
)
|
||||
# 日志全程只从服务端 state store 流转，避免日志在 LLM 上下文里反复
|
||||
# 进出造成响应延迟（见 collect_feedback_diagnostics 中的设计注释）。
|
||||
logs = diagnostics.logs
|
||||
|
||||
for value, allowed, field_name in (
|
||||
(environment, ALLOWED_ENVIRONMENTS, "environment"),
|
||||
(issue_type, ALLOWED_ISSUE_TYPES, "issue_type"),
|
||||
):
|
||||
err = SubmitFeedbackIssueTool._validate_enum(value, allowed, field_name)
|
||||
if err:
|
||||
return self._result_payload(success=False, reason="invalid_input", message=err)
|
||||
|
||||
title = SubmitFeedbackIssueTool._truncate(title, MAX_TITLE_CHARS, marker="…")
|
||||
quality_err = SubmitFeedbackIssueTool._check_content_quality(
|
||||
title=title,
|
||||
description=description,
|
||||
original_user_request=original_user_request,
|
||||
)
|
||||
if quality_err:
|
||||
self._agent_context["feedback_issue_rejected_quality"] = True
|
||||
self._agent_context["feedback_issue_rejected_quality_reason"] = quality_err
|
||||
return self._result_payload(
|
||||
success=False,
|
||||
reason="rejected_quality",
|
||||
message=quality_err,
|
||||
)
|
||||
|
||||
draft_hash = build_feedback_draft_hash(
|
||||
title=title,
|
||||
version=version,
|
||||
environment=environment,
|
||||
issue_type=issue_type,
|
||||
description=description,
|
||||
original_user_request=original_user_request,
|
||||
logs=logs,
|
||||
diagnostics_id=diagnostics_id,
|
||||
)
|
||||
|
||||
# 同会话/用户已经发过预览且尚未被用户点击确认：拒绝重复发预览。
|
||||
# Why: Issue #5806 实测中 agent 在一次用户输入里连续调用了两次
|
||||
# prepare_feedback_issue，导致 TG 里出现两份「确认提交」按钮，用户
|
||||
# 点击两次后才进入提交。这里直接挡住重复预览：草稿一致就复用旧
|
||||
# token，草稿变了则要求 Agent 自己撤销旧 token 再发新预览（以免
|
||||
# 残留按钮指向过期内容）。
|
||||
active = feedback_issue_state_store.find_active_confirmation(
|
||||
session_id=self._session_id,
|
||||
user_id=self._user_id,
|
||||
)
|
||||
if active is not None:
|
||||
if active.draft_hash == draft_hash:
|
||||
logger.info(
|
||||
"feedback issue preview deduped: session_id=%s reuse token=%s",
|
||||
self._session_id,
|
||||
active.confirmation_token[:8],
|
||||
)
|
||||
self._agent_context["user_reply_sent"] = True
|
||||
self._agent_context["reply_mode"] = "feedback_issue_confirmation"
|
||||
return self._result_payload(
|
||||
success=True,
|
||||
deduped=True,
|
||||
confirmation_token=active.confirmation_token,
|
||||
diagnostics_id=diagnostics_id,
|
||||
message=(
|
||||
"上一份相同内容的反馈预览仍在等待用户点击确认，"
|
||||
"未重复发送按钮。请勿再次调用 prepare_feedback_issue。"
|
||||
),
|
||||
)
|
||||
logger.info(
|
||||
"feedback issue preview superseded: session_id=%s drop_token=%s",
|
||||
self._session_id,
|
||||
active.confirmation_token[:8],
|
||||
)
|
||||
feedback_issue_state_store.invalidate_active_confirmations(
|
||||
session_id=self._session_id,
|
||||
user_id=self._user_id,
|
||||
)
|
||||
|
||||
confirmation = feedback_issue_state_store.create_confirmation(
|
||||
session_id=self._session_id,
|
||||
user_id=self._user_id,
|
||||
username=self._username,
|
||||
draft_hash=draft_hash,
|
||||
diagnostics_id=diagnostics_id,
|
||||
)
|
||||
|
||||
option_value = f"{FEEDBACK_CONFIRM_VALUE_PREFIX}{confirmation.confirmation_token}"
|
||||
request = agent_interaction_manager.create_request(
|
||||
session_id=self._session_id,
|
||||
user_id=str(self._user_id),
|
||||
channel=channel.value,
|
||||
source=self._source,
|
||||
username=self._username,
|
||||
title="确认提交问题反馈",
|
||||
prompt="请确认是否将以下问题反馈提交到 MoviePilot 上游仓库。",
|
||||
options=[
|
||||
AgentInteractionOption(label="确认提交", value=option_value),
|
||||
AgentInteractionOption(label="取消提交", value="取消提交问题反馈"),
|
||||
],
|
||||
)
|
||||
|
||||
max_text_length = ChannelCapabilityManager.get_max_button_text_length(channel)
|
||||
buttons = [
|
||||
[
|
||||
{
|
||||
"text": self._truncate_button_text("确认提交", max_text_length),
|
||||
"callback_data": f"agent_interaction:choice:{request.request_id}:1",
|
||||
}
|
||||
],
|
||||
[
|
||||
{
|
||||
"text": self._truncate_button_text("取消提交", max_text_length),
|
||||
"callback_data": f"agent_interaction:choice:{request.request_id}:2",
|
||||
}
|
||||
],
|
||||
]
|
||||
preview = (
|
||||
"请确认是否提交以下问题反馈：\n\n"
|
||||
f"标题：{title}\n"
|
||||
f"版本：{version}\n"
|
||||
f"环境：{environment}\n"
|
||||
f"类型：{issue_type}\n"
|
||||
f"诊断日志：{'已找到相关日志' if diagnostics.found else '未找到明确相关日志'}\n\n"
|
||||
f"{description.strip()[:1800]}"
|
||||
)
|
||||
await ToolChain().async_post_message(
|
||||
Notification(
|
||||
channel=channel,
|
||||
source=self._source,
|
||||
mtype=NotificationType.Agent,
|
||||
userid=self._user_id,
|
||||
username=self._username,
|
||||
title="确认提交问题反馈",
|
||||
text=preview,
|
||||
buttons=buttons,
|
||||
)
|
||||
)
|
||||
logger.info(
|
||||
"feedback issue preview sent: session_id=%s diagnostics_id=%s token=%s",
|
||||
self._session_id,
|
||||
diagnostics_id,
|
||||
confirmation.confirmation_token[:8],
|
||||
)
|
||||
self._agent_context["user_reply_sent"] = True
|
||||
self._agent_context["reply_mode"] = "feedback_issue_confirmation"
|
||||
return self._result_payload(
|
||||
success=True,
|
||||
confirmation_token=confirmation.confirmation_token,
|
||||
diagnostics_id=diagnostics_id,
|
||||
message=(
|
||||
"已通过独立通知卡片发送 Issue 预览和「确认提交 / 取消提交」"
|
||||
"按钮给用户。**本轮对话不要再生成任何额外文字回复**——按钮"
|
||||
"卡片已经完整表达了 Issue 草稿和操作引导，复述「已生成 "
|
||||
"Issue 预览，请点击确认按钮」会和卡片重复并让用户困惑。"
|
||||
"请直接结束本轮，等待用户点击按钮触发下一轮。"
|
||||
),
|
||||
)
|
||||
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user