"""收集 feedback-issue 提交流程需要的本地诊断日志。""" from __future__ import annotations import argparse import re import shutil import subprocess import sys from datetime import datetime, timedelta from pathlib import Path from typing import Optional from feedback_issue_common import ( MAX_LOGS_CHARS, format_log_selection, feedback_runtime_dir, result_payload, runtime_file, sanitize_logs, settings, write_json_file, ) _MAX_READ_BYTES = 512 * 1024 _DEFAULT_TIME_WINDOW_MINUTES = 30 _MIN_TIME_WINDOW_MINUTES = 5 _MAX_TIME_WINDOW_MINUTES = 24 * 60 _LOG_TIMESTAMP_RE = re.compile(r"(\d{4}-\d{2}-\d{2}\s\d{2}:\d{2}:\d{2})") _LOG_TIMESTAMP_FORMAT = "%Y-%m-%d %H:%M:%S" _LOG_MODULE_RE = re.compile( r"^【[^】]+】\d{4}-\d{2}-\d{2}\s\d{2}:\d{2}:\d{2},\d+\s+-\s+([^\s][^\-]*?)\s+-\s+" ) _META_NOISE_MODULES = frozenset({ "collect_feedback_diagnostics.py", "prepare_feedback_issue.py", "submit_feedback_issue.py", "ask_user_choice.py", "base.py", "agent", "factory.py", "callback", "prompt", "memory.py", "activity_log.py", "message.py", "event.py", "chain", "discord", "telegram", "telegram.py", "execute_command.py", }) _VAGUE_KEYWORDS = frozenset({ "错误", "异常", "失败", "error", "exception", "failed", "warn", "warning", "日志", "问题", "bug", "log", "logs", }) _FEEDBACK_VERB_PHRASES: tuple[str, ...] = ( "反馈", "提交", "上报", "汇报", "提 issue", "提issue", "提 bug", "提bug", "提需求", "提交需求", "反馈需求", "提功能", "功能请求", "报 bug", "报bug", "报告 bug", "报告bug", "新建 issue", "新建issue", "开 issue", "开issue", "让上游", "给上游", "file an issue", "report a bug", "open an upstream issue", "submit an issue", "raise an issue", "report this upstream", "report upstream", "feature request", "submit a feature request", "open a feature request", ) _FEEDBACK_TARGET_TOKENS: tuple[str, ...] = ( "issue", "bug", "问题", "错误报告", "上游", "mp", "moviepilot", "需求", "功能", "feature", ) _FEEDBACK_STANDALONE_PHRASES: tuple[str, ...] = ( "file an issue", "report a bug", "open an upstream issue", "submit an issue", "raise an issue", "report this upstream", "report upstream", "feature request", "submit a feature request", "open a feature request", "新建 issue", "新建issue", "开 issue", "开issue", "提 issue", "提issue", "提 bug", "提bug", "提需求", "提交需求", "反馈需求", "提功能请求", "功能请求", "报 bug", "报bug", "报告 bug", "报告bug", "让上游", "给上游", ) _FEEDBACK_REGEX_PATTERNS: tuple[re.Pattern, ...] = ( re.compile(r"提.{0,6}(bug|issue|问题|错误报告)", re.IGNORECASE), re.compile(r"提.{0,6}(需求|功能请求|feature request)", re.IGNORECASE), re.compile(r"提交.{0,6}(需求|功能请求|feature request)", re.IGNORECASE), re.compile(r"报.{0,6}(bug|issue|错误报告)", re.IGNORECASE), re.compile(r"反馈.{0,8}(issue|bug|问题|上游|错误)", re.IGNORECASE), re.compile(r"反馈.{0,8}(需求|功能请求|feature request)", re.IGNORECASE), re.compile(r"开.{0,4}(issue|bug)", re.IGNORECASE), re.compile(r"开.{0,8}(需求|功能请求|feature request)", re.IGNORECASE), re.compile(r"上报.{0,6}(bug|issue|问题|错误)", re.IGNORECASE), ) def read_tail(path: Path) -> str: """读取日志文件尾部，避免大日志一次性进入内存。""" try: size = path.stat().st_size with path.open("rb") as file_obj: if size > _MAX_READ_BYTES: file_obj.seek(size - _MAX_READ_BYTES) return file_obj.read().decode("utf-8", errors="replace") except OSError: return "" def candidate_log_files() -> list[Path]: """返回反馈诊断可读取的主日志和插件日志文件。""" files = [settings.LOG_PATH / "moviepilot.log"] plugin_log_dir = settings.LOG_PATH / "plugins" if plugin_log_dir.exists(): files.extend(sorted(plugin_log_dir.rglob("*.log"))) return [path for path in files if path.exists() and path.is_file()] def collect_doctor_report() -> dict: """调用离线 doctor 命令收集结构化诊断报告。""" commands = [] moviepilot_bin = shutil.which("moviepilot") if moviepilot_bin: commands.append([moviepilot_bin, "doctor", "--json"]) commands.append([sys.executable, "-m", "app.cli", "doctor", "--json"]) for command in commands: try: result = subprocess.run( command, cwd=str(settings.ROOT_PATH), stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True, encoding="utf-8", errors="replace", timeout=30, check=False, ) except (OSError, subprocess.TimeoutExpired) as err: last_error = str(err) continue output = (result.stdout or "").strip() if not output: last_error = f"{' '.join(command)} 没有输出" continue try: payload = json_loads_from_output(output) except ValueError as err: last_error = str(err) continue payload["_command"] = " ".join(command) payload["_returncode"] = result.returncode return { "success": True, "report": payload, } return { "success": False, "error": last_error if "last_error" in locals() else "doctor 命令不可用", } def json_loads_from_output(output: str) -> dict: """从命令输出中解析 doctor JSON 对象。""" import json start = output.find("{") end = output.rfind("}") if start == -1 or end == -1 or end < start: raise ValueError("doctor 输出中未找到 JSON 对象") payload = json.loads(output[start:end + 1]) if not isinstance(payload, dict): raise ValueError("doctor JSON 顶层不是对象") return payload def normalize_keywords(keywords: Optional[list[str]]) -> list[str]: """过滤掉过短或过于宽泛的日志关键词。""" normalized: list[str] = [] for item in keywords or []: item = str(item or "").strip() if len(item) < 2: continue if item.lower() in _VAGUE_KEYWORDS: continue if item not in normalized: normalized.append(item) return normalized def has_explicit_feedback_intent(original_user_request: str) -> bool: """判断用户原话里是否出现明确要求提 Issue 的意图。""" if not original_user_request: return False normalized = original_user_request.lower().strip() if any(phrase in normalized for phrase in _FEEDBACK_STANDALONE_PHRASES): return True if any(pattern.search(normalized) for pattern in _FEEDBACK_REGEX_PATTERNS): return True has_verb = any(phrase in normalized for phrase in _FEEDBACK_VERB_PHRASES) has_target = any(token in normalized for token in _FEEDBACK_TARGET_TOKENS) return has_verb and has_target def normalize_window(time_window_minutes: int) -> int: """把传入的时间窗限制到 5 到 1440 分钟之间。""" try: window = int(time_window_minutes or _DEFAULT_TIME_WINDOW_MINUTES) except (TypeError, ValueError): window = _DEFAULT_TIME_WINDOW_MINUTES return max(_MIN_TIME_WINDOW_MINUTES, min(_MAX_TIME_WINDOW_MINUTES, window)) def parse_line_timestamp(line: str) -> Optional[datetime]: """从一行日志开头提取时间戳；提取不到返回 None。""" match = _LOG_TIMESTAMP_RE.search(line[:64]) if not match: return None try: return datetime.strptime(match.group(1), _LOG_TIMESTAMP_FORMAT) except ValueError: return None def is_meta_noise(line: str) -> bool: """判断日志行是否来自 Agent 自身的工具调度或消息框架噪音。""" match = _LOG_MODULE_RE.match(line) if not match: return False return match.group(1).strip() in _META_NOISE_MODULES def filter_lines( text: str, keywords: list[str], max_lines: int, window_start: datetime, ) -> tuple[list[str], list[str]]: """按时间窗、模块噪音和关键词筛选日志行。""" candidates: list[str] = [] last_seen_in_window: Optional[bool] = None last_seen_was_meta = False for line in text.splitlines(): if not line.strip(): continue timestamp = parse_line_timestamp(line) if timestamp is not None: in_window = timestamp >= window_start meta = is_meta_noise(line) last_seen_was_meta = meta last_seen_in_window = in_window and not meta if in_window and not meta: candidates.append(line) elif last_seen_in_window and not last_seen_was_meta: candidates.append(line) if not candidates: return [], [] if not keywords: return [], [] lowered_keywords = [item.lower() for item in keywords] matched: list[str] = [] matched_keywords: set[str] = set() keep_block = False for line in candidates: has_timestamp = parse_line_timestamp(line) is not None if has_timestamp: line_keywords = [ keyword for keyword, lowered in zip(keywords, lowered_keywords) if lowered in line.lower() ] keep_block = bool(line_keywords) if keep_block: matched_keywords.update(line_keywords) matched.append(line) elif keep_block: matched.append(line) if matched: return matched[-max_lines:], sorted(matched_keywords) return [], [] def collect_diagnostics( *, original_user_request: str, keywords: list[str], max_lines: int, time_window_minutes: int, ) -> dict: """读取日志、筛选、脱敏并写入运行时诊断文件。""" if not has_explicit_feedback_intent(original_user_request): return { "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，" "请先回到常规诊断路径；只有明确说出反馈 issue / 提 issue / 报 bug " "等意图时才运行 feedback-issue 流程。" ), } normalized_max_lines = min(max(int(max_lines or 80), 20), 200) window_minutes = normalize_window(time_window_minutes) window_start = datetime.now() - timedelta(minutes=window_minutes) normalized_keywords = normalize_keywords(keywords) collected: list[str] = [] source_files: list[str] = [] matched_files: list[dict] = [] for path in candidate_log_files(): text = read_tail(path) if not text: continue lines, matched_keywords = filter_lines( text=text, keywords=normalized_keywords, max_lines=normalized_max_lines, window_start=window_start, ) if not lines: continue source_files.append(str(path)) matched_files.append({ "path": str(path), "matched_keywords": matched_keywords, "line_count": len(lines), }) collected.append(f"### {path.name}\n" + "\n".join(lines)) logs = sanitize_logs("\n\n".join(collected), MAX_LOGS_CHARS) log_selection = { "strategy": "time_window_and_keyword_block_match", "time_window_minutes": window_minutes, "window_start": window_start.isoformat(timespec="seconds"), "keywords": normalized_keywords, "max_lines_per_file": normalized_max_lines, "matched_files": matched_files, "warning": ( "未提供具体关键词，已跳过日志正文收集以避免误带无关日志。" if not normalized_keywords else "" ), } diagnostics_file = runtime_file("diagnostics", ".json") diagnostics = { "original_user_request": original_user_request, "keywords": normalized_keywords, "found": bool(logs.strip()), "logs": logs, "log_selection": log_selection, "doctor": collect_doctor_report(), "source_files": source_files, "created_at": datetime.now().isoformat(timespec="seconds"), } write_json_file(diagnostics_file, diagnostics) return { "success": True, "found": diagnostics["found"], "diagnostics_file": str(diagnostics_file), "runtime_dir": str(feedback_runtime_dir()), "source_files": source_files, "log_selection_summary": format_log_selection(log_selection), "log_bytes": len(logs.encode("utf-8", errors="replace")), "log_lines": len(logs.splitlines()) if logs else 0, "doctor_collected": bool(diagnostics["doctor"].get("success")), "message": ( "已收集并写入反馈诊断日志文件。" if logs else "已完成诊断日志收集，但未找到明显相关日志。" ), } def parse_args() -> argparse.Namespace: """解析命令行参数。""" parser = argparse.ArgumentParser(description="收集 MoviePilot 反馈 Issue 诊断日志") parser.add_argument("--original-user-request", required=True, help="触发反馈的用户原话") parser.add_argument("--keyword", action="append", default=[], help="用于过滤日志的具体关键词，可重复") parser.add_argument("--max-lines", type=int, default=80, help="最多保留的日志行数") parser.add_argument( "--time-window-minutes", type=int, default=_DEFAULT_TIME_WINDOW_MINUTES, help="只收集最近 N 分钟日志，默认 30", ) return parser.parse_args() def main() -> int: """脚本入口：输出 JSON 结果给 Agent 解析。""" args = parse_args() result = collect_diagnostics( original_user_request=args.original_user_request, keywords=args.keyword, max_lines=args.max_lines, time_window_minutes=args.time_window_minutes, ) print(result_payload(**result)) return 0 if result.get("success") else 2 if __name__ == "__main__": raise SystemExit(main())