JOJO
72a49a7c8d
- 新增 server/work_timer.py，在对话真正空闲（无前台任务、无后台子智能体/后台命令/压缩）时持久化 work_timer，并同步内存副本，解决刷新后计时器回退问题。 - server/chat_flow_task_main.py / chat_flow.py / tasks/models.py 在任务结束/取消时按空闲判定决定是否持久化。 - 前端 lifecycle.ts 在仍有后台任务时不提前停止计时器。 - 子智能体工具（create/terminate/get_status）渲染美化，task 参数放在顶部元信息区。 - 子智能体状态查询支持返回「已完成」「已终止」「不存在」；修复 wait_for_completion 在 final_result 就绪前返回导致的「ID 被占用」误报。 - 统一后台完成通知池 poll_completion_notifications，合并子智能体与后台 run_command 两路轮询，避免逐条触发工作循环与单工作区互斥冲突。 - 删除本次新增的各类 debug_log / notify_pool_log 调用及辅助脚本。
567 lines
24 KiB
Python
567 lines
24 KiB
Python
# utils/conversation_manager.py - 对话持久化管理器（集成Token统计）
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import json
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import os
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import time
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import tempfile
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import threading
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from datetime import datetime
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from pathlib import Path
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from typing import Dict, List, Optional, Any
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from dataclasses import dataclass
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try:
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from config import DATA_DIR, HOST_WORKSPACES_FILE
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except ImportError:
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import sys
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from pathlib import Path
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project_root = Path(__file__).resolve().parents[1]
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if str(project_root) not in sys.path:
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sys.path.insert(0, str(project_root))
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from config import DATA_DIR, HOST_WORKSPACES_FILE
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@dataclass
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class ConversationMetadata:
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"""对话元数据"""
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id: str
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title: str
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created_at: str
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updated_at: str
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project_path: Optional[str]
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project_relative_path: Optional[str]
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thinking_mode: bool
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total_messages: int
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total_tools: int
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run_mode: str = "fast"
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model_key: Optional[str] = None
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has_images: bool = False
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has_videos: bool = False
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status: str = "active" # active, archived, error
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class CrudMixin:
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"""ConversationManager crud mixin 能力 mixin。"""
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def create_conversation(
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self,
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project_path: str,
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thinking_mode: bool = False,
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run_mode: str = "fast",
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initial_messages: List[Dict] = None,
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model_key: Optional[str] = None,
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has_images: bool = False,
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has_videos: bool = False,
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metadata_overrides: Optional[Dict[str, Any]] = None
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) -> str:
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"""
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创建新对话
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Args:
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project_path: 项目路径
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thinking_mode: 思考模式
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initial_messages: 初始消息列表
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Returns:
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conversation_id: 对话ID
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"""
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conversation_id = self._generate_conversation_id()
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messages = initial_messages or []
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# 创建对话数据
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path_metadata = self._prepare_project_path_metadata(project_path)
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normalized_mode = run_mode if run_mode in {"fast", "thinking", "deep"} else ("thinking" if thinking_mode else "fast")
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metadata = {
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"project_path": path_metadata["project_path"],
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"project_relative_path": path_metadata["project_relative_path"],
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"thinking_mode": thinking_mode,
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"run_mode": normalized_mode,
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"model_key": model_key,
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"permission_mode": "unrestricted",
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"execution_mode": "sandbox",
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"pending_permission_mode": None,
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"pending_execution_mode": None,
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"frozen_permission_prompt": None,
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"frozen_execution_prompt": None,
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"has_images": has_images,
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"has_videos": has_videos,
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# 首次对话尚未生成文件树快照，待首次用户消息时填充
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"project_file_tree": None,
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"project_statistics": None,
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"project_snapshot_at": None,
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"total_messages": len(messages),
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"total_tools": self._count_tools_in_messages(messages),
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"status": "active",
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# 压缩相关字段
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"compression_count": 0,
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"is_long_conversation": False,
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"is_ultra_long_conversation": False,
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"tool_call_count": 0,
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"last_shallow_compress_tool_count": 0,
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"compression_in_progress": False,
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"compression_mode": None,
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"compression_stage": None,
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"compression_job_id": None,
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"compression_error": None,
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"compression_resume_payload": None,
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"deep_compression_records": [],
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"last_deep_compression_record": None,
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"skip_auto_title_generation": False,
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}
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if isinstance(metadata_overrides, dict):
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metadata.update(metadata_overrides)
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conversation_data = {
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"id": conversation_id,
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"title": self._extract_title_from_messages(messages),
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"created_at": datetime.now().isoformat(),
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"updated_at": datetime.now().isoformat(),
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"messages": messages,
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"todo_list": None,
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"metadata": metadata,
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"token_statistics": self._initialize_token_statistics() # 新增
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}
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# 保存对话文件
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self._save_conversation_file(conversation_id, conversation_data)
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# 更新索引
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self._update_index(conversation_id, conversation_data)
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self.current_conversation_id = conversation_id
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print(f"📝 创建新对话: {conversation_id} - {conversation_data['title']}")
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return conversation_id
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def update_conversation_metadata(self, conversation_id: str, updates: Dict[str, Any]) -> bool:
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"""合并更新对话 metadata。"""
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if not conversation_id or not isinstance(updates, dict):
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return False
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try:
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data = self.load_conversation(conversation_id)
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if not data:
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return False
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metadata = data.get("metadata", {}) or {}
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metadata.update(updates)
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data["metadata"] = metadata
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data["updated_at"] = datetime.now().isoformat()
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self._save_conversation_file(conversation_id, data)
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self._update_index(conversation_id, data)
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return True
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except Exception as exc:
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print(f"⚠️ 更新对话 metadata 失败 {conversation_id}: {exc}")
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return False
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def update_conversation_title(self, conversation_id: str, title: str) -> bool:
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"""更新对话标题并刷新索引。"""
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if not conversation_id or not title:
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return False
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try:
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data = self.load_conversation(conversation_id)
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if not data:
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return False
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data["title"] = title
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data["updated_at"] = datetime.now().isoformat()
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meta = data.get("metadata", {}) or {}
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meta["title_locked"] = True
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data["metadata"] = meta
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self._save_conversation_file(conversation_id, data)
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self._update_index(conversation_id, data)
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if self.current_conversation_id == conversation_id:
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self.current_conversation_title = title
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return True
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except Exception as exc:
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print(f"⚠️ 更新对话标题失败 {conversation_id}: {exc}")
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return False
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def _save_conversation_file(self, conversation_id: str, data: Dict):
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"""保存对话文件"""
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file_path = self._get_conversation_file_path(conversation_id)
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try:
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# 确保Token统计数据有效
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data = self._validate_token_statistics(data)
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with self._io_lock:
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self._atomic_write_json(file_path, data)
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except Exception as e:
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print(f"⌘ 保存对话文件失败 {conversation_id}: {e}")
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def _update_index(self, conversation_id: str, conversation_data: Dict):
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"""更新对话索引"""
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try:
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index = self._load_index()
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# 创建元数据
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metadata = ConversationMetadata(
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id=conversation_id,
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title=conversation_data["title"],
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created_at=conversation_data["created_at"],
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updated_at=conversation_data["updated_at"],
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project_path=conversation_data["metadata"]["project_path"],
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project_relative_path=conversation_data["metadata"].get("project_relative_path"),
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thinking_mode=conversation_data["metadata"]["thinking_mode"],
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run_mode=conversation_data["metadata"].get("run_mode", "thinking" if conversation_data["metadata"]["thinking_mode"] else "fast"),
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total_messages=conversation_data["metadata"]["total_messages"],
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total_tools=conversation_data["metadata"]["total_tools"],
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status=conversation_data["metadata"].get("status", "active")
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)
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# 添加到索引
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index[conversation_id] = {
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"title": metadata.title,
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"created_at": metadata.created_at,
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"updated_at": metadata.updated_at,
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"project_path": metadata.project_path,
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"project_relative_path": metadata.project_relative_path,
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"thinking_mode": metadata.thinking_mode,
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"run_mode": metadata.run_mode,
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"model_key": conversation_data["metadata"].get("model_key"),
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"has_images": conversation_data["metadata"].get("has_images", False),
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"has_videos": conversation_data["metadata"].get("has_videos", False),
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"total_messages": metadata.total_messages,
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"total_tools": metadata.total_tools,
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"status": metadata.status
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}
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self._save_index(index)
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except Exception as e:
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print(f"⌘ 更新对话索引失败: {e}")
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def save_conversation(
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self,
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conversation_id: str,
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messages: List[Dict],
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project_path: str = None,
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thinking_mode: bool = None,
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run_mode: Optional[str] = None,
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todo_list: Optional[Dict] = None,
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model_key: Optional[str] = None,
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has_images: Optional[bool] = None,
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has_videos: Optional[bool] = None,
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project_file_tree: Optional[str] = None,
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project_statistics: Optional[Dict] = None,
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project_snapshot_at: Optional[str] = None
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) -> bool:
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"""
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保存对话（更新现有对话）
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Args:
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conversation_id: 对话ID
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messages: 消息列表
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project_path: 项目路径
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thinking_mode: 思考模式
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Returns:
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bool: 保存是否成功
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"""
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try:
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# 加载现有对话数据
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existing_data = self.load_conversation(conversation_id)
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if not existing_data:
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print(f"⚠️ 对话 {conversation_id} 不存在，无法更新")
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return False
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# 更新数据
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existing_data["messages"] = messages
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existing_data["updated_at"] = datetime.now().isoformat()
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# 更新标题（如未锁定自动标题时，仍按首条消息回退）
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title_locked = existing_data.get("metadata", {}).get("title_locked", False)
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if not title_locked:
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new_title = self._extract_title_from_messages(messages)
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if new_title != "新对话":
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existing_data["title"] = new_title
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# 更新元数据
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if project_path is not None:
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path_metadata = self._prepare_project_path_metadata(project_path)
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existing_data["metadata"]["project_path"] = path_metadata["project_path"]
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existing_data["metadata"]["project_relative_path"] = path_metadata["project_relative_path"]
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else:
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existing_data["metadata"].setdefault("project_relative_path", None)
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if thinking_mode is not None:
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existing_data["metadata"]["thinking_mode"] = thinking_mode
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if run_mode:
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normalized_mode = run_mode if run_mode in {"fast", "thinking", "deep"} else (
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"thinking" if existing_data["metadata"].get("thinking_mode") else "fast"
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)
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existing_data["metadata"]["run_mode"] = normalized_mode
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elif "run_mode" not in existing_data["metadata"]:
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existing_data["metadata"]["run_mode"] = "thinking" if existing_data["metadata"].get("thinking_mode") else "fast"
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# 推断最新使用的模型（优先参数，其次倒序扫描助手消息）
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inferred_model = None
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if model_key is None:
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for msg in reversed(messages):
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if msg.get("role") != "assistant":
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continue
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msg_meta = msg.get("metadata") or {}
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mk = msg_meta.get("model_key")
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if mk:
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inferred_model = mk
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break
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target_model = model_key if model_key is not None else inferred_model
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if target_model is not None:
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existing_data["metadata"]["model_key"] = target_model
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elif "model_key" not in existing_data["metadata"]:
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existing_data["metadata"]["model_key"] = None
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if has_images is not None:
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existing_data["metadata"]["has_images"] = bool(has_images)
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elif "has_images" not in existing_data["metadata"]:
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existing_data["metadata"]["has_images"] = False
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if has_videos is not None:
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existing_data["metadata"]["has_videos"] = bool(has_videos)
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elif "has_videos" not in existing_data["metadata"]:
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existing_data["metadata"]["has_videos"] = False
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# 文件树快照（如果有新值则更新，若已有则保持）
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if project_file_tree is not None:
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existing_data["metadata"]["project_file_tree"] = project_file_tree
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elif "project_file_tree" not in existing_data["metadata"]:
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existing_data["metadata"]["project_file_tree"] = None
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if project_statistics is not None:
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existing_data["metadata"]["project_statistics"] = project_statistics
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elif "project_statistics" not in existing_data["metadata"]:
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existing_data["metadata"]["project_statistics"] = None
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if project_snapshot_at is not None:
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existing_data["metadata"]["project_snapshot_at"] = project_snapshot_at
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elif "project_snapshot_at" not in existing_data["metadata"]:
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existing_data["metadata"]["project_snapshot_at"] = None
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existing_data["metadata"]["total_messages"] = len(messages)
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existing_data["metadata"]["total_tools"] = self._count_tools_in_messages(messages)
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# 更新待办列表
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existing_data["todo_list"] = todo_list
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# 确保Token统计结构存在（向后兼容）
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if "token_statistics" not in existing_data:
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existing_data["token_statistics"] = self._initialize_token_statistics()
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else:
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existing_data["token_statistics"]["updated_at"] = datetime.now().isoformat()
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# 保存文件
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self._save_conversation_file(conversation_id, existing_data)
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# 更新索引
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self._update_index(conversation_id, existing_data)
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return True
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except Exception as e:
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print(f"⌘ 保存对话失败 {conversation_id}: {e}")
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return False
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def mark_latest_user_work_completed(
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self,
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conversation_id: str,
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finished_at: Optional[str] = None,
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context_manager: Optional[Any] = None,
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) -> bool:
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"""将对话中最后一条 status 为 working 的用户消息的 work_timer 标记为完成。
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用于任务停止或正常结束后，刷新页面时不再恢复为"工作中"状态。
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Args:
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conversation_id: 要处理的对话 ID。
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finished_at: 完成时间 ISO 字符串，默认当前时间。
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context_manager: 可选的当前 ContextManager 实例；若提供，会同步更新
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其内存中的 conversation_history，避免后续 auto_save 把已持久化的
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完成状态覆盖回去。
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"""
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if not conversation_id:
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return False
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try:
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data = self.load_conversation(conversation_id)
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if not data:
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return False
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messages = data.get("messages") or []
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completed = False
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now_iso = finished_at or datetime.now().isoformat()
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for msg in reversed(messages):
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if not isinstance(msg, dict) or msg.get("role") != "user":
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continue
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metadata = msg.get("metadata") or {}
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timer = metadata.get("work_timer")
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if not isinstance(timer, dict):
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continue
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if timer.get("status") != "working":
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continue
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started_at = timer.get("started_at") or msg.get("timestamp") or now_iso
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try:
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start_dt = datetime.fromisoformat(str(started_at).replace("Z", "+00:00"))
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end_dt = datetime.fromisoformat(now_iso.replace("Z", "+00:00"))
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duration_ms = max(0, int((end_dt - start_dt).total_seconds() * 1000))
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except Exception:
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duration_ms = timer.get("duration_ms", 0) or 0
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timer["status"] = "completed"
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timer["started_at"] = started_at
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timer["finished_at"] = now_iso
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timer["duration_ms"] = duration_ms
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msg["metadata"] = metadata
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completed = True
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break
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if not completed:
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return False
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data["updated_at"] = datetime.now().isoformat()
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self._save_conversation_file(conversation_id, data)
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self._update_index(conversation_id, data)
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# 同步内存副本（如果调用方持有当前对话的内存引用）
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if (
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context_manager
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and getattr(context_manager, "current_conversation_id", None) == conversation_id
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):
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try:
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self._sync_work_timer_in_memory(context_manager, now_iso)
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except Exception:
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pass
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return True
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except Exception as exc:
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print(f"⌘ 标记用户工作完成失败 {conversation_id}: {exc}")
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return False
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def _sync_work_timer_in_memory(self, context_manager: Any, finished_at: str) -> bool:
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"""将当前 ContextManager 内存中最后一条 working 的 work_timer 标记为完成。"""
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history = getattr(context_manager, "conversation_history", None) or []
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if not history:
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return False
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for msg in reversed(history):
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if not isinstance(msg, dict) or msg.get("role") != "user":
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continue
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metadata = msg.get("metadata") or {}
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timer = metadata.get("work_timer")
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if not isinstance(timer, dict):
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continue
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if timer.get("status") != "working":
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continue
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started_at = timer.get("started_at") or msg.get("timestamp") or finished_at
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||
try:
|
||
start_dt = datetime.fromisoformat(str(started_at).replace("Z", "+00:00"))
|
||
end_dt = datetime.fromisoformat(finished_at.replace("Z", "+00:00"))
|
||
duration_ms = max(0, int((end_dt - start_dt).total_seconds() * 1000))
|
||
except Exception:
|
||
duration_ms = timer.get("duration_ms", 0) or 0
|
||
|
||
timer.update({
|
||
"status": "completed",
|
||
"started_at": started_at,
|
||
"finished_at": finished_at,
|
||
"duration_ms": duration_ms,
|
||
})
|
||
msg["metadata"] = metadata
|
||
return True
|
||
|
||
return False
|
||
|
||
def update_project_snapshot(
|
||
self,
|
||
conversation_id: str,
|
||
project_file_tree: str,
|
||
project_statistics: Optional[Dict],
|
||
project_snapshot_at: Optional[str] = None
|
||
) -> bool:
|
||
"""
|
||
单独更新对话的项目文件树快照，不修改消息内容。
|
||
便于在首次用户消息时写入固定文件结构。
|
||
"""
|
||
try:
|
||
data = self.load_conversation(conversation_id)
|
||
if not data:
|
||
return False
|
||
meta = data.get("metadata", {}) or {}
|
||
meta["project_file_tree"] = project_file_tree
|
||
meta["project_statistics"] = project_statistics
|
||
meta["project_snapshot_at"] = project_snapshot_at
|
||
data["metadata"] = meta
|
||
self._save_conversation_file(conversation_id, data)
|
||
self._update_index(conversation_id, data)
|
||
return True
|
||
except Exception as exc:
|
||
print(f"⌘ 更新项目快照失败 {conversation_id}: {exc}")
|
||
return False
|
||
|
||
def load_conversation(self, conversation_id: str) -> Optional[Dict]:
|
||
"""
|
||
加载对话数据
|
||
|
||
Args:
|
||
conversation_id: 对话ID
|
||
|
||
Returns:
|
||
Dict: 对话数据，如果不存在返回None
|
||
"""
|
||
try:
|
||
file_path = self._get_conversation_file_path(conversation_id)
|
||
if not file_path.exists():
|
||
return None
|
||
|
||
with open(file_path, 'r', encoding='utf-8') as f:
|
||
content = f.read().strip()
|
||
if not content:
|
||
return None
|
||
|
||
data = json.loads(content)
|
||
|
||
metadata = data.get("metadata", {})
|
||
if "project_relative_path" not in metadata:
|
||
metadata["project_relative_path"] = None
|
||
self._save_conversation_file(conversation_id, data)
|
||
print(f"🔧 为对话 {conversation_id} 添加相对路径字段")
|
||
|
||
# 向后兼容：确保Token统计结构存在
|
||
if "token_statistics" not in data:
|
||
data["token_statistics"] = self._initialize_token_statistics()
|
||
# 自动保存修复后的数据
|
||
self._save_conversation_file(conversation_id, data)
|
||
print(f"🔧 为对话 {conversation_id} 添加Token统计结构")
|
||
else:
|
||
# 验证现有Token统计数据
|
||
data = self._validate_token_statistics(data)
|
||
|
||
if "run_mode" not in metadata:
|
||
metadata["run_mode"] = "thinking" if metadata.get("thinking_mode") else "fast"
|
||
self._save_conversation_file(conversation_id, data)
|
||
print(f"🔧 为对话 {conversation_id} 添加运行模式字段")
|
||
|
||
# 确保项目快照字段存在（向后兼容）
|
||
changed = False
|
||
if "project_file_tree" not in metadata:
|
||
metadata["project_file_tree"] = None
|
||
changed = True
|
||
if "project_statistics" not in metadata:
|
||
metadata["project_statistics"] = None
|
||
changed = True
|
||
if "project_snapshot_at" not in metadata:
|
||
metadata["project_snapshot_at"] = None
|
||
changed = True
|
||
if changed:
|
||
data["metadata"] = metadata
|
||
self._save_conversation_file(conversation_id, data)
|
||
print(f"🔧 为对话 {conversation_id} 补齐项目快照字段")
|
||
|
||
# 兼容历史口径：旧版本 total_tools 可能把 role=tool 也计入，导致翻倍。
|
||
expected_total_tools = self._count_tools_in_messages(data.get("messages") or [])
|
||
if int(metadata.get("total_tools", 0) or 0) != expected_total_tools:
|
||
metadata["total_tools"] = expected_total_tools
|
||
data["metadata"] = metadata
|
||
self._save_conversation_file(conversation_id, data)
|
||
self._update_index(conversation_id, data)
|
||
print(f"🔧 修正对话 {conversation_id} 的 total_tools 统计为 {expected_total_tools}")
|
||
|
||
# 回填缺失的模型字段：从最近的助手消息元数据推断
|
||
if metadata.get("model_key") is None:
|
||
inferred_model = None
|
||
for msg in reversed(data.get("messages") or []):
|
||
if msg.get("role") != "assistant":
|
||
continue
|
||
mk = (msg.get("metadata") or {}).get("model_key")
|
||
if mk:
|
||
inferred_model = mk
|
||
break
|
||
if inferred_model is not None:
|
||
metadata["model_key"] = inferred_model
|
||
self._save_conversation_file(conversation_id, data)
|
||
print(f"🔧 为对话 {conversation_id} 回填模型字段: {inferred_model}")
|
||
|
||
return data
|
||
except (json.JSONDecodeError, Exception) as e:
|
||
print(f"⌘ 加载对话失败 {conversation_id}: {e}")
|
||
return None
|