agent-Specialization/core/main_terminal.py

# core/main_terminal.py - 主终端（集成对话持久化）

import asyncio
import json
from datetime import datetime
from pathlib import Path
from typing import Any, Dict, List, Optional, Set, TYPE_CHECKING
from datetime import datetime

try:
    from config import (
        OUTPUT_FORMATS, DATA_DIR, PROMPTS_DIR, NEED_CONFIRMATION,
        MAX_TERMINALS, TERMINAL_BUFFER_SIZE, TERMINAL_DISPLAY_SIZE,
        MAX_READ_FILE_CHARS, READ_TOOL_DEFAULT_MAX_CHARS,
        READ_TOOL_DEFAULT_CONTEXT_BEFORE, READ_TOOL_DEFAULT_CONTEXT_AFTER,
        READ_TOOL_MAX_CONTEXT_BEFORE, READ_TOOL_MAX_CONTEXT_AFTER,
        READ_TOOL_DEFAULT_MAX_MATCHES, READ_TOOL_MAX_MATCHES,
        READ_TOOL_MAX_FILE_SIZE, MAX_FOCUS_FILE_CHARS,
        TERMINAL_SANDBOX_MOUNT_PATH,
        TERMINAL_SANDBOX_CPUS,
        TERMINAL_SANDBOX_MEMORY,
        PROJECT_MAX_STORAGE_MB,
    )
except ImportError:
    import sys
    from pathlib import Path
    project_root = Path(__file__).resolve().parents[1]
    if str(project_root) not in sys.path:
        sys.path.insert(0, str(project_root))
    from config import (
        OUTPUT_FORMATS, DATA_DIR, PROMPTS_DIR, NEED_CONFIRMATION,
        MAX_TERMINALS, TERMINAL_BUFFER_SIZE, TERMINAL_DISPLAY_SIZE,
        MAX_READ_FILE_CHARS, READ_TOOL_DEFAULT_MAX_CHARS,
        READ_TOOL_DEFAULT_CONTEXT_BEFORE, READ_TOOL_DEFAULT_CONTEXT_AFTER,
        READ_TOOL_MAX_CONTEXT_BEFORE, READ_TOOL_MAX_CONTEXT_AFTER,
        READ_TOOL_DEFAULT_MAX_MATCHES, READ_TOOL_MAX_MATCHES,
        READ_TOOL_MAX_FILE_SIZE, MAX_FOCUS_FILE_CHARS,
        TERMINAL_SANDBOX_MOUNT_PATH,
        TERMINAL_SANDBOX_CPUS,
        TERMINAL_SANDBOX_MEMORY,
        PROJECT_MAX_STORAGE_MB,
    )
from modules.file_manager import FileManager
from modules.search_engine import SearchEngine
from modules.terminal_ops import TerminalOperator
from modules.memory_manager import MemoryManager
from modules.terminal_manager import TerminalManager
from modules.todo_manager import TodoManager
from modules.sub_agent_manager import SubAgentManager
from modules.webpage_extractor import extract_webpage_content, tavily_extract
from modules.ocr_client import OCRClient
from modules.easter_egg_manager import EasterEggManager
from modules.personalization_manager import (
    load_personalization_config,
    build_personalization_prompt,
)
try:
    from config.limits import THINKING_FAST_INTERVAL
except ImportError:
    THINKING_FAST_INTERVAL = 10
from modules.container_monitor import collect_stats, inspect_state
from core.tool_config import TOOL_CATEGORIES
from utils.api_client import DeepSeekClient
from utils.context_manager import ContextManager
from utils.tool_result_formatter import format_tool_result_for_context
from utils.logger import setup_logger
from config.model_profiles import get_model_profile, get_model_prompt_replacements

if TYPE_CHECKING:
    from modules.user_container_manager import ContainerHandle

logger = setup_logger(__name__)
# 临时禁用长度检查
DISABLE_LENGTH_CHECK = True
class MainTerminal:
    def __init__(
        self,
        project_path: str,
        thinking_mode: bool = False,
        run_mode: Optional[str] = None,
        data_dir: Optional[str] = None,
        container_session: Optional["ContainerHandle"] = None,
        usage_tracker: Optional[object] = None,
    ):
        self.project_path = project_path
        allowed_modes = {"fast", "thinking", "deep"}
        initial_mode = run_mode if run_mode in allowed_modes else ("thinking" if thinking_mode else "fast")
        self.run_mode = initial_mode
        self.thinking_mode = initial_mode != "fast"  # False=快速模式, True=思考模式
        self.deep_thinking_mode = initial_mode == "deep"
        self.data_dir = Path(data_dir).expanduser().resolve() if data_dir else Path(DATA_DIR).resolve()
        self.usage_tracker = usage_tracker
        
        # 初始化组件
        self.api_client = DeepSeekClient(thinking_mode=self.thinking_mode)
        self.api_client.set_deep_thinking_mode(self.deep_thinking_mode)
        self.model_key = "kimi"
        self.model_profile = get_model_profile(self.model_key)
        self.apply_model_profile(self.model_profile)
        self.context_manager = ContextManager(project_path, data_dir=str(self.data_dir))
        self.context_manager.main_terminal = self
        self.container_mount_path = TERMINAL_SANDBOX_MOUNT_PATH or "/workspace"
        self.container_cpu_limit = TERMINAL_SANDBOX_CPUS or "未限制"
        self.container_memory_limit = TERMINAL_SANDBOX_MEMORY or "未限制"
        self.project_storage_limit = f"{PROJECT_MAX_STORAGE_MB}MB" if PROJECT_MAX_STORAGE_MB else "未限制"
        self.project_storage_limit_bytes = (
            PROJECT_MAX_STORAGE_MB * 1024 * 1024 if PROJECT_MAX_STORAGE_MB else None
        )
        self.container_session: Optional["ContainerHandle"] = None
        self.memory_manager = MemoryManager(data_dir=str(self.data_dir))
        self.file_manager = FileManager(project_path, container_session=container_session)
        self.search_engine = SearchEngine()
        self.terminal_ops = TerminalOperator(project_path, container_session=container_session)
        self.ocr_client = OCRClient(project_path, self.file_manager)
        self.pending_image_view = None  # 供 view_image 工具使用，保存一次性图片插入请求
        
        # 新增：终端管理器
        self.terminal_manager = TerminalManager(
            project_path=project_path,
            max_terminals=MAX_TERMINALS,
            terminal_buffer_size=TERMINAL_BUFFER_SIZE,
            terminal_display_size=TERMINAL_DISPLAY_SIZE,
            broadcast_callback=None,  # CLI模式不需要广播
            container_session=container_session,
        )
        self._apply_container_session(container_session)

        self.todo_manager = TodoManager(self.context_manager)
        self.sub_agent_manager = SubAgentManager(
            project_path=self.project_path,
            data_dir=str(self.data_dir)
        )
        self.easter_egg_manager = EasterEggManager()
        self._announced_sub_agent_tasks = set()
        
        # 聚焦文件管理
        self.focused_files = {}  # {path: content} 存储聚焦的文件内容
        
        self.current_session_id = 0  # 用于标识不同的任务会话
        # 工具启用状态
        self.tool_category_states = {
            key: category.default_enabled
            for key, category in TOOL_CATEGORIES.items()
        }
        self.disabled_tools = set()
        self.disabled_notice_tools = set()
        self._refresh_disabled_tools()
        self.thinking_fast_interval = THINKING_FAST_INTERVAL
        self.default_disabled_tool_categories: List[str] = []
        # 个性化工具意图开关
        self.tool_intent_enabled: bool = False
        self.apply_personalization_preferences()
        
        # 新增：自动开始新对话
        self._ensure_conversation()
        
        # 命令映射
        self.commands = {
            "help": self.show_help,
            "exit": self.exit_system,
            "status": self.show_status,
            "memory": self.manage_memory,
            "clear": self.clear_conversation,
            "history": self.show_history,
            "files": self.show_files,
            "mode": self.toggle_mode,
            "focused": self.show_focused_files,
            "terminals": self.show_terminals,
            # 新增：对话管理命令
            "conversations": self.show_conversations,
            "load": self.load_conversation_command,
            "new": self.new_conversation_command,
            "save": self.save_conversation_command
        }
        #self.context_manager._web_terminal_callback = message_callback
        #self.context_manager._focused_files = self.focused_files  # 引用传递

    def _apply_container_session(self, session: Optional["ContainerHandle"]):
        self.container_session = session
        if session and session.mode == "docker":
            self.container_mount_path = session.mount_path or (TERMINAL_SANDBOX_MOUNT_PATH or "/workspace")
        else:
            self.container_mount_path = TERMINAL_SANDBOX_MOUNT_PATH or "/workspace"

    def record_model_call(self, is_thinking: bool):
        tracker = getattr(self, "usage_tracker", None)
        if not tracker:
            return True, {}
        mode = "thinking" if is_thinking else "fast"
        try:
            allowed, info = tracker.check_and_increment(mode)
            if allowed:
                self._notify_quota_update(mode)
            return allowed, info
        except Exception:
            return True, {}

    def record_search_call(self):
        tracker = getattr(self, "usage_tracker", None)
        if not tracker:
            return True, {}
        try:
            allowed, info = tracker.check_and_increment("search")
            if allowed:
                self._notify_quota_update("search")
            return allowed, info
        except Exception:
            return True, {}

    def _notify_quota_update(self, metric: str):
        callback = getattr(self, "quota_update_callback", None)
        if callable(callback):
            try:
                callback(metric)
            except Exception:
                pass

    def update_container_session(self, session: Optional["ContainerHandle"]):
        self._apply_container_session(session)
        if getattr(self, "terminal_manager", None):
            self.terminal_manager.update_container_session(session)
        if getattr(self, "terminal_ops", None):
            self.terminal_ops.set_container_session(session)
        if getattr(self, "file_manager", None):
            self.file_manager.set_container_session(session)


    def _ensure_conversation(self):
        """确保CLI模式下存在可用的对话ID"""
        if self.context_manager.current_conversation_id:
            return

        latest_list = self.context_manager.get_conversation_list(limit=1, offset=0)
        conversations = latest_list.get("conversations", []) if latest_list else []

        if conversations:
            latest = conversations[0]
            conv_id = latest.get("id")
            if conv_id and self.context_manager.load_conversation_by_id(conv_id):
                print(f"{OUTPUT_FORMATS['info']} 已加载最近对话: {conv_id}")
                return

        conversation_id = self.context_manager.start_new_conversation(
            project_path=self.project_path,
            thinking_mode=self.thinking_mode,
            run_mode=self.run_mode
        )
        print(f"{OUTPUT_FORMATS['info']} 新建对话: {conversation_id}")

    @staticmethod
    def _clamp_int(value, default, min_value=None, max_value=None):
        """将输入转换为整数并限制范围。"""
        if value is None:
            return default
        try:
            num = int(value)
        except (TypeError, ValueError):
            return default
        if min_value is not None:
            num = max(min_value, num)
        if max_value is not None:
            num = min(max_value, num)
        return num

    @staticmethod
    def _parse_optional_line(value, field_name: str):
        """解析可选的行号参数。"""
        if value is None:
            return None, None
        try:
            number = int(value)
        except (TypeError, ValueError):
            return None, f"{field_name} 必须是整数"
        if number < 1:
            return None, f"{field_name} 必须大于等于1"
        return number, None

    @staticmethod
    def _truncate_text_block(text: str, max_chars: int):
        """对单段文本应用字符限制。"""
        if max_chars and len(text) > max_chars:
            return text[:max_chars], True, max_chars
        return text, False, len(text)

    @staticmethod
    def _limit_text_chunks(chunks: List[Dict], text_key: str, max_chars: int):
        """对多个文本片段应用全局字符限制。"""
        if max_chars is None or max_chars <= 0:
            return chunks, False, sum(len(chunk.get(text_key, "") or "") for chunk in chunks)
        
        remaining = max_chars
        limited_chunks: List[Dict] = []
        truncated = False
        consumed = 0
        
        for chunk in chunks:
            snippet = chunk.get(text_key, "") or ""
            snippet_len = len(snippet)
            chunk_copy = dict(chunk)
            
            if remaining <= 0:
                truncated = True
                break
            
            if snippet_len > remaining:
                chunk_copy[text_key] = snippet[:remaining]
                chunk_copy["truncated"] = True
                consumed += remaining
                limited_chunks.append(chunk_copy)
                truncated = True
                remaining = 0
                break
            
            limited_chunks.append(chunk_copy)
            consumed += snippet_len
            remaining -= snippet_len
        
        return limited_chunks, truncated, consumed

    def _record_sub_agent_message(self, message: Optional[str], task_id: Optional[str] = None, inline: bool = False):
        """以 system 消息记录子智能体状态。"""
        if not message:
            return
        if task_id and task_id in self._announced_sub_agent_tasks:
            return
        if task_id:
            self._announced_sub_agent_tasks.add(task_id)
        logger.info(
            "[SubAgent] record message | task=%s | inline=%s | content=%s",
            task_id,
            inline,
            message.replace("\n", "\\n")[:200],
        )
        metadata = {"sub_agent_notice": True, "inline": inline}
        if task_id:
            metadata["task_id"] = task_id
        self.context_manager.add_conversation("system", message, metadata=metadata)
        print(f"{OUTPUT_FORMATS['info']} {message}")

    def apply_personalization_preferences(self, config: Optional[Dict[str, Any]] = None):
        """Apply persisted personalization settings that affect runtime behavior."""
        try:
            effective_config = config or load_personalization_config(self.data_dir)
        except Exception:
            effective_config = {}

        # 工具意图开关
        self.tool_intent_enabled = bool(effective_config.get("tool_intent_enabled"))

        interval = effective_config.get("thinking_interval")
        if isinstance(interval, int) and interval > 0:
            self.thinking_fast_interval = interval
        else:
            self.thinking_fast_interval = THINKING_FAST_INTERVAL

        disabled_categories = []
        raw_disabled = effective_config.get("disabled_tool_categories")
        if isinstance(raw_disabled, list):
            disabled_categories = [
                key for key in raw_disabled
                if isinstance(key, str) and key in TOOL_CATEGORIES
            ]
        self.default_disabled_tool_categories = disabled_categories

        # Reset category states to defaults before applying overrides
        for key, category in TOOL_CATEGORIES.items():
            self.tool_category_states[key] = False if key in disabled_categories else category.default_enabled
        self._refresh_disabled_tools()

        # 默认模型偏好（优先应用，再处理运行模式）
        preferred_model = effective_config.get("default_model")
        if isinstance(preferred_model, str) and preferred_model != self.model_key:
            try:
                self.set_model(preferred_model)
            except Exception as exc:
                logger.warning("忽略无效默认模型: %s (%s)", preferred_model, exc)

        preferred_mode = effective_config.get("default_run_mode")
        if isinstance(preferred_mode, str):
            normalized_mode = preferred_mode.strip().lower()
            if normalized_mode in {"fast", "thinking", "deep"} and normalized_mode != self.run_mode:
                try:
                    self.set_run_mode(normalized_mode)
                except ValueError:
                    logger.warning("忽略无效默认运行模式: %s", preferred_mode)


    def _handle_read_tool(self, arguments: Dict) -> Dict:
        """集中处理 read_file 工具的三种模式。"""
        file_path = arguments.get("path")
        if not file_path:
            return {"success": False, "error": "缺少文件路径参数"}
        
        read_type = (arguments.get("type") or "read").lower()
        if read_type not in {"read", "search", "extract"}:
            return {"success": False, "error": f"未知的读取类型: {read_type}"}
        
        max_chars = self._clamp_int(
            arguments.get("max_chars"),
            READ_TOOL_DEFAULT_MAX_CHARS,
            1,
            MAX_READ_FILE_CHARS
        )
        
        base_result = {
            "success": True,
            "type": read_type,
            "path": None,
            "encoding": "utf-8",
            "max_chars": max_chars,
            "truncated": False
        }
        
        if read_type == "read":
            start_line, error = self._parse_optional_line(arguments.get("start_line"), "start_line")
            if error:
                return {"success": False, "error": error}
            end_line_val = arguments.get("end_line")
            end_line = None
            if end_line_val is not None:
                end_line, error = self._parse_optional_line(end_line_val, "end_line")
                if error:
                    return {"success": False, "error": error}
                if start_line and end_line < start_line:
                    return {"success": False, "error": "end_line 必须大于等于 start_line"}
            
            read_result = self.file_manager.read_text_segment(
                file_path,
                start_line=start_line,
                end_line=end_line,
                size_limit=READ_TOOL_MAX_FILE_SIZE
            )
            if not read_result.get("success"):
                return read_result
            
            content, truncated, char_count = self._truncate_text_block(read_result["content"], max_chars)
            base_result.update({
                "path": read_result["path"],
                "content": content,
                "line_start": read_result["line_start"],
                "line_end": read_result["line_end"],
                "total_lines": read_result["total_lines"],
                "file_size": read_result["size"],
                "char_count": char_count,
                "message": f"已读取 {read_result['path']} 的内容（行 {read_result['line_start']}~{read_result['line_end']}）"
            })
            base_result["truncated"] = truncated
            self.context_manager.load_file(read_result["path"])
            return base_result
        
        if read_type == "search":
            query = arguments.get("query")
            if not query:
                return {"success": False, "error": "搜索模式需要提供 query 参数"}
            
            max_matches = self._clamp_int(
                arguments.get("max_matches"),
                READ_TOOL_DEFAULT_MAX_MATCHES,
                1,
                READ_TOOL_MAX_MATCHES
            )
            context_before = self._clamp_int(
                arguments.get("context_before"),
                READ_TOOL_DEFAULT_CONTEXT_BEFORE,
                0,
                READ_TOOL_MAX_CONTEXT_BEFORE
            )
            context_after = self._clamp_int(
                arguments.get("context_after"),
                READ_TOOL_DEFAULT_CONTEXT_AFTER,
                0,
                READ_TOOL_MAX_CONTEXT_AFTER
            )
            case_sensitive = bool(arguments.get("case_sensitive"))
            
            search_result = self.file_manager.search_text(
                file_path,
                query=query,
                max_matches=max_matches,
                context_before=context_before,
                context_after=context_after,
                case_sensitive=case_sensitive,
                size_limit=READ_TOOL_MAX_FILE_SIZE
            )
            if not search_result.get("success"):
                return search_result
            
            matches = search_result["matches"]
            limited_matches, truncated, char_count = self._limit_text_chunks(matches, "snippet", max_chars)
            
            base_result.update({
                "path": search_result["path"],
                "file_size": search_result["size"],
                "query": query,
                "max_matches": max_matches,
                "actual_matches": len(matches),
                "returned_matches": len(limited_matches),
                "context_before": context_before,
                "context_after": context_after,
                "case_sensitive": case_sensitive,
                "matches": limited_matches,
                "char_count": char_count,
                "message": f"在 {search_result['path']} 中搜索 \"{query}\"，返回 {len(limited_matches)} 条结果"
            })
            base_result["truncated"] = truncated
            return base_result
        
        # extract
        segments = arguments.get("segments")
        if not isinstance(segments, list) or not segments:
            return {"success": False, "error": "extract 模式需要提供 segments 数组"}
        
        extract_result = self.file_manager.extract_segments(
            file_path,
            segments=segments,
            size_limit=READ_TOOL_MAX_FILE_SIZE
        )
        if not extract_result.get("success"):
            return extract_result
        
        limited_segments, truncated, char_count = self._limit_text_chunks(
            extract_result["segments"],
            "content",
            max_chars
        )
        
        base_result.update({
            "path": extract_result["path"],
            "segments": limited_segments,
            "file_size": extract_result["size"],
            "total_lines": extract_result["total_lines"],
            "segment_count": len(limited_segments),
            "char_count": char_count,
            "message": f"已从 {extract_result['path']} 抽取 {len(limited_segments)} 个片段"
        })
        base_result["truncated"] = truncated
        self.context_manager.load_file(extract_result["path"])
        return base_result

    def set_tool_category_enabled(self, category: str, enabled: bool) -> None:
        """设置工具类别的启用状态 / Toggle tool category enablement."""
        if category not in TOOL_CATEGORIES:
            raise ValueError(f"未知的工具类别: {category}")
        self.tool_category_states[category] = bool(enabled)
        self._refresh_disabled_tools()

    def get_tool_settings_snapshot(self) -> List[Dict[str, object]]:
        """获取工具类别状态快照 / Return tool category states snapshot."""
        snapshot: List[Dict[str, object]] = []
        for key, category in TOOL_CATEGORIES.items():
            snapshot.append({
                "id": key,
                "label": category.label,
                "enabled": self.tool_category_states.get(key, category.default_enabled),
                "tools": list(category.tools),
            })
        return snapshot

    def _refresh_disabled_tools(self) -> None:
        """刷新禁用工具列表 / Refresh disabled tool set."""
        disabled = set()
        notice = set()
        for key, enabled in self.tool_category_states.items():
            if not enabled:
                category = TOOL_CATEGORIES[key]
                disabled.update(category.tools)
                if not getattr(category, "silent_when_disabled", False):
                    notice.update(category.tools)
        self.disabled_tools = disabled
        self.disabled_notice_tools = notice

    def _format_disabled_tool_notice(self) -> Optional[str]:
        """生成禁用工具提示信息 / Format disabled tool notice."""
        if not self.disabled_notice_tools:
            return None

        lines = ["=== 工具可用性提醒 ==="]
        for tool_name in sorted(self.disabled_notice_tools):
            lines.append(f"{tool_name}：已被用户禁用")
        lines.append("=== 提示结束 ===")
        return "\n".join(lines)


    async def run(self):
        """运行主终端循环"""
        print(f"\n{OUTPUT_FORMATS['info']} 主终端已启动")
        print(f"{OUTPUT_FORMATS['info']} 当前对话: {self.context_manager.current_conversation_id}")

        while True:
            try:
                # 获取用户输入（使用人的表情）
                user_input = input("\n👤 > ").strip()
                
                if not user_input:
                    continue
                
                # 处理命令（命令不记录到对话历史）
                if user_input.startswith('/'):
                    await self.handle_command(user_input[1:])
                elif user_input.lower() in ['exit', 'quit', 'q']:
                    # 用户可能忘记加斜杠
                    print(f"{OUTPUT_FORMATS['info']} 提示: 使用 /exit 退出系统")
                    continue
                elif user_input.lower() == 'help':
                    print(f"{OUTPUT_FORMATS['info']} 提示: 使用 /help 查看帮助")
                    continue
                else:
                    # 确保有活动对话
                    self._ensure_conversation()
                    
                    # 只有非命令的输入才记录到对话历史
                    self.context_manager.add_conversation("user", user_input)
                    
                    # 新增：开始新的任务会话
                    self.current_session_id += 1
                    
                    # AI回复前空一行，并显示机器人图标
                    print("\n🤖 >", end=" ")
                    await self.handle_task(user_input)
                    # 回复后自动空一行（在handle_task完成后）
                
            except KeyboardInterrupt:
                print(f"\n{OUTPUT_FORMATS['warning']} 使用 /exit 退出系统")
                continue
            except Exception as e:
                logger.error(f"主终端错误: {e}", exc_info=True)
                print(f"{OUTPUT_FORMATS['error']} 发生错误: {e}")
                # 错误后仍然尝试自动保存
                try:
                    self.context_manager.auto_save_conversation()
                except:
                    pass
    
    async def handle_command(self, command: str):
        """处理系统命令"""
        parts = command.split(maxsplit=1)
        cmd = parts[0].lower()
        args = parts[1] if len(parts) > 1 else ""
        
        if cmd in self.commands:
            await self.commands[cmd](args)
        else:
            print(f"{OUTPUT_FORMATS['error']} 未知命令: {cmd}")
            await self.show_help()
    
    async def handle_task(self, user_input: str):
        """处理用户任务（完全修复版：彻底解决对话记录重复问题）"""
        try:
            # 如果是思考模式，每个新任务重置状态
            # 注意：这里重置的是当前任务的第一次调用标志，确保新用户请求重新思考
            if self.thinking_mode:
                self.api_client.start_new_task(force_deep=self.deep_thinking_mode)
            
            # 新增：开始新的任务会话
            self.current_session_id += 1
            
            # 构建上下文
            context = self.build_context()
            
            # 构建消息
            messages = self.build_messages(context, user_input)
            
            # 定义可用工具
            tools = self.define_tools()
            
            # 用于收集本次任务的所有信息（关键：不立即保存到对话历史）
            collected_tool_calls = []
            collected_tool_results = []
            final_response = ""
            final_thinking = ""
            
            # 工具处理器：只执行工具，收集信息，绝不保存到对话历史
            async def tool_handler(tool_name: str, arguments: Dict) -> str:
                # 执行工具调用
                result = await self.handle_tool_call(tool_name, arguments)
                
                # 生成工具调用ID
                tool_call_id = f"call_{datetime.now().timestamp()}_{tool_name}"
                
                # 收集工具调用信息（不保存）
                tool_call_info = {
                    "id": tool_call_id,
                    "type": "function", 
                    "function": {
                        "name": tool_name,
                        "arguments": json.dumps(arguments, ensure_ascii=False)
                    }
                }
                collected_tool_calls.append(tool_call_info)
                
                # 处理工具结果用于保存
                try:
                    parsed = json.loads(result)
                    result_data = parsed if isinstance(parsed, dict) else {}
                except Exception:
                    result_data = {}
                tool_result_content = format_tool_result_for_context(tool_name, result_data, result)
                
                # 收集工具结果（不保存）
                collected_tool_results.append({
                    "tool_call_id": tool_call_id,
                    "name": tool_name,
                    "content": tool_result_content,
                    "system_message": result_data.get("system_message") if isinstance(result_data, dict) else None,
                    "task_id": result_data.get("task_id") if isinstance(result_data, dict) else None,
                    "raw_result_data": result_data if result_data else None,
                })
                
                return result
            
            # 调用带工具的API（模型自己决定是否使用工具）
            response = await self.api_client.chat_with_tools(
                messages=messages,
                tools=tools,
                tool_handler=tool_handler
            )
            
            # 保存响应内容
            final_response = response
            
            # 获取思考内容（如果有的话）
            if self.api_client.current_task_thinking:
                final_thinking = self.api_client.current_task_thinking
            
            # ===== 统一保存到对话历史（关键修复） =====
            
            # 1. 构建助手回复内容（思考内容通过 reasoning_content 存储）
            assistant_content = final_response or "已完成操作。"
            
            # 2. 保存assistant消息（包含tool_calls但不包含结果）
            self.context_manager.add_conversation(
                "assistant",
                assistant_content,
                collected_tool_calls if collected_tool_calls else None,
                reasoning_content=final_thinking or None
            )
            
            # 3. 保存独立的tool消息
            for tool_result in collected_tool_results:
                self.context_manager.add_conversation(
                    "tool",
                    tool_result["content"],
                    tool_call_id=tool_result["tool_call_id"],
                    name=tool_result["name"]
                )
                system_message = tool_result.get("system_message")
                if system_message:
                    self._record_sub_agent_message(system_message, tool_result.get("task_id"), inline=False)
                # 补充TODO完成提示，放在tool消息之后保证格式正确
                raw_payload = tool_result.get("raw_result_data") or {}
                todo_note = raw_payload.get("system_note")
                if todo_note:
                    self.context_manager.add_conversation("system", todo_note)
            
            # 4. 在终端显示执行信息（不保存到历史）
            if collected_tool_calls:
                tool_names = [tc['function']['name'] for tc in collected_tool_calls]
                
                for tool_name in tool_names:
                    if tool_name == "create_file":
                        print(f"{OUTPUT_FORMATS['file']} 创建文件")
                    elif tool_name == "read_file":
                        print(f"{OUTPUT_FORMATS['file']} 读取文件")
                    elif tool_name in {"vlm_analyze", "ocr_image"}:
                        print(f"{OUTPUT_FORMATS['file']} VLM 视觉理解")
                    elif tool_name == "write_file_diff":
                        print(f"{OUTPUT_FORMATS['file']} 应用补丁")
                    elif tool_name == "delete_file":
                        print(f"{OUTPUT_FORMATS['file']} 删除文件")
                    elif tool_name == "terminal_session":
                        print(f"{OUTPUT_FORMATS['session']} 终端会话操作")
                    elif tool_name == "terminal_input":
                        print(f"{OUTPUT_FORMATS['terminal']} 执行终端命令")
                    elif tool_name == "web_search":
                        print(f"{OUTPUT_FORMATS['search']} 网络搜索")
                    elif tool_name == "run_python":
                        print(f"{OUTPUT_FORMATS['code']} 执行Python代码")
                    elif tool_name == "run_command":
                        print(f"{OUTPUT_FORMATS['terminal']} 执行系统命令")
                    elif tool_name == "update_memory":
                        print(f"{OUTPUT_FORMATS['memory']} 更新记忆")
                    elif tool_name == "focus_file":
                        print(f"🔍 聚焦文件")
                    elif tool_name == "unfocus_file":
                        print(f"❌ 取消聚焦")
                    elif tool_name == "sleep":
                        print(f"{OUTPUT_FORMATS['info']} 等待操作")
                    else:
                        print(f"{OUTPUT_FORMATS['action']} 执行: {tool_name}")
                
                if len(tool_names) > 1:
                    print(f"{OUTPUT_FORMATS['info']} 共执行 {len(tool_names)} 个操作")
                    
        except Exception as e:
            logger.error(f"任务处理错误: {e}", exc_info=True)
            print(f"{OUTPUT_FORMATS['error']} 任务处理失败: {e}")
            # 错误时也尝试自动保存
            try:
                self.context_manager.auto_save_conversation()
            except:
                pass
    async def show_conversations(self, args: str = ""):
        """显示对话列表"""
        try:
            limit = 10  # 默认显示最近10个对话
            if args:
                try:
                    limit = int(args)
                    limit = max(1, min(limit, 50))  # 限制在1-50之间
                except ValueError:
                    print(f"{OUTPUT_FORMATS['warning']} 无效数量，使用默认值10")
                    limit = 10
            
            conversations = self.context_manager.get_conversation_list(limit=limit)
            
            if not conversations["conversations"]:
                print(f"{OUTPUT_FORMATS['info']} 暂无对话记录")
                return
            
            print(f"\n📚 最近 {len(conversations['conversations'])} 个对话:")
            print("="*70)
            
            for i, conv in enumerate(conversations["conversations"], 1):
                # 状态图标
                status_icon = "🟢" if conv["status"] == "active" else "📦" if conv["status"] == "archived" else "❌"
                
                # 当前对话标记
                current_mark = " [当前]" if conv["id"] == self.context_manager.current_conversation_id else ""
                
                # 思考模式标记
                mode_mark = "💭" if conv["thinking_mode"] else "⚡"
                
                print(f"{i:2d}. {status_icon} {conv['id'][:16]}...{current_mark}")
                print(f"    {mode_mark} {conv['title'][:50]}{'...' if len(conv['title']) > 50 else ''}")
                print(f"    📅 {conv['updated_at'][:19]} | 💬 {conv['total_messages']} 条消息 | 🔧 {conv['total_tools']} 个工具")
                print(f"    📁 {conv['project_path']}")
                print()
            
            print(f"总计: {conversations['total']} 个对话")
            if conversations["has_more"]:
                print(f"使用 /conversations {limit + 10} 查看更多")
            
        except Exception as e:
            print(f"{OUTPUT_FORMATS['error']} 获取对话列表失败: {e}")
    
    async def load_conversation_command(self, args: str):
        """加载指定对话"""
        if not args:
            print(f"{OUTPUT_FORMATS['error']} 请指定对话ID")
            print("使用方法: /load <对话ID>")
            await self.show_conversations("5")  # 显示最近5个对话作为提示
            return
        
        conversation_id = args.strip()
        
        try:
            success = self.context_manager.load_conversation_by_id(conversation_id)
            if success:
                print(f"{OUTPUT_FORMATS['success']} 对话已加载: {conversation_id}")
                print(f"{OUTPUT_FORMATS['info']} 消息数量: {len(self.context_manager.conversation_history)}")
                
                # 如果是思考模式，重置状态（下次任务会重新思考）
                if self.thinking_mode:
                    self.api_client.start_new_task(force_deep=self.deep_thinking_mode)
                
                self.current_session_id += 1
                
            else:
                print(f"{OUTPUT_FORMATS['error']} 对话加载失败")
                
        except Exception as e:
            print(f"{OUTPUT_FORMATS['error']} 加载对话异常: {e}")
    
    async def new_conversation_command(self, args: str = ""):
        """创建新对话"""
        try:
            conversation_id = self.context_manager.start_new_conversation(
                project_path=self.project_path,
                thinking_mode=self.thinking_mode
            )
            
            print(f"{OUTPUT_FORMATS['success']} 已创建新对话: {conversation_id}")
            
            # 重置相关状态
            if self.thinking_mode:
                self.api_client.start_new_task(force_deep=self.deep_thinking_mode)
            
            self.current_session_id += 1
            
        except Exception as e:
            print(f"{OUTPUT_FORMATS['error']} 创建新对话失败: {e}")
    
    async def save_conversation_command(self, args: str = ""):
        """手动保存当前对话"""
        try:
            success = self.context_manager.save_current_conversation()
            if success:
                print(f"{OUTPUT_FORMATS['success']} 对话已保存")
            else:
                print(f"{OUTPUT_FORMATS['error']} 对话保存失败")
        except Exception as e:
            print(f"{OUTPUT_FORMATS['error']} 保存对话异常: {e}")
    
    # ===== 修改现有命令，集成对话管理 =====
    
    async def clear_conversation(self, args: str = ""):
        """清除对话记录（修改版：创建新对话而不是清空）"""
        if input("确认创建新对话? 当前对话将被保存 (y/n): ").lower() == 'y':
            try:
                # 保存当前对话
                if self.context_manager.current_conversation_id:
                    self.context_manager.save_current_conversation()
                
                # 创建新对话
                await self.new_conversation_command()
                
                print(f"{OUTPUT_FORMATS['success']} 已开始新对话")
                
            except Exception as e:
                print(f"{OUTPUT_FORMATS['error']} 创建新对话失败: {e}")
    
    async def show_status(self, args: str = ""):
        """显示系统状态"""
        # 上下文状态
        context_status = self.context_manager.check_context_size()
        
        # 记忆状态
        memory_stats = self.memory_manager.get_memory_stats()
        
        # 文件结构
        structure = self.context_manager.get_project_structure()
        
        # 聚焦文件状态
        focused_size = sum(len(content) for content in self.focused_files.values())
        
        # 终端会话状态
        terminal_status = self.terminal_manager.list_terminals()
        
        # 思考模式状态
        thinking_status = self.get_run_mode_label()
        if self.thinking_mode:
            thinking_status += f" ({'等待新任务' if self.api_client.current_task_first_call else '任务进行中'})"
        
        # 新增：对话统计
        conversation_stats = self.context_manager.get_conversation_statistics()
        
        status_text = f"""
📊 系统状态:
  项目路径: {self.project_path}
  运行模式: {thinking_status}
  当前对话: {self.context_manager.current_conversation_id or '无'}
  
  上下文使用: {context_status['usage_percent']:.1f}%
  当前消息: {len(self.context_manager.conversation_history)} 条
  聚焦文件: {len(self.focused_files)}/3 个 ({focused_size/1024:.1f}KB)
  终端会话: {terminal_status['total']}/{terminal_status['max_allowed']} 个
  当前会话ID: {self.current_session_id}
  
  项目文件: {structure['total_files']} 个
  项目大小: {structure['total_size'] / 1024 / 1024:.2f} MB
  
  对话总数: {conversation_stats.get('total_conversations', 0)} 个
  历史消息: {conversation_stats.get('total_messages', 0)} 条
  工具调用: {conversation_stats.get('total_tools', 0)} 次
  
  主记忆: {memory_stats['main_memory']['lines']} 行
  任务记忆: {memory_stats['task_memory']['lines']} 行
"""
        container_report = self._container_status_report()
        if container_report:
            status_text += container_report
        print(status_text)

    def _container_status_report(self) -> str:
        session = getattr(self, "container_session", None)
        if not session or session.mode != "docker":
            return ""
        stats = collect_stats(session.container_name, session.sandbox_bin)
        state = inspect_state(session.container_name, session.sandbox_bin)
        lines = [f"  容器: {session.container_name or '未知'}"]
        if stats:
            cpu = stats.get("cpu_percent")
            mem = stats.get("memory", {})
            net = stats.get("net_io", {})
            block = stats.get("block_io", {})
            lines.append(f"    CPU: {cpu:.2f}%" if cpu is not None else "    CPU: 未知")
            if mem:
                used = mem.get("used_bytes")
                limit = mem.get("limit_bytes")
                percent = mem.get("percent")
                mem_line = "    内存: "
                if used is not None:
                    mem_line += f"{used / (1024 * 1024):.2f}MB"
                if limit:
                    mem_line += f" / {limit / (1024 * 1024):.2f}MB"
                if percent is not None:
                    mem_line += f" ({percent:.2f}%)"
                lines.append(mem_line)
            if net:
                rx = net.get("rx_bytes") or 0
                tx = net.get("tx_bytes") or 0
                lines.append(f"    网络: ↓{rx/1024:.1f}KB ↑{tx/1024:.1f}KB")
            if block:
                read = block.get("read_bytes") or 0
                write = block.get("write_bytes") or 0
                lines.append(f"    磁盘: 读 {read/1024:.1f}KB / 写 {write/1024:.1f}KB")
        else:
            lines.append("    指标: 暂无")
        if state:
            lines.append(f"    状态: {state.get('status')}")
        return "\n".join(lines) + "\n"
    
    async def save_state(self):
        """保存状态"""
        try:
            # 保存对话历史（使用新的持久化系统）
            self.context_manager.save_current_conversation()
            
            # 保存文件备注
            self.context_manager.save_annotations()
            
            print(f"{OUTPUT_FORMATS['success']} 状态已保存")
        except Exception as e:
            print(f"{OUTPUT_FORMATS['error']} 状态保存失败: {e}")
    
    async def show_help(self, args: str = ""):
        """显示帮助信息"""
        # 根据当前模式显示不同的帮助信息
        mode_info = ""
        if self.thinking_mode:
            mode_info = "\n💡 思考模式:\n  - 每个新任务首次调用深度思考\n  - 同一任务后续调用快速响应\n  - 每个新任务都会重新思考"
        else:
            mode_info = "\n⚡ 快速模式:\n  - 不进行思考，直接响应\n  - 适合简单任务和快速交互"
        
        help_text = f"""
📚 可用命令:
  /help         - 显示此帮助信息
  /exit         - 退出系统
  /status       - 显示系统状态
  /memory       - 管理记忆
  /clear        - 创建新对话
  /history      - 显示对话历史
  /files        - 显示项目文件
  /focused      - 显示聚焦文件
  /terminals    - 显示终端会话
  /mode         - 切换运行模式
  
🗂️ 对话管理:
  /conversations [数量]  - 显示对话列表
  /load <对话ID>        - 加载指定对话
  /new                  - 创建新对话
  /save                 - 手动保存当前对话
  
💡 使用提示:
  - 直接输入任务描述，系统会自动判断是否需要执行
  - 使用 Ctrl+C 可以中断当前操作
  - 重要操作会要求确认
  - 所有对话都会自动保存，不用担心丢失
  
🔍 文件聚焦功能:
  - 系统可以聚焦最多3个文件，实现"边看边改"
  - 聚焦的文件内容会持续显示在上下文中
  - 适合需要频繁查看和修改的文件
  
📺 持久化终端:
  - 可以打开最多3个终端会话
  - 终端保持运行状态，支持交互式程序
  - 使用 terminal_session 和 terminal_input 工具控制{mode_info}
"""
        print(help_text)
    
    # ===== 保持原有的其他方法不变，只需要小修改 =====
    
    def _inject_intent(self, properties: Dict[str, Any]) -> Dict[str, Any]:
        """在工具参数中注入 intent（简短意图说明），仅当开关启用时。

        字段含义：要求模型用不超过15个中文字符对即将执行的动作做简要说明，供前端展示。
        """
        if not self.tool_intent_enabled:
            return properties
        if not isinstance(properties, dict):
            return properties
        intent_field = {
            "intent": {
                "type": "string",
                "description": "用不超过15个字向用户说明你要做什么，例如：等待下载完成/创建日志文件"
            }
        }
        # 将 intent 放在最前面以提高模型关注度
        return {**intent_field, **properties}

    def _apply_intent_to_tools(self, tools: List[Dict]) -> List[Dict]:
        """遍历工具列表，为缺少 intent 的工具补充字段（开关启用时生效）。"""
        if not self.tool_intent_enabled:
            return tools
        intent_field = {
            "intent": {
                "type": "string",
                "description": "用不超过15个字向用户说明你要做什么，例如：等待下载完成/创建日志文件/搜索最新新闻"
            }
        }
        for tool in tools:
            func = tool.get("function") or {}
            params = func.get("parameters") or {}
            if not isinstance(params, dict):
                continue
            if params.get("type") != "object":
                continue
            props = params.get("properties")
            if not isinstance(props, dict):
                continue
            # 补充 intent 属性
            if "intent" not in props:
                params["properties"] = {**intent_field, **props}
            # 将 intent 加入必填
            required_list = params.get("required")
            if isinstance(required_list, list):
                if "intent" not in required_list:
                    required_list.insert(0, "intent")
                    params["required"] = required_list
            else:
                params["required"] = ["intent"]
        return tools

    def define_tools(self) -> List[Dict]:
        """定义可用工具（添加确认工具）"""
        current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")

        tools = [
                {
                "type": "function",
                "function": {
                    "name": "sleep",
                    "description": "等待指定的秒数。用于等待长时间操作完成，如安装包、编译、服务启动等。当终端或进程需要时间完成操作时使用。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "seconds": {
                                "type": "number",
                                "description": "等待的秒数，可以是小数（如2.5秒）。建议范围：0.5-30秒"
                            },
                            "reason": {
                                "type": "string",
                                "description": "等待的原因说明（可选）"
                            }
                        }),
                        "required": ["seconds"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "create_file",
                    "description": "创建新文件（仅创建空文件，正文请使用 write_file_diff 提交补丁）",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "path": {"type": "string", "description": "文件路径"},
                            "file_type": {"type": "string", "enum": ["txt", "py", "md"], "description": "文件类型"},
                            "annotation": {"type": "string", "description": "文件备注"}
                        }),
                        "required": ["path", "file_type", "annotation"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "read_file",
                    "description": "读取/搜索/抽取 UTF-8 文本文件内容。通过 type 参数选择 read（阅读）、search（搜索）、extract（具体行段），支持限制返回字符数。若文件非 UTF-8 或过大，请改用 run_python。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "path": {"type": "string", "description": "文件路径"},
                            "type": {
                                "type": "string",
                                "enum": ["read", "search", "extract"],
                                "description": "读取模式：read=阅读、search=搜索、extract=按行抽取"
                            },
                            "max_chars": {
                                "type": "integer",
                                "description": "返回内容的最大字符数，默认与 config 一致"
                            },
                            "start_line": {
                                "type": "integer",
                                "description": "[read] 可选的起始行号（1开始）"
                            },
                            "end_line": {
                                "type": "integer",
                                "description": "[read] 可选的结束行号（>=start_line）"
                            },
                            "query": {
                                "type": "string",
                                "description": "[search] 搜索关键词"
                            },
                            "max_matches": {
                                "type": "integer",
                                "description": "[search] 最多返回多少条命中（默认5，最大50）"
                            },
                            "context_before": {
                                "type": "integer",
                                "description": "[search] 命中行向上追加的行数（默认1，最大3）"
                            },
                            "context_after": {
                                "type": "integer",
                                "description": "[search] 命中行向下追加的行数（默认1，最大5）"
                            },
                            "case_sensitive": {
                                "type": "boolean",
                                "description": "[search] 是否区分大小写，默认 false"
                            },
                            "segments": {
                                "type": "array",
                                "description": "[extract] 需要抽取的行区间",
                                "items": {
                                    "type": "object",
                                    "properties": {
                                        "label": {
                                            "type": "string",
                                            "description": "该片段的标签（可选）"
                                        },
                                        "start_line": {
                                            "type": "integer",
                                            "description": "起始行号（>=1）"
                                        },
                                        "end_line": {
                                            "type": "integer",
                                            "description": "结束行号（>=start_line）"
                                        }
                                    },
                                    "required": ["start_line", "end_line"]
                                },
                                "minItems": 1
                            }
                        }),
                        "required": ["path", "type"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "vlm_analyze",
                    "description": "使用大参数视觉语言模型（Qwen-VL模型）理解图片：文字、物体、布局、表格等，仅支持本地路径。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "path": {"type": "string", "description": "项目内的图片相对路径"},
                            "prompt": {"type": "string", "description": "传递给 VLM 的中文提示词，如“请总结这张图的内容”“表格的总金额是多少”“图中是什么车？”。"}
                        }),
                        "required": ["path", "prompt"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "delete_file",
                    "description": "删除文件",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "path": {"type": "string", "description": "文件路径"}
                        }),
                        "required": ["path"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "rename_file",
                    "description": "重命名文件",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "old_path": {"type": "string", "description": "原文件路径"},
                            "new_path": {"type": "string", "description": "新文件路径"}
                        }),
                        "required": ["old_path", "new_path"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "write_file_diff",
                    "description": "使用统一 diff（`@@` 块、`-`/`+`/空格行）对单个文件做精确编辑：追加、插入、替换、删除都可以在一次调用里完成。\\n硬性规则：\\n\\n1) 补丁必须被 `*** Begin Patch` 与 `*** End Patch` 包裹。\\n2) 每个修改块必须以 `@@ [id:数字]` 开头。\\n3) 块内每一行只能是三类之一：\\n   - 上下文行：以空格开头（` ␠`），表示“文件里必须原样存在”的锚点；\\n   - 删除行：以 `-` 开头，表示要从文件中移除的原文；\\n   - 新增行：以 `+` 开头，表示要写入的新内容。\\n4) 任何“想新增/想删除/想替换”的内容都必须逐行写 `+` 或 `-`；空行也必须写成单独一行的 `+`（这一行只有 `+` 和换行）；如果你把多行新内容直接贴上去却不加 `+`，它会被当成上下文锚点去匹配原文件，极易导致“未找到匹配的原文”。\\n5) 重要语义：一个块里如果完全没有上下文行（空格开头）也没有删除行（`-`），那么它会被视为“仅追加（append-only）”，也就是把所有 `+` 行追加到文件末尾——这对“给空文件写正文”很合适，但对“插入到中间”是错误的。\\n\\n正面案例（至少 5 个，且都包含多行原文/多处修改）\\n\\n1) 给空文件写完整正文（追加到末尾；空文件=正确）\\n目标：新建 README.md 后一次性写入标题、安装、用法、FAQ（多段落、多行）。\\n要点：没有上下文/删除行 → 追加模式；空文件时最常用。\\n\\n*** Begin Patch\\n@@ [id:1]\\n+# 项目名称\\n+\\n+一个简短说明：这个项目用于……\\n+\\n+## 安装\\n+\\n+```bash\\n+pip install -r requirements.txt\\n+```\\n+\\n+## 快速开始\\n+\\n+```bash\\n+python main.py\\n+```\\n+\\n+## 常见问题\\n+\\n+- Q: 为什么会报 xxx？\\n+  A: 先检查 yyy，再确认 zzz。\\n+\\n*** End Patch\\n\\n2) “不删除，直接插入内容”到函数内部（必须用上下文锚定插入位置）\\n目标：在 def build_prompt(...): 里插入日志与参数归一化，但不改动其它行。\\n要点：插入发生在“两个上下文行之间”，上下文必须精确（包含缩进）。\\n\\n*** Begin Patch\\n@@ [id:1]\\n def build_prompt(user_text: str, system_text: str, tags: list):\\n     prompt_parts = []\\n+    # 参数归一化：去掉首尾空白，避免模型误判\\n+    user_text = (user_text or \\\"\\\").strip()\\n+    system_text = (system_text or \\\"\\\").strip()\\n+\\n+    logger.debug(\\\"build_prompt: tags=%s, user_len=%d\\\", tags, len(user_text))\\n     prompt_parts.append(system_text)\\n     prompt_parts.append(user_text)\\n     if tags:\\n         prompt_parts.append(\\\"TAGS: \\\" + \\\",\\\".join(tags))\\n*** End Patch\\n\\n3) 复杂替换：整段函数重构（多行 old/new + 保留稳定上下文）\\n目标：把旧的 apply_patch()（弱校验）替换成新实现（多分支、异常信息更清晰）。\\n要点：替换不是“改一行”，而是“删一段、加一段”，并用函数签名/相邻代码作锚点。\\n\\n*** Begin Patch\\n@@ [id:1]\\n class FilePatcher:\\n     def __init__(self, root: Path):\\n         self.root = root\\n\\n     def apply_patch(self, path: str, patch_text: str) -> dict:\\n-        # old: naive replace\\n-        content = (self.root / path).read_text(encoding=\\\"utf-8\\\")\\n-        content = content.replace(\\\"foo\\\", \\\"bar\\\")\\n-        (self.root / path).write_text(content, encoding=\\\"utf-8\\\")\\n-        return {\\\"success\\\": True}\\n+        full_path = (self.root / path).resolve()\\n+        if self.root not in full_path.parents and full_path != self.root:\\n+            return {\\\"success\\\": False, \\\"error\\\": \\\"非法路径：越界访问\\\"}\\n+\\n+        if \\\"*** Begin Patch\\\" not in patch_text or \\\"*** End Patch\\\" not in patch_text:\\n+            return {\\\"success\\\": False, \\\"error\\\": \\\"补丁格式错误：缺少 Begin/End 标记\\\"}\\n+\\n+        try:\\n+            original = full_path.read_text(encoding=\\\"utf-8\\\")\\n+        except Exception as e:\\n+            return {\\\"success\\\": False, \\\"error\\\": f\\\"读取失败: {e}\\\"}\\n+\\n+        # 这里省略：解析 blocks、逐块应用、失败回滚等\\n+        updated = original\\n+        try:\\n+            full_path.write_text(updated, encoding=\\\"utf-8\\\")\\n+        except Exception as e:\\n+            return {\\\"success\\\": False, \\\"error\\\": f\\\"写入失败: {e}\\\"}\\n+\\n+        return {\\\"success\\\": True, \\\"message\\\": \\\"已应用补丁\\\"}\\n*** End Patch\\n\\n4) 复杂多块：同一文件里同时“加 import + 替换逻辑 + 插入新 helper + 删除旧函数”\\n目标：一次调用完成 4 种操作，且每块都有足够上下文，避免误匹配。\\n要点：不同区域用不同 @@ [id:n] 分块，互不干扰。\\n\\n*** Begin Patch\\n@@ [id:1]\\n-import json\\n+import json\\n+import re\\n from pathlib import Path\\n\\n@@ [id:2]\\n def normalize_user_input(text: str) -> str:\\n-    return text\\n+    text = (text or \\\"\\\").strip()\\n+    # 压缩多余空白，减少提示词抖动\\n+    text = re.sub(r\\\"\\\\\\\\s+\\\", \\\" \\\", text)\\n+    return text\\n\\n@@ [id:3]\\n def load_config(path: str) -> dict:\\n     cfg_path = Path(path)\\n     if not cfg_path.exists():\\n         return {}\\n     data = cfg_path.read_text(encoding=\\\"utf-8\\\")\\n     return json.loads(data)\\n+\\n+def safe_get(cfg: dict, key: str, default=None):\\n+    if not isinstance(cfg, dict):\\n+        return default\\n+    return cfg.get(key, default)\\n\\n@@ [id:4]\\n-def legacy_parse_flags(argv):\\n-    # deprecated, kept for compatibility\\n-    flags = {}\\n-    for item in argv:\\n-        if item.startswith(\\\"--\\\"):\\n-            k, _, v = item[2:].partition(\\\"=\\\")\\n-            flags[k] = v or True\\n-    return flags\\n-\\n def main():\\n     cfg = load_config(\\\"config.json\\\")\\n     # ...\\n*** End Patch\\n\\n5) 删除示例：删除一整段“废弃配置块”，并顺手修正周围空行（多行删除 + 上下文）\\n目标：删掉 DEPRECATED_* 配置和旧注释，确保删除位置精确。\\n要点：删除行必须逐行 `-`；保留上下文行确保定位。\\n\\n*** Begin Patch\\n@@ [id:1]\\n # ==============================\\n # Runtime Config\\n # ==============================\\n-DEPRECATED_TIMEOUT = 5\\n-DEPRECATED_RETRIES = 1\\n-# 注意：这些字段将在下个版本移除\\n-# 请迁移到 NEW_TIMEOUT / NEW_RETRIES\\n NEW_TIMEOUT = 30\\n NEW_RETRIES = 3\\n*** End Patch\\n\\n如何写“带上下文”的正确姿势（要点）\\n\\n- 上下文要选“稳定锚点”：函数签名、类名、关键注释、紧邻的两三行缩进代码。\\n- 不要用“容易变的行”当唯一锚点：时间戳、日志序号、随机 id、生成内容片段。\\n- 上下文必须字节级一致（空格/Tab/大小写/标点都算），否则会匹配失败。\\n\\n反面案例（至少 3 个，且都是“真实会踩坑”的类型）\\n\\n反例 A（来自一次常见错误）：空文件时只有第一行加了 `+`，后面直接贴正文\\n这会让后面的正文变成“上下文锚点”，工具会去空文件里找这些原文，必然失败（常见报错：未找到匹配的原文）。\\n\\n*** Begin Patch\\n@@ [id:1]\\n+\\n仰望U9X·电驭苍穹\\n银箭破空电光闪\\n三千马力云中藏\\n*** End Patch\\n\\n正确做法：正文每一行都要写 `+`（包括空行也写 `+`），空行写法是一行单独的 `+`。\\n\\n（反例：空行没加 `+`，会被当成上下文，空文件/定位修改时容易失败）\\n\\n*** Begin Patch\\n@@ [id:1]\\n+title = \\\"示例\\\"\\n\\n+[db]\\n+enabled = true\\n*** End Patch\\n\\n（正确：空行也要用 `+` 表示）\\n\\n*** Begin Patch\\n@@ [id:1]\\n+title = \\\"示例\\\"\\n+\\n+[db]\\n+enabled = true\\n*** End Patch\\n\\n（对应的正确 patch 示例：向空文件追加多行）\\n\\n*** Begin Patch\\n@@ [id:1]\\n+\\n+仰望U9X·电驭苍穹\\n+银箭破空电光闪\\n+三千马力云中藏\\n*** End Patch\\n\\n反例 B：想“插入到中间”，却只写 `+`（没有任何上下文/删除行）\\n这种块会被当成“追加到文件末尾”，结果内容跑到文件最后，不会插入到你以为的位置。\\n\\n*** Begin Patch\\n@@ [id:1]\\n+# 我以为会插到某个函数上面\\n+print(\\\"hello\\\")\\n*** End Patch\\n\\n正确做法：用上下文锚定插入点（见正面案例 2）。\\n\\n（对应的正确 patch 示例：用上下文把内容插入到函数内部，而不是追加到文件末尾）\\n\\n*** Begin Patch\\n@@ [id:1]\\n def main():\\n     config = load_config(\\\"config.json\\\")\\n+    # 这里插入：启动提示（不会移动到文件末尾）\\n+    print(\\\"hello\\\")\\n     run(config)\\n*** End Patch\\n\\n反例 C：补丁在第一个 `@@` 之前出现内容 / 或漏掉 Begin/End 标记\\n解析会直接报格式错误（例如：“在检测到第一个 @@ 块之前出现内容”、“缺少 Begin/End 标记”）。\\n\\n（错误形态示意）\\n这里先写了一段说明文字（没有 @@）\\n@@ [id:1]\\n+...\\n\\n正确做法：确保第一段非空内容必须从 `@@ [id:n]` 开始，并且整体有 Begin/End。\\n\\n（对应的正确 patch 示例：完整结构、第一段内容从 @@ 块开始）\\n\\n*** Begin Patch\\n@@ [id:1]\\n # ==============================\\n # Runtime Config\\n # ==============================\\n+# 说明：此处新增一行注释作为示例\\n NEW_TIMEOUT = 30\\n*** End Patch\\n",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "path": {"type": "string", "description": "目标文件路径（相对项目根目录）。"},
                            "patch": {
                                "type": "string",
                                "description": "完整补丁文本，格式类似 unified diff，必须用 *** Begin Patch / *** End Patch 包裹，并用 @@ [id:数字] 划分多个修改块。示例：*** Begin Patch\\n@@ [id:1]\\n def main():\\n-    def greet(self):\\n-        return \"hi\"\\n+    def greet(self, name: str) -> str:\\n+        message = f\"Hello, {name}!\"\\n+        return message\\n@@ [id:2]\\n+\\n+if __name__ == \"__main__\":\\n+    print(\"hello world\")\\n*** End Patch"
                            }
                        }),
                        "required": ["path", "patch"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "create_folder",
                    "description": "创建文件夹",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "path": {"type": "string", "description": "文件夹路径"}
                        }),
                        "required": ["path"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "focus_file",
                    "description": "聚焦 UTF-8 文本文件，将完整内容持续注入上下文。适合频繁查看/修改的核心文件；超过字符限制或非 UTF-8 时会拒绝。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "path": {"type": "string", "description": "文件路径"}
                        }),
                        "required": ["path"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "unfocus_file",
                    "description": "取消聚焦文件，从上下文中移除",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "path": {"type": "string", "description": "文件路径"}
                        }),
                        "required": ["path"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "terminal_session",
                    "description": "管理持久化终端会话，可打开、关闭、列出或切换终端。请在授权工作区内执行命令，禁止启动需要完整 TTY 的程序（python REPL、vim、top 等）。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "action": {
                                "type": "string", 
                                "enum": ["open", "close", "list", "switch"],
                                "description": "操作类型：open-打开新终端，close-关闭终端，list-列出所有终端，switch-切换活动终端"
                            },
                            "session_name": {
                                "type": "string",
                                "description": "终端会话名称（open、close、switch时需要）"
                            },
                            "working_dir": {
                                "type": "string",
                                "description": "工作目录，相对于项目路径（open时可选）"
                            }
                        }),
                        "required": ["action"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "terminal_input",
                    "description": "向活动终端发送命令或输入。禁止启动会占用终端界面的程序（python/node/nano/vim 等）；如遇卡死请结合 terminal_snapshot 并使用 terminal_reset 恢复。必须提供 timeout，超时仅终止当前命令，终端保持可用。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "command": {
                                "type": "string",
                                "description": "要执行的命令或发送的输入"
                            },
                            "session_name": {
                                "type": "string",
                                "description": "目标终端会话名称（可选，默认使用活动终端）"
                            },
                            "timeout": {
                                "type": "number",
                                "description": "等待输出的最长秒数，必填，最大300"
                            }
                        }),
                        "required": ["command", "timeout"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "terminal_snapshot",
                    "description": "获取指定终端最近的输出快照，用于判断当前状态。默认返回末尾的50行，可通过参数调整。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "session_name": {
                                "type": "string",
                                "description": "目标终端会话名称（可选，默认活动终端）"
                            },
                            "lines": {
                                "type": "integer",
                                "description": "返回的最大行数（可选）"
                            },
                            "max_chars": {
                                "type": "integer",
                                "description": "返回的最大字符数（可选）"
                            }
                        })
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "terminal_reset",
                    "description": "重置指定终端：关闭当前进程并重新创建同名会话，用于从卡死或非法状态中恢复。请在总结中说明重置原因。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "session_name": {
                                "type": "string",
                                "description": "目标终端会话名称（可选，默认活动终端）"
                            }
                        })
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "web_search",
                    "description": f"当现有资料不足时搜索外部信息（当前时间 {current_time}）。调用前说明目的，精准撰写 query，并合理设置时间/主题参数；避免重复或无意义的搜索。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "query": {
                                "type": "string",
                                "description": "搜索查询内容（不要包含日期或时间范围）"
                            },
                            "max_results": {
                                "type": "integer",
                                "description": "最大结果数，可选"
                            },
                            "topic": {
                                "type": "string",
                                "description": "搜索主题，可选值：general（默认）/news/finance"
                            },
                            "time_range": {
                                "type": "string",
                                "description": "相对时间范围，可选 day/week/month/year，支持缩写 d/w/m/y；与 days 和 start_date/end_date 互斥"
                            },
                            "days": {
                                "type": "integer",
                                "description": "最近 N 天，仅当 topic=news 时可用；与 time_range、start_date/end_date 互斥"
                            },
                            "start_date": {
                                "type": "string",
                                "description": "开始日期，YYYY-MM-DD；必须与 end_date 同时提供，与 time_range、days 互斥"
                            },
                            "end_date": {
                                "type": "string",
                                "description": "结束日期，YYYY-MM-DD；必须与 start_date 同时提供，与 time_range、days 互斥"
                            },
                            "country": {
                                "type": "string",
                                "description": "国家过滤，仅 topic=general 可用，使用英文小写国名"
                            }
                        }),
                        "required": ["query"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "extract_webpage",
                    "description": "在 web_search 结果不够详细时提取网页正文。调用前说明用途，注意提取内容会消耗大量 token，超过80000字符将被拒绝。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "url": {"type": "string", "description": "要提取内容的网页URL"}
                        }),
                        "required": ["url"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "save_webpage",
                    "description": "提取网页内容并保存为纯文本文件，适合需要长期留存的长文档。请提供网址与目标路径（含 .txt 后缀），落地后请通过终端命令查看。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "url": {"type": "string", "description": "要保存的网页URL"},
                            "target_path": {"type": "string", "description": "保存位置，包含文件名，相对于项目根目录"}
                        }),
                        "required": ["url", "target_path"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "run_python",
                    "description": "执行一次性 Python 脚本，可用于处理二进制或非 UTF-8 文件（如 Excel、Word、PDF、图片），或进行数据分析与验证。必须提供 timeout（最长60秒）；超时会尝试中断并返回已捕获输出。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "code": {"type": "string", "description": "Python代码"},
                            "timeout": {
                                "type": "number",
                                "description": "超时时长（秒），必填，最大60"
                            }
                        }),
                        "required": ["code", "timeout"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "run_command",
                    "description": "执行一次性终端命令，适合查看文件信息（file/ls/stat/iconv 等）、转换编码或调用 CLI 工具。禁止启动交互式程序；对已聚焦文件仅允许使用 grep -n 等定位命令。必须提供 timeout（最长30秒），超时会尝试中断并返回已捕获输出；输出超过10000字符将被截断或拒绝。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "command": {"type": "string", "description": "终端命令"},
                            "timeout": {
                                "type": "number",
                                "description": "超时时长（秒），必填，最大30"
                            }
                        }),
                        "required": ["command", "timeout"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "update_memory",
                    "description": "按条目更新记忆列表（自动编号）。append 追加新条目；replace 用序号替换；delete 用序号删除。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "memory_type": {"type": "string", "enum": ["main", "task"], "description": "记忆类型"},
                            "content": {"type": "string", "description": "条目内容。append/replace 时必填"},
                            "operation": {"type": "string", "enum": ["append", "replace", "delete"], "description": "操作类型"},
                            "index": {"type": "integer", "description": "要替换/删除的序号（从1开始）"}
                        }),
                        "required": ["memory_type", "operation"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "todo_create",
                    "description": "创建待办列表，将多步骤任务拆解为最多 8 条可执行项。概述请控制在 50 字以内，直接说明清单目标；任务列表只写 2~4 条明确步骤。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "overview": {"type": "string", "description": "一句话概述待办清单要完成的目标，50 字以内。"},
                            "tasks": {
                                "type": "array",
                                "description": "任务列表，建议 2~4 条，每条写清“动词+对象+目标”。",
                                "items": {
                                    "type": "object",
                                    "properties": {
                                        "title": {"type": "string", "description": "单个任务描述，写成可执行的步骤"}
                                    },
                                    "required": ["title"]
                                },
                                "minItems": 1,
                                "maxItems": 8
                            }
                        }),
                        "required": ["overview", "tasks"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "todo_update_task",
                    "description": "勾选或取消指定任务。在调整任务顺序或内容前，请先向用户说明最新理解或变更。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "task_index": {"type": "integer", "description": "任务序号（1-8）"},
                            "completed": {"type": "boolean", "description": "true=打勾，false=取消"}
                        }),
                        "required": ["task_index", "completed"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "todo_finish",
                    "description": "尝试结束待办列表，需同步汇报每项任务结果。若仍有未完事项，请注明原因与后续建议。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "reason": {"type": "string", "description": "可选说明"}
                        })
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "todo_finish_confirm",
                    "description": "在任务未完成时确认是否提前结束。若确认结束，请说明后续交付建议或遗留风险。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "confirm": {"type": "boolean", "description": "true=确认结束，false=继续执行"},
                            "reason": {"type": "string", "description": "确认结束时的说明"}
                        }),
                        "required": ["confirm"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "close_sub_agent",
                    "description": "强制关闭指定子智能体，适用于长时间无响应、超时或卡死的任务。使用前请确认必要的日志/文件已保留，操作会立即终止该任务。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "task_id": {"type": "string", "description": "子智能体任务ID"},
                            "agent_id": {"type": "integer", "description": "子智能体编号（1~5），若缺少 task_id 可用"}
                        })
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "create_sub_agent",
                    "description": "创建新的子智能体任务。适合大规模信息搜集、网页提取与多文档总结等会占用大量上下文的工作，需要提供任务摘要、详细要求、交付目录以及参考文件。注意：同一时间最多运行5个子智能体。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "agent_id": {"type": "integer", "description": "子智能体代号（1~5）"},
                            "summary": {"type": "string", "description": "任务摘要，简要说明目标"},
                            "task": {"type": "string", "description": "任务详细要求"},
                            "target_dir": {"type": "string", "description": "项目下用于接收交付的相对目录"},
                            "reference_files": {
                                "type": "array",
                                "description": "提供给子智能体的参考文件列表（相对路径），禁止在summary和task中直接告知子智能体引用图片的路径，必须使用本参数提供",
                                "items": {"type": "string"},
                                "maxItems": 10
                            },
                            "timeout_seconds": {"type": "integer", "description": "子智能体最大运行秒数：单/双次搜索建议180秒，多轮搜索整理建议300秒，深度调研或长篇分析可设600秒"}
                        }),
                        "required": ["agent_id", "summary", "task", "target_dir"]
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "wait_sub_agent",
                    "description": "等待指定子智能体任务结束（或超时）。任务完成后会返回交付目录，并将结果复制到指定的项目文件夹。调用时 `timeout_seconds` 应不少于对应子智能体的 `timeout_seconds`，否则可能提前终止等待。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "task_id": {"type": "string", "description": "子智能体任务ID"},
                            "agent_id": {"type": "integer", "description": "子智能体代号（可选，用于缺省 task_id 的情况）"},
                            "timeout_seconds": {"type": "integer", "description": "本次等待的超时时长（秒）"}
                        }),
                        "required": []
                    }
                }
            },
            {
                "type": "function",
                "function": {
                    "name": "trigger_easter_egg",
                    "description": "触发隐藏彩蛋，用于展示非功能性特效。需指定 effect 参数，例如 flood（灌水）或 snake（贪吃蛇）。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "effect": {
                                "type": "string",
                                "description": "彩蛋标识，目前支持 flood（灌水）与 snake（贪吃蛇）。"
                            }
                        }),
                        "required": ["effect"]
                    }
                }
            }
        ]
        # Qwen-VL 自带多模态能力，不向其暴露额外的 vlm_analyze 工具，避免重复与误导
        if getattr(self, "model_key", None) == "qwen3-vl-plus":
            tools = [
                tool for tool in tools
                if (tool.get("function") or {}).get("name") != "vlm_analyze"
            ]
            tools.append({
                "type": "function",
                "function": {
                    "name": "view_image",
                    "description": "将指定本地图片插入到对话中（系统代发一条包含图片的消息），便于模型主动查看图片内容。",
                    "parameters": {
                        "type": "object",
                        "properties": self._inject_intent({
                            "path": {
                                "type": "string",
                                "description": "项目内的图片相对路径（不要以 /workspace 开头），支持 png/jpg/webp/gif/bmp/svg。"
                            }
                        }),
                        "required": ["path"]
                    }
                }
            })
        if self.disabled_tools:
            tools = [
                tool for tool in tools
                if tool.get("function", {}).get("name") not in self.disabled_tools
            ]
        return self._apply_intent_to_tools(tools)

    async def handle_tool_call(self, tool_name: str, arguments: Dict) -> str:
        """处理工具调用（添加参数预检查和改进错误处理）"""
        # 导入字符限制配置
        from config import (
            MAX_READ_FILE_CHARS, MAX_FOCUS_FILE_CHARS, 
            MAX_RUN_COMMAND_CHARS, MAX_EXTRACT_WEBPAGE_CHARS
        )
        
        # 检查是否需要确认
        if tool_name in NEED_CONFIRMATION:
            if not await self.confirm_action(tool_name, arguments):
                return json.dumps({"success": False, "error": "用户取消操作"})
        
        # === 新增：预检查参数大小和格式 ===
        try:
            # 检查参数总大小
            arguments_str = json.dumps(arguments, ensure_ascii=False)
            if len(arguments_str) > 50000:  # 50KB限制
                return json.dumps({
                    "success": False,
                    "error": f"参数过大({len(arguments_str)}字符)，超过50KB限制",
                    "suggestion": "请分块处理或减少参数内容"
                }, ensure_ascii=False)
            
            # 针对特定工具的内容检查
            if tool_name == "create_file" and "content" in arguments:
                content = arguments.get("content", "")
                if not DISABLE_LENGTH_CHECK and len(content) > 9999999999:  # 30KB内容限制
                    return json.dumps({
                        "success": False,
                        "error": f"文件内容过长({len(content)}字符)，建议分块处理",
                        "suggestion": "请拆分内容或使用 write_file_diff 工具输出结构化补丁"
                    }, ensure_ascii=False)
                
                # 检查内容中的特殊字符
                if '\\' in content and content.count('\\') > len(content) / 10:
                    print(f"{OUTPUT_FORMATS['warning']} 检测到大量转义字符，可能存在格式问题")
                
        except Exception as e:
            return json.dumps({
                "success": False,
                "error": f"参数预检查失败: {str(e)}"
            }, ensure_ascii=False)
        
        try:
            if tool_name == "read_file":
                result = self._handle_read_tool(arguments)
            elif tool_name in {"vlm_analyze", "ocr_image"}:
                path = arguments.get("path")
                prompt = arguments.get("prompt")
                if not path:
                    return json.dumps({"success": False, "error": "缺少 path 参数", "warnings": []}, ensure_ascii=False)
                result = self.ocr_client.vlm_analyze(path=path, prompt=prompt or "")
            elif tool_name == "view_image":
                path = (arguments.get("path") or "").strip()
                if not path:
                    return json.dumps({"success": False, "error": "path 不能为空"}, ensure_ascii=False)
                if path.startswith("/workspace"):
                    return json.dumps({"success": False, "error": "非法路径，超出项目根目录，请使用不带/workspace的相对路径"}, ensure_ascii=False)
                abs_path = (Path(self.context_manager.project_path) / path).resolve()
                try:
                    abs_path.relative_to(Path(self.context_manager.project_path).resolve())
                except Exception:
                    return json.dumps({"success": False, "error": "非法路径，超出项目根目录，请使用不带/workspace的相对路径"}, ensure_ascii=False)
                if not abs_path.exists() or not abs_path.is_file():
                    return json.dumps({"success": False, "error": f"图片不存在: {path}"}, ensure_ascii=False)
                if abs_path.stat().st_size > 10 * 1024 * 1024:
                    return json.dumps({"success": False, "error": "图片过大，需 <= 10MB"}, ensure_ascii=False)
                allowed_ext = {".png", ".jpg", ".jpeg", ".webp", ".gif", ".bmp", ".svg"}
                if abs_path.suffix.lower() not in allowed_ext:
                    return json.dumps({"success": False, "error": f"不支持的图片格式: {abs_path.suffix}"}, ensure_ascii=False)
                # 记录待注入图片，供上层循环追加消息
                self.pending_image_view = {
                    "path": str(path)
                }
                result = {"success": True, "message": "图片已请求插入到对话中，将在后续消息中呈现。", "path": path}
            
            # 终端会话管理工具
            elif tool_name == "terminal_session":
                action = arguments["action"]
                
                if action == "open":
                    result = self.terminal_manager.open_terminal(
                        session_name=arguments.get("session_name", "default"),
                        working_dir=arguments.get("working_dir"),
                        make_active=True
                    )
                    if result["success"]:
                        print(f"{OUTPUT_FORMATS['session']} 终端会话已打开: {arguments.get('session_name', 'default')}")
                        
                elif action == "close":
                    result = self.terminal_manager.close_terminal(
                        session_name=arguments.get("session_name", "default")
                    )
                    if result["success"]:
                        print(f"{OUTPUT_FORMATS['session']} 终端会话已关闭: {arguments.get('session_name', 'default')}")
                        
                elif action == "list":
                    result = self.terminal_manager.list_terminals()
                    
                elif action == "switch":
                    result = self.terminal_manager.switch_terminal(
                        session_name=arguments.get("session_name", "default")
                    )
                    if result["success"]:
                        print(f"{OUTPUT_FORMATS['session']} 切换到终端: {arguments.get('session_name', 'default')}")
                        
                else:
                    result = {"success": False, "error": f"未知操作: {action}"}
                result["action"] = action
                    
            # 终端输入工具
            elif tool_name == "terminal_input":
                result = self.terminal_manager.send_to_terminal(
                    command=arguments["command"],
                    session_name=arguments.get("session_name"),
                    timeout=arguments.get("timeout")
                )
                if result["success"]:
                    print(f"{OUTPUT_FORMATS['terminal']} 执行命令: {arguments['command']}")
            
            elif tool_name == "terminal_snapshot":
                result = self.terminal_manager.get_terminal_snapshot(
                    session_name=arguments.get("session_name"),
                    lines=arguments.get("lines"),
                    max_chars=arguments.get("max_chars")
                )
            
            elif tool_name == "terminal_reset":
                result = self.terminal_manager.reset_terminal(
                    session_name=arguments.get("session_name")
                )
                if result["success"]:
                    print(f"{OUTPUT_FORMATS['session']} 终端会话已重置: {result['session']}")
                    
            # sleep工具
            elif tool_name == "sleep":
                seconds = arguments.get("seconds", 1)
                reason = arguments.get("reason", "等待操作完成")
                
                # 限制最大等待时间
                max_sleep = 600  # 最多等待60秒
                if seconds > max_sleep:
                    result = {
                        "success": False,
                        "error": f"等待时间过长，最多允许 {max_sleep} 秒",
                        "suggestion": f"建议分多次等待或减少等待时间"
                    }
                else:
                    # 确保秒数为正数
                    if seconds <= 0:
                        result = {
                            "success": False,
                            "error": "等待时间必须大于0"
                        }
                    else:
                        print(f"{OUTPUT_FORMATS['info']} 等待 {seconds} 秒: {reason}")
                        
                        # 执行等待
                        import asyncio
                        await asyncio.sleep(seconds)
                        
                        result = {
                            "success": True,
                            "message": f"已等待 {seconds} 秒",
                            "reason": reason,
                            "timestamp": datetime.now().isoformat()
                        }
                        
                        print(f"{OUTPUT_FORMATS['success']} 等待完成")
                    
            elif tool_name == "create_file":
                result = self.file_manager.create_file(
                    path=arguments["path"],
                    file_type=arguments["file_type"]
                )
                # 添加备注
                if result["success"] and arguments.get("annotation"):
                    self.context_manager.update_annotation(
                        result["path"],
                        arguments["annotation"]
                    )
                if result.get("success"):
                    result["message"] = (
                        f"已创建空文件: {result['path']}。请使用 write_file_diff 提交补丁写入正文。"
                    )
            
            elif tool_name == "delete_file":
                result = self.file_manager.delete_file(arguments["path"])
                # 如果删除成功，同时删除备注和聚焦
                if result.get("success") and result.get("action") == "deleted":
                    deleted_path = result.get("path")
                    # 删除备注
                    if deleted_path in self.context_manager.file_annotations:
                        del self.context_manager.file_annotations[deleted_path]
                        self.context_manager.save_annotations()
                        print(f"🧹 已删除文件备注: {deleted_path}")
                    # 删除聚焦
                    if deleted_path in self.focused_files:
                        del self.focused_files[deleted_path]
                        print(f"🔍 已取消文件聚焦: {deleted_path}")
                
            elif tool_name == "rename_file":
                result = self.file_manager.rename_file(
                    arguments["old_path"],
                    arguments["new_path"]
                )
                # 如果重命名成功，更新备注和聚焦的key
                if result.get("success") and result.get("action") == "renamed":
                    old_path = result.get("old_path")
                    new_path = result.get("new_path")
                    # 更新备注
                    if old_path in self.context_manager.file_annotations:
                        annotation = self.context_manager.file_annotations[old_path]
                        del self.context_manager.file_annotations[old_path]
                        self.context_manager.file_annotations[new_path] = annotation
                        self.context_manager.save_annotations()
                        print(f"📝 已更新文件备注: {old_path} -> {new_path}")
                    # 更新聚焦
                    if old_path in self.focused_files:
                        content = self.focused_files[old_path]
                        del self.focused_files[old_path]
                        self.focused_files[new_path] = content
                        print(f"🔍 已更新文件聚焦: {old_path} -> {new_path}")
                
            elif tool_name == "write_file_diff":
                path = arguments.get("path")
                patch_text = arguments.get("patch")
                if not path or not patch_text:
                    result = {"success": False, "error": "缺少必要参数: path/patch"}
                else:
                    length_limit = 30000
                    if not DISABLE_LENGTH_CHECK and len(patch_text) > length_limit:
                        result = {
                            "success": False,
                            "error": f"补丁内容过长({len(patch_text)}字符)，超过{length_limit}字符上限",
                            "suggestion": "请拆分补丁后多次调用 write_file_diff。"
                        }
                    else:
                        diff_result = self.file_manager.apply_diff_patch(path, patch_text)
                        result = diff_result
                    
            elif tool_name == "create_folder":
                result = self.file_manager.create_folder(arguments["path"])
            
            elif tool_name == "focus_file":
                path = arguments["path"]
                # 检查是否已经聚焦
                if path in self.focused_files:
                    result = {"success": False, "error": f"文件已经处于聚焦状态: {path}"}
                else:
                    # 检查聚焦文件数量限制
                    if len(self.focused_files) >= 3:
                        result = {
                            "success": False, 
                            "error": f"已达到最大聚焦文件数量(3个)，当前聚焦: {list(self.focused_files.keys())}",
                            "suggestion": "请先使用 unfocus_file 取消部分文件的聚焦"
                        }
                    else:
                        # 读取文件内容
                        read_result = self.file_manager.read_file(path)
                        if read_result["success"]:
                            # 字符数检查
                            char_count = len(read_result["content"])
                            if char_count > MAX_FOCUS_FILE_CHARS:
                                result = {
                                    "success": False,
                                    "error": f"文件过大，有{char_count}字符，请使用run_command限制字符数返回",
                                    "char_count": char_count,
                                    "limit": MAX_FOCUS_FILE_CHARS
                                }
                            else:
                                self.focused_files[path] = read_result["content"]
                                result = {
                                    "success": True, 
                                    "message": f"文件已聚焦: {path}",
                                    "focused_files": list(self.focused_files.keys()),
                                    "file_size": len(read_result["content"])
                                }
                                print(f"🔍 文件已聚焦: {path} ({len(read_result['content'])} 字节)")
                        else:
                            result = read_result
            
            elif tool_name == "unfocus_file":
                path = arguments["path"]
                if path in self.focused_files:
                    del self.focused_files[path]
                    result = {
                        "success": True, 
                        "message": f"已取消文件聚焦: {path}",
                        "remaining_focused": list(self.focused_files.keys())
                    }
                    print(f"✖️ 已取消文件聚焦: {path}")
                else:
                    result = {"success": False, "error": f"文件未处于聚焦状态: {path}"}
                
            elif tool_name == "web_search":
                allowed, quota_info = self.record_search_call()
                if not allowed:
                    return json.dumps({
                        "success": False,
                        "error": f"搜索配额已用尽，将在 {quota_info.get('reset_at')} 重置。请向用户说明情况并提供替代方案。",
                        "quota": quota_info
                    }, ensure_ascii=False)
                search_response = await self.search_engine.search_with_summary(
                    query=arguments["query"],
                    max_results=arguments.get("max_results"),
                    topic=arguments.get("topic"),
                    time_range=arguments.get("time_range"),
                    days=arguments.get("days"),
                    start_date=arguments.get("start_date"),
                    end_date=arguments.get("end_date"),
                    country=arguments.get("country")
                )
                
                if search_response["success"]:
                    result = {
                        "success": True,
                        "summary": search_response["summary"],
                        "filters": search_response.get("filters", {}),
                        "query": search_response.get("query"),
                        "results": search_response.get("results", []),
                        "total_results": search_response.get("total_results", 0)
                    }
                else:
                    result = {
                        "success": False,
                        "error": search_response.get("error", "搜索失败"),
                        "filters": search_response.get("filters", {}),
                        "query": search_response.get("query"),
                        "results": search_response.get("results", []),
                        "total_results": search_response.get("total_results", 0)
                    }
                
            elif tool_name == "extract_webpage":
                url = arguments["url"]
                try:
                    # 从config获取API密钥
                    from config import TAVILY_API_KEY
                    full_content, _ = await extract_webpage_content(
                        urls=url, 
                        api_key=TAVILY_API_KEY,
                        extract_depth="basic",
                        max_urls=1
                    )
                    
                    # 字符数检查
                    char_count = len(full_content)
                    if char_count > MAX_EXTRACT_WEBPAGE_CHARS:
                        result = {
                            "success": False,
                            "error": f"网页提取返回了过长的{char_count}字符，请不要提取这个网页，可以使用网页保存功能，然后使用read工具查找或查看网页",
                            "char_count": char_count,
                            "limit": MAX_EXTRACT_WEBPAGE_CHARS,
                            "url": url
                        }
                    else:
                        result = {
                            "success": True,
                            "url": url,
                            "content": full_content
                        }
                except Exception as e:
                    result = {
                        "success": False,
                        "error": f"网页提取失败: {str(e)}",
                        "url": url
                    }

            elif tool_name == "save_webpage":
                url = arguments["url"]
                target_path = arguments["target_path"]
                try:
                    from config import TAVILY_API_KEY
                except ImportError:
                    TAVILY_API_KEY = None

                if not TAVILY_API_KEY or TAVILY_API_KEY == "your-tavily-api-key":
                    result = {
                        "success": False,
                        "error": "Tavily API密钥未配置，无法保存网页",
                        "url": url,
                        "path": target_path
                    }
                else:
                    try:
                        extract_result = await tavily_extract(
                            urls=url,
                            api_key=TAVILY_API_KEY,
                            extract_depth="basic",
                            max_urls=1
                        )

                        if not extract_result or "error" in extract_result:
                            error_message = extract_result.get("error", "提取失败，未返回任何内容") if isinstance(extract_result, dict) else "提取失败"
                            result = {
                                "success": False,
                                "error": error_message,
                                "url": url,
                                "path": target_path
                            }
                        else:
                            results_list = extract_result.get("results", []) if isinstance(extract_result, dict) else []

                            primary_result = None
                            for item in results_list:
                                if item.get("raw_content"):
                                    primary_result = item
                                    break
                            if primary_result is None and results_list:
                                primary_result = results_list[0]

                            if not primary_result:
                                failed_list = extract_result.get("failed_results", []) if isinstance(extract_result, dict) else []
                                result = {
                                    "success": False,
                                    "error": "提取成功结果为空，无法保存",
                                    "url": url,
                                    "path": target_path,
                                    "failed": failed_list
                                }
                            else:
                                content_to_save = primary_result.get("raw_content") or primary_result.get("content") or ""

                                if not content_to_save:
                                    result = {
                                        "success": False,
                                        "error": "网页内容为空，未写入文件",
                                        "url": url,
                                        "path": target_path
                                    }
                                else:
                                    write_result = self.file_manager.write_file(target_path, content_to_save, mode="w")

                                    if not write_result.get("success"):
                                        result = {
                                            "success": False,
                                            "error": write_result.get("error", "写入文件失败"),
                                            "url": url,
                                            "path": target_path
                                        }
                                    else:
                                        char_count = len(content_to_save)
                                        byte_size = len(content_to_save.encode("utf-8"))
                                        result = {
                                            "success": True,
                                            "url": url,
                                            "path": write_result.get("path", target_path),
                                            "char_count": char_count,
                                            "byte_size": byte_size,
                                            "message": f"网页内容已以纯文本保存到 {write_result.get('path', target_path)}，可用 read_file 的 search/extract 查看，必要时再用终端命令。"
                                        }

                                        if isinstance(extract_result, dict) and extract_result.get("failed_results"):
                                            result["warnings"] = extract_result["failed_results"]

                    except Exception as e:
                        result = {
                            "success": False,
                            "error": f"网页保存失败: {str(e)}",
                            "url": url,
                            "path": target_path
                        }

            elif tool_name == "run_python":
                result = await self.terminal_ops.run_python_code(
                    arguments["code"],
                    timeout=arguments.get("timeout")
                )
                
            elif tool_name == "run_command":
                result = await self.terminal_ops.run_command(
                    arguments["command"],
                    timeout=arguments.get("timeout")
                )
                
                # 字符数检查
                if result.get("success") and "output" in result:
                    char_count = len(result["output"])
                    if char_count > MAX_RUN_COMMAND_CHARS:
                        result = {
                            "success": False,
                            "error": f"结果内容过大，有{char_count}字符，请使用限制字符数的获取内容方式，根据程度选择10k以内的数",
                            "char_count": char_count,
                            "limit": MAX_RUN_COMMAND_CHARS,
                            "command": arguments["command"]
                        }
                
            elif tool_name == "update_memory":
                memory_type = arguments["memory_type"]
                operation = arguments["operation"]
                content = arguments.get("content")
                index = arguments.get("index")

                # 参数校验
                if operation == "append" and (not content or not str(content).strip()):
                    result = {"success": False, "error": "append 操作需要 content"}
                elif operation == "replace" and (index is None or index <= 0 or not content or not str(content).strip()):
                    result = {"success": False, "error": "replace 操作需要有效的 index 和 content"}
                elif operation == "delete" and (index is None or index <= 0):
                    result = {"success": False, "error": "delete 操作需要有效的 index"}
                else:
                    result = self.memory_manager.update_entries(
                        memory_type=memory_type,
                        operation=operation,
                        content=content,
                        index=index
                    )
            
            elif tool_name == "todo_create":
                result = self.todo_manager.create_todo_list(
                    overview=arguments.get("overview", ""),
                    tasks=arguments.get("tasks", [])
                )
            
            elif tool_name == "todo_update_task":
                result = self.todo_manager.update_task_status(
                    task_index=arguments.get("task_index"),
                    completed=arguments.get("completed", True)
                )
            
            elif tool_name == "todo_finish":
                result = self.todo_manager.finish_todo(
                    reason=arguments.get("reason")
                )
            
            elif tool_name == "todo_finish_confirm":
                result = self.todo_manager.confirm_finish(
                    confirm=arguments.get("confirm", False),
                    reason=arguments.get("reason")
                )
            
            elif tool_name == "create_sub_agent":
                result = self.sub_agent_manager.create_sub_agent(
                    agent_id=arguments.get("agent_id"),
                    summary=arguments.get("summary", ""),
                    task=arguments.get("task", ""),
                    target_dir=arguments.get("target_dir", ""),
                    reference_files=arguments.get("reference_files", []),
                    timeout_seconds=arguments.get("timeout_seconds"),
                    conversation_id=self.context_manager.current_conversation_id
                )
            
            elif tool_name == "wait_sub_agent":
                wait_timeout = arguments.get("timeout_seconds")
                if not wait_timeout:
                    task_ref = self.sub_agent_manager.lookup_task(
                        task_id=arguments.get("task_id"),
                        agent_id=arguments.get("agent_id")
                    )
                    if task_ref:
                        wait_timeout = task_ref.get("timeout_seconds")
                result = self.sub_agent_manager.wait_for_completion(
                    task_id=arguments.get("task_id"),
                    agent_id=arguments.get("agent_id"),
                    timeout_seconds=wait_timeout
                )

            elif tool_name == "close_sub_agent":
                result = self.sub_agent_manager.terminate_sub_agent(
                    task_id=arguments.get("task_id"),
                    agent_id=arguments.get("agent_id")
                )
            
            elif tool_name == "trigger_easter_egg":
                result = self.easter_egg_manager.trigger_effect(arguments.get("effect"))
            
            else:
                result = {"success": False, "error": f"未知工具: {tool_name}"}
                
        except Exception as e:
            logger.error(f"工具执行失败: {tool_name} - {e}")
            result = {"success": False, "error": f"工具执行异常: {str(e)}"}
    
        return json.dumps(result, ensure_ascii=False)
    
    async def confirm_action(self, action: str, arguments: Dict) -> bool:
        """确认危险操作"""
        print(f"\n{OUTPUT_FORMATS['confirm']} 需要确认的操作:")
        print(f"  操作: {action}")
        print(f"  参数: {json.dumps(arguments, ensure_ascii=False, indent=2)}")
        
        response = input("\n是否继续? (y/n): ").strip().lower()
        return response == 'y'
    
    def build_context(self) -> Dict:
        """构建主终端上下文"""
        # 读取记忆
        memory = self.memory_manager.read_main_memory()
        
        # 构建上下文
        return self.context_manager.build_main_context(memory)
    
    def _tool_calls_followed_by_tools(self, conversation: List[Dict], start_idx: int, tool_calls: List[Dict]) -> bool:
        """判断指定助手消息的工具调用是否拥有后续的工具响应。"""
        if not tool_calls:
            return False
        expected_ids = [tc.get("id") for tc in tool_calls if tc.get("id")]
        if not expected_ids:
            return False
        matched: Set[str] = set()
        idx = start_idx + 1
        total = len(conversation)
        while idx < total and len(matched) < len(expected_ids):
            next_conv = conversation[idx]
            role = next_conv.get("role")
            if role == "tool":
                call_id = next_conv.get("tool_call_id")
                if call_id in expected_ids:
                    matched.add(call_id)
                else:
                    break
            elif role in ("assistant", "user"):
                break
            idx += 1
        return len(matched) == len(expected_ids)

    def build_messages(self, context: Dict, user_input: str) -> List[Dict]:
        """构建消息列表（添加终端内容注入）"""
        # 加载系统提示（Qwen-VL 使用专用提示）
        prompt_name = "main_system_qwenvl" if getattr(self, "model_key", "kimi") == "qwen3-vl-plus" else "main_system"
        system_prompt = self.load_prompt(prompt_name)
        
        # 格式化系统提示
        container_path = self.container_mount_path or "/workspace"
        container_cpus = self.container_cpu_limit
        container_memory = self.container_memory_limit
        project_storage = self.project_storage_limit
        model_key = getattr(self, "model_key", "kimi")
        prompt_replacements = get_model_prompt_replacements(model_key)
        system_prompt = system_prompt.format(
            project_path=container_path,
            container_path=container_path,
            container_cpus=container_cpus,
            container_memory=container_memory,
            project_storage=project_storage,
            file_tree=context["project_info"]["file_tree"],
            memory=context["memory"],
            current_time=datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
            model_description=prompt_replacements.get("model_description", "")
        )
        
        messages = [
            {"role": "system", "content": system_prompt}
        ]

        if self.tool_category_states.get("todo", True):
            todo_prompt = self.load_prompt("todo_guidelines").strip()
            if todo_prompt:
                messages.append({"role": "system", "content": todo_prompt})
        
        if self.tool_category_states.get("sub_agent", True):
            sub_agent_prompt = self.load_prompt("sub_agent_guidelines").strip()
            if sub_agent_prompt:
                messages.append({"role": "system", "content": sub_agent_prompt})
        
        if self.deep_thinking_mode:
            deep_prompt = self.load_prompt("deep_thinking_mode_guidelines").strip()
            if deep_prompt:
                deep_prompt = deep_prompt.format(
                    deep_thinking_line=prompt_replacements.get("deep_thinking_line", "")
                )
                messages.append({"role": "system", "content": deep_prompt})
        elif self.thinking_mode:
            thinking_prompt = self.load_prompt("thinking_mode_guidelines").strip()
            if thinking_prompt:
                thinking_prompt = thinking_prompt.format(
                    thinking_model_line=prompt_replacements.get("thinking_model_line", "")
                )
                messages.append({"role": "system", "content": thinking_prompt})

        personalization_config = load_personalization_config(self.data_dir)
        personalization_block = build_personalization_prompt(personalization_config, include_header=False)
        if personalization_block:
            personalization_template = self.load_prompt("personalization").strip()
            if personalization_template and "{personalization_block}" in personalization_template:
                personalization_text = personalization_template.format(personalization_block=personalization_block)
            elif personalization_template:
                personalization_text = f"{personalization_template}\n{personalization_block}"
            else:
                personalization_text = personalization_block
            messages.append({"role": "system", "content": personalization_text})
        
        # 添加对话历史（保留完整结构，包括tool_calls和tool消息）
        conversation = context["conversation"]
        for idx, conv in enumerate(conversation):
            metadata = conv.get("metadata") or {}
            if conv["role"] == "assistant":
                # Assistant消息可能包含工具调用
                message = {
                    "role": conv["role"],
                    "content": conv["content"]
                }
                reasoning = conv.get("reasoning_content")
                if reasoning:
                    message["reasoning_content"] = reasoning
                # 如果有工具调用信息，添加到消息中
                tool_calls = conv.get("tool_calls") or []
                if tool_calls and self._tool_calls_followed_by_tools(conversation, idx, tool_calls):
                    message["tool_calls"] = tool_calls
                messages.append(message)
                
            elif conv["role"] == "tool":
                # Tool消息需要保留完整结构
                message = {
                    "role": "tool",
                    "content": conv["content"],
                    "tool_call_id": conv.get("tool_call_id", ""),
                    "name": conv.get("name", "")
                }
                messages.append(message)
                
            elif conv["role"] == "system" and metadata.get("sub_agent_notice"):
                # 转换为用户消息，让模型能及时响应
                messages.append({
                    "role": "user",
                    "content": conv["content"]
                })
            else:
                # User 或普通 System 消息
                images = conv.get("images") or metadata.get("images") or []
                content_payload = (
                    self.context_manager._build_content_with_images(conv["content"], images)
                    if images else conv["content"]
                )
                messages.append({
                    "role": conv["role"],
                    "content": content_payload
                })
        
        # 当前用户输入已经在conversation中了，不需要重复添加

        todo_message = self.context_manager.render_todo_system_message()
        if todo_message:
            messages.append({
                "role": "system",
                "content": todo_message
            })
        
        # 在最后注入聚焦文件内容作为系统消息
        if self.focused_files:
            focused_content = "\n\n=== 🔍 正在聚焦的文件 ===\n"
            focused_content += f"(共 {len(self.focused_files)} 个文件处于聚焦状态)\n"
            
            for path, content in self.focused_files.items():
                size_kb = len(content) / 1024
                focused_content += f"\n--- 文件: {path} ({size_kb:.1f}KB) ---\n"
                focused_content += f"```\n{content}\n```\n"
            
            focused_content += "\n=== 聚焦文件结束 ===\n"
            focused_content += "提示：以上文件正在被聚焦，你可以直接看到完整内容并进行修改，禁止再次读取。"
            
            messages.append({
                "role": "system",
                "content": focused_content
            })
        disabled_notice = self._format_disabled_tool_notice()
        if disabled_notice:
            messages.append({
                "role": "system",
                "content": disabled_notice
            })
        return messages
    
    def load_prompt(self, name: str) -> str:
        """加载提示模板"""
        prompt_file = Path(PROMPTS_DIR) / f"{name}.txt"
        if prompt_file.exists():
            with open(prompt_file, 'r', encoding='utf-8') as f:
                return f.read()
        return "你是一个AI助手。"
    
    async def show_focused_files(self, args: str = ""):
        """显示当前聚焦的文件"""
        if not self.focused_files:
            print(f"{OUTPUT_FORMATS['info']} 当前没有聚焦的文件")
        else:
            print(f"\n🔍 聚焦文件列表 ({len(self.focused_files)}/3):")
            print("="*50)
            for path, content in self.focused_files.items():
                size_kb = len(content) / 1024
                lines = content.count('\n') + 1
                print(f"  📄 {path}")
                print(f"     大小: {size_kb:.1f}KB | 行数: {lines}")
            print("="*50)
    
    async def show_terminals(self, args: str = ""):
        """显示终端会话列表"""
        result = self.terminal_manager.list_terminals()
        
        if result["total"] == 0:
            print(f"{OUTPUT_FORMATS['info']} 当前没有活动的终端会话")
        else:
            print(f"\n📺 终端会话列表 ({result['total']}/{result['max_allowed']}):")
            print("="*50)
            for session in result["sessions"]:
                status_icon = "🟢" if session["is_running"] else "🔴"
                active_mark = " [活动]" if session["is_active"] else ""
                print(f"  {status_icon} {session['session_name']}{active_mark}")
                print(f"     工作目录: {session['working_dir']}")
                print(f"     Shell: {session['shell']}")
                print(f"     运行时间: {session['uptime_seconds']:.1f}秒")
                if session["is_interactive"]:
                    print(f"     ⚠️ 等待输入")
            print("="*50)
    
    async def exit_system(self, args: str = ""):
        """退出系统"""
        print(f"{OUTPUT_FORMATS['info']} 正在退出...")
        
        # 关闭所有终端会话
        self.terminal_manager.close_all()
        
        # 保存状态
        await self.save_state()
        
        exit(0)
    
    async def manage_memory(self, args: str = ""):
        """管理记忆"""
        if not args:
            print("""
🧠 记忆管理:
  /memory show [main|task]  - 显示记忆内容
  /memory edit [main|task]  - 编辑记忆
  /memory clear task        - 清空任务记忆
  /memory merge             - 合并任务记忆到主记忆
  /memory backup [main|task]- 备份记忆
""")
            return
        
        parts = args.split()
        action = parts[0] if parts else ""
        target = parts[1] if len(parts) > 1 else "main"
        
        if action == "show":
            if target == "main":
                content = self.memory_manager.read_main_memory()
            else:
                content = self.memory_manager.read_task_memory()
            print(f"\n{'='*50}")
            print(content)
            print('='*50)
        
        elif action == "clear" and target == "task":
            if input("确认清空任务记忆? (y/n): ").lower() == 'y':
                self.memory_manager.clear_task_memory()
        
        elif action == "merge":
            self.memory_manager.merge_memories()
        
        elif action == "backup":
            path = self.memory_manager.backup_memory(target)
            if path:
                print(f"备份保存到: {path}")
    
    async def show_history(self, args: str = ""):
        """显示对话历史"""
        history = self.context_manager.conversation_history[-2000:]  # 最近2000条
        
        print("\n📜 对话历史:")
        print("="*50)
        for conv in history:
            timestamp = conv.get("timestamp", "")
            if conv["role"] == "user":
                role = "👤 用户"
            elif conv["role"] == "assistant":
                role = "🤖 助手"
            elif conv["role"] == "tool":
                role = f"🔧 工具[{conv.get('name', 'unknown')}]"
            else:
                role = conv["role"]
                
            content = conv["content"][:100] + "..." if len(conv["content"]) > 100 else conv["content"]
            print(f"\n[{timestamp[:19]}] {role}:")
            print(content)
            
            # 如果是助手消息且有工具调用，显示工具信息
            if conv["role"] == "assistant" and "tool_calls" in conv and conv["tool_calls"]:
                tools = [tc["function"]["name"] for tc in conv["tool_calls"]]
                print(f"  🔗 调用工具: {', '.join(tools)}")
        print("="*50)
    
    async def show_files(self, args: str = ""):
        """显示项目文件"""
        structure = self.context_manager.get_project_structure()
        print(f"\n📁 项目文件结构:")
        print(self.context_manager._build_file_tree(structure))
        print(f"\n总计: {structure['total_files']} 个文件, {structure['total_size'] / 1024 / 1024:.2f} MB")

    def set_run_mode(self, mode: str) -> str:
        """统一设置运行模式"""
        allowed = ["fast", "thinking", "deep"]
        normalized = mode.lower()
        if normalized not in allowed:
            raise ValueError(f"不支持的模式: {mode}")
        # Qwen-VL 官方不支持深度思考模式
        if getattr(self, "model_key", None) == "qwen3-vl-plus" and normalized == "deep":
            raise ValueError("Qwen-VL 不支持深度思考模式")
        # fast-only 模型限制
        if getattr(self, "model_profile", {}).get("fast_only") and normalized != "fast":
            raise ValueError("当前模型仅支持快速模式")
        previous_mode = getattr(self, "run_mode", "fast")
        self.run_mode = normalized
        self.thinking_mode = normalized != "fast"
        self.deep_thinking_mode = normalized == "deep"
        self.api_client.thinking_mode = self.thinking_mode
        self.api_client.set_deep_thinking_mode(self.deep_thinking_mode)
        if self.deep_thinking_mode:
            self.api_client.force_thinking_next_call = False
            self.api_client.skip_thinking_next_call = False
        if not self.thinking_mode:
            self.api_client.start_new_task()
        elif previous_mode == "deep" and normalized != "deep":
            self.api_client.start_new_task()
        return self.run_mode

    def apply_model_profile(self, profile: dict):
        """将模型配置应用到 API 客户端"""
        if not profile:
            return
        self.api_client.apply_profile(profile)

    def set_model(self, model_key: str) -> str:
        profile = get_model_profile(model_key)
        if getattr(self.context_manager, "has_images", False) and model_key != "qwen3-vl-plus":
            raise ValueError("当前对话包含图片，仅支持 Qwen-VL")
        self.model_key = model_key
        self.model_profile = profile
        # 将模型标识传递给底层 API 客户端，便于按模型做兼容处理
        self.api_client.model_key = model_key
        # 应用模型配置
        self.apply_model_profile(profile)
        # fast-only 模型强制快速模式
        if profile.get("fast_only") and self.run_mode != "fast":
            self.set_run_mode("fast")
        # 如果模型支持思考，但当前 run_mode 为 thinking/deep，则保持；否则无需调整
        self.api_client.start_new_task(force_deep=self.deep_thinking_mode)
        return self.model_key

    def get_run_mode_label(self) -> str:
        labels = {
            "fast": "快速模式（无思考）",
            "thinking": "思考模式（首次调用使用思考模型）",
            "deep": "深度思考模式（整轮使用思考模型）"
        }
        return labels.get(self.run_mode, "快速模式（无思考）")

    async def toggle_mode(self, args: str = ""):
        """切换运行模式"""
        modes = ["fast", "thinking", "deep"]
        target_mode = ""
        if args:
            candidate = args.strip().lower()
            if candidate not in modes:
                print(f"{OUTPUT_FORMATS['error']} 无效模式: {args}。可选: fast / thinking / deep")
                return
            target_mode = candidate
        else:
            current_index = modes.index(self.run_mode) if self.run_mode in modes else 0
            target_mode = modes[(current_index + 1) % len(modes)]
        if target_mode == self.run_mode:
            print(f"{OUTPUT_FORMATS['info']} 当前已是 {self.get_run_mode_label()}")
            return
        try:
            self.set_run_mode(target_mode)
            print(f"{OUTPUT_FORMATS['info']} 已切换到: {self.get_run_mode_label()}")
        except ValueError as exc:
            print(f"{OUTPUT_FORMATS['error']} {exc}")