2546 lines
126 KiB
Python
2546 lines
126 KiB
Python
# core/main_terminal.py - 主终端（集成对话持久化）
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import asyncio
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import json
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from datetime import datetime
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from pathlib import Path
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from typing import Any, Dict, List, Optional, Set, TYPE_CHECKING
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from datetime import datetime
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try:
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from config import (
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OUTPUT_FORMATS, DATA_DIR, PROMPTS_DIR, NEED_CONFIRMATION,
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MAX_TERMINALS, TERMINAL_BUFFER_SIZE, TERMINAL_DISPLAY_SIZE,
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MAX_READ_FILE_CHARS, READ_TOOL_DEFAULT_MAX_CHARS,
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READ_TOOL_DEFAULT_CONTEXT_BEFORE, READ_TOOL_DEFAULT_CONTEXT_AFTER,
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READ_TOOL_MAX_CONTEXT_BEFORE, READ_TOOL_MAX_CONTEXT_AFTER,
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READ_TOOL_DEFAULT_MAX_MATCHES, READ_TOOL_MAX_MATCHES,
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READ_TOOL_MAX_FILE_SIZE, MAX_FOCUS_FILE_CHARS,
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TERMINAL_SANDBOX_MOUNT_PATH,
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TERMINAL_SANDBOX_CPUS,
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TERMINAL_SANDBOX_MEMORY,
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PROJECT_MAX_STORAGE_MB,
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)
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except ImportError:
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import sys
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from pathlib import Path
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project_root = Path(__file__).resolve().parents[1]
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if str(project_root) not in sys.path:
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sys.path.insert(0, str(project_root))
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from config import (
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OUTPUT_FORMATS, DATA_DIR, PROMPTS_DIR, NEED_CONFIRMATION,
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MAX_TERMINALS, TERMINAL_BUFFER_SIZE, TERMINAL_DISPLAY_SIZE,
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MAX_READ_FILE_CHARS, READ_TOOL_DEFAULT_MAX_CHARS,
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READ_TOOL_DEFAULT_CONTEXT_BEFORE, READ_TOOL_DEFAULT_CONTEXT_AFTER,
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READ_TOOL_MAX_CONTEXT_BEFORE, READ_TOOL_MAX_CONTEXT_AFTER,
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READ_TOOL_DEFAULT_MAX_MATCHES, READ_TOOL_MAX_MATCHES,
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READ_TOOL_MAX_FILE_SIZE, MAX_FOCUS_FILE_CHARS,
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TERMINAL_SANDBOX_MOUNT_PATH,
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TERMINAL_SANDBOX_CPUS,
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TERMINAL_SANDBOX_MEMORY,
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PROJECT_MAX_STORAGE_MB,
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)
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from modules.file_manager import FileManager
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from modules.search_engine import SearchEngine
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from modules.terminal_ops import TerminalOperator
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from modules.memory_manager import MemoryManager
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from modules.terminal_manager import TerminalManager
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from modules.todo_manager import TodoManager
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from modules.sub_agent_manager import SubAgentManager
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from modules.webpage_extractor import extract_webpage_content, tavily_extract
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from modules.ocr_client import OCRClient
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from modules.easter_egg_manager import EasterEggManager
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from modules.personalization_manager import (
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load_personalization_config,
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build_personalization_prompt,
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)
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try:
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from config.limits import THINKING_FAST_INTERVAL
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except ImportError:
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THINKING_FAST_INTERVAL = 10
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from modules.container_monitor import collect_stats, inspect_state
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from core.tool_config import TOOL_CATEGORIES
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from utils.api_client import DeepSeekClient
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from utils.context_manager import ContextManager
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from utils.tool_result_formatter import format_tool_result_for_context
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from utils.logger import setup_logger
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if TYPE_CHECKING:
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from modules.user_container_manager import ContainerHandle
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logger = setup_logger(__name__)
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# 临时禁用长度检查
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DISABLE_LENGTH_CHECK = True
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class MainTerminal:
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def __init__(
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self,
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project_path: str,
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thinking_mode: bool = False,
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run_mode: Optional[str] = None,
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data_dir: Optional[str] = None,
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container_session: Optional["ContainerHandle"] = None,
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usage_tracker: Optional[object] = None,
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):
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self.project_path = project_path
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allowed_modes = {"fast", "thinking", "deep"}
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initial_mode = run_mode if run_mode in allowed_modes else ("thinking" if thinking_mode else "fast")
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self.run_mode = initial_mode
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self.thinking_mode = initial_mode != "fast" # False=快速模式, True=思考模式
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self.deep_thinking_mode = initial_mode == "deep"
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self.data_dir = Path(data_dir).expanduser().resolve() if data_dir else Path(DATA_DIR).resolve()
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self.usage_tracker = usage_tracker
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# 初始化组件
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self.api_client = DeepSeekClient(thinking_mode=self.thinking_mode)
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self.api_client.set_deep_thinking_mode(self.deep_thinking_mode)
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self.context_manager = ContextManager(project_path, data_dir=str(self.data_dir))
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self.context_manager.main_terminal = self
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self.container_mount_path = TERMINAL_SANDBOX_MOUNT_PATH or "/workspace"
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self.container_cpu_limit = TERMINAL_SANDBOX_CPUS or "未限制"
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self.container_memory_limit = TERMINAL_SANDBOX_MEMORY or "未限制"
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self.project_storage_limit = f"{PROJECT_MAX_STORAGE_MB}MB" if PROJECT_MAX_STORAGE_MB else "未限制"
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self.project_storage_limit_bytes = (
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PROJECT_MAX_STORAGE_MB * 1024 * 1024 if PROJECT_MAX_STORAGE_MB else None
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)
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self.container_session: Optional["ContainerHandle"] = None
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self.memory_manager = MemoryManager(data_dir=str(self.data_dir))
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self.file_manager = FileManager(project_path, container_session=container_session)
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self.search_engine = SearchEngine()
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self.terminal_ops = TerminalOperator(project_path, container_session=container_session)
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self.ocr_client = OCRClient(project_path, self.file_manager)
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# 新增：终端管理器
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self.terminal_manager = TerminalManager(
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project_path=project_path,
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max_terminals=MAX_TERMINALS,
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terminal_buffer_size=TERMINAL_BUFFER_SIZE,
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terminal_display_size=TERMINAL_DISPLAY_SIZE,
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broadcast_callback=None, # CLI模式不需要广播
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container_session=container_session,
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)
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self._apply_container_session(container_session)
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self.todo_manager = TodoManager(self.context_manager)
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self.sub_agent_manager = SubAgentManager(
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project_path=self.project_path,
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data_dir=str(self.data_dir)
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)
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self.easter_egg_manager = EasterEggManager()
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self._announced_sub_agent_tasks = set()
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# 聚焦文件管理
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self.focused_files = {} # {path: content} 存储聚焦的文件内容
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self.current_session_id = 0 # 用于标识不同的任务会话
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# 工具启用状态
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self.tool_category_states = {
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key: category.default_enabled
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for key, category in TOOL_CATEGORIES.items()
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}
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self.disabled_tools = set()
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self.disabled_notice_tools = set()
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self._refresh_disabled_tools()
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self.thinking_fast_interval = THINKING_FAST_INTERVAL
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self.default_disabled_tool_categories: List[str] = []
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self.apply_personalization_preferences()
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# 新增：自动开始新对话
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self._ensure_conversation()
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# 命令映射
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self.commands = {
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"help": self.show_help,
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"exit": self.exit_system,
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"status": self.show_status,
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"memory": self.manage_memory,
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"clear": self.clear_conversation,
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"history": self.show_history,
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"files": self.show_files,
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"mode": self.toggle_mode,
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"focused": self.show_focused_files,
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"terminals": self.show_terminals,
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# 新增：对话管理命令
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"conversations": self.show_conversations,
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"load": self.load_conversation_command,
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"new": self.new_conversation_command,
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"save": self.save_conversation_command
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}
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#self.context_manager._web_terminal_callback = message_callback
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#self.context_manager._focused_files = self.focused_files # 引用传递
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def _apply_container_session(self, session: Optional["ContainerHandle"]):
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self.container_session = session
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if session and session.mode == "docker":
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self.container_mount_path = session.mount_path or (TERMINAL_SANDBOX_MOUNT_PATH or "/workspace")
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else:
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self.container_mount_path = TERMINAL_SANDBOX_MOUNT_PATH or "/workspace"
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def record_model_call(self, is_thinking: bool):
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tracker = getattr(self, "usage_tracker", None)
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if not tracker:
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return True, {}
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mode = "thinking" if is_thinking else "fast"
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try:
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allowed, info = tracker.check_and_increment(mode)
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if allowed:
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self._notify_quota_update(mode)
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return allowed, info
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except Exception:
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return True, {}
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def record_search_call(self):
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tracker = getattr(self, "usage_tracker", None)
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if not tracker:
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return True, {}
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try:
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allowed, info = tracker.check_and_increment("search")
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if allowed:
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self._notify_quota_update("search")
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return allowed, info
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except Exception:
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return True, {}
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def _notify_quota_update(self, metric: str):
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callback = getattr(self, "quota_update_callback", None)
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if callable(callback):
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try:
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callback(metric)
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except Exception:
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pass
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def update_container_session(self, session: Optional["ContainerHandle"]):
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self._apply_container_session(session)
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if getattr(self, "terminal_manager", None):
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self.terminal_manager.update_container_session(session)
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if getattr(self, "terminal_ops", None):
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self.terminal_ops.set_container_session(session)
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if getattr(self, "file_manager", None):
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self.file_manager.set_container_session(session)
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def _ensure_conversation(self):
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||
"""确保CLI模式下存在可用的对话ID"""
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if self.context_manager.current_conversation_id:
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return
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latest_list = self.context_manager.get_conversation_list(limit=1, offset=0)
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conversations = latest_list.get("conversations", []) if latest_list else []
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||
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if conversations:
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latest = conversations[0]
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conv_id = latest.get("id")
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if conv_id and self.context_manager.load_conversation_by_id(conv_id):
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||
print(f"{OUTPUT_FORMATS['info']} 已加载最近对话: {conv_id}")
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return
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conversation_id = self.context_manager.start_new_conversation(
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project_path=self.project_path,
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thinking_mode=self.thinking_mode,
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run_mode=self.run_mode
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)
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print(f"{OUTPUT_FORMATS['info']} 新建对话: {conversation_id}")
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@staticmethod
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def _clamp_int(value, default, min_value=None, max_value=None):
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"""将输入转换为整数并限制范围。"""
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||
if value is None:
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return default
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try:
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num = int(value)
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except (TypeError, ValueError):
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||
return default
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||
if min_value is not None:
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num = max(min_value, num)
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if max_value is not None:
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num = min(max_value, num)
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return num
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@staticmethod
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def _parse_optional_line(value, field_name: str):
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"""解析可选的行号参数。"""
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if value is None:
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return None, None
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||
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"
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||
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
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||
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 = {}
|
||
|
||
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()
|
||
|
||
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 == "ocr_image":
|
||
print(f"{OUTPUT_FORMATS['file']} 图片OCR")
|
||
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 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": {
|
||
"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": {
|
||
"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": {
|
||
"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": "ocr_image",
|
||
"description": "使用 Qwen3-VL模型 读取图片中的文字或根据提示生成描述，仅支持本地图片路径。",
|
||
"parameters": {
|
||
"type": "object",
|
||
"properties": {
|
||
"path": {"type": "string", "description": "项目内的图片路径"},
|
||
"prompt": {"type": "string", "description": "传递给 OCR 模型的提示词，如“请识别图片中的文字”，“图中的手机是什么颜色的”必须使用中文提示词。"}
|
||
},
|
||
"required": ["path", "prompt"]
|
||
}
|
||
}
|
||
},
|
||
{
|
||
"type": "function",
|
||
"function": {
|
||
"name": "delete_file",
|
||
"description": "删除文件",
|
||
"parameters": {
|
||
"type": "object",
|
||
"properties": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"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": {
|
||
"effect": {
|
||
"type": "string",
|
||
"description": "彩蛋标识，目前支持 flood（灌水）与 snake（贪吃蛇）。"
|
||
}
|
||
},
|
||
"required": ["effect"]
|
||
}
|
||
}
|
||
}
|
||
]
|
||
if self.disabled_tools:
|
||
tools = [
|
||
tool for tool in tools
|
||
if tool.get("function", {}).get("name") not in self.disabled_tools
|
||
]
|
||
return 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 == "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.ocr_image(path=path, prompt=prompt or "")
|
||
|
||
# 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)}，请使用终端命令查看（文件建议为 .txt）。"
|
||
}
|
||
|
||
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
|
||
system_prompt = self.load_prompt("main_system")
|
||
|
||
# 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
|
||
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")
|
||
)
|
||
|
||
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:
|
||
messages.append({"role": "system", "content": deep_prompt})
|
||
elif self.thinking_mode:
|
||
thinking_prompt = self.load_prompt("thinking_mode_guidelines").strip()
|
||
if thinking_prompt:
|
||
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
|
||
messages.append({
|
||
"role": conv["role"],
|
||
"content": conv["content"]
|
||
})
|
||
|
||
# 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}")
|
||
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 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}")
|
||
|