JOJO
9ed956518c
- 重写子智能体执行核心，不再启动 easyagent Node.js 子进程 - 新增 modules/sub_agent/ 包集中管理子智能体逻辑 - 工具调用复用主进程 WebTerminal.handle_tool_call，自然经过沙箱/容器链路 - 子智能体模型独立读取 ~/.agents/<mode>/config/sub_agent_models.json - 支持 8 个工具：read_file/write_file/edit_file(replacements+replace_all)/run_command/web_search/extract_webpage/search_workspace/read_mediafile - 修复子智能体进度弹窗：标题颜色、write_file 显示、过滤非 progress 条目、统一滚动条样式 - 更新 AGENTS.md / CLAUDE.md 子智能体描述 - 新增 test/test_sub_agent_regression.py 回归测试
681 lines
32 KiB
Python
681 lines
32 KiB
Python
import asyncio
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import json
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from pathlib import Path
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from typing import Any, Dict, List, Optional, Set
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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,
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TERMINAL_SANDBOX_MOUNT_PATH,
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TERMINAL_SANDBOX_MODE,
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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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CUSTOM_TOOLS_ENABLED,
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)
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except ImportError:
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import sys
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project_root = Path(__file__).resolve().parents[2]
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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,
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TERMINAL_SANDBOX_MOUNT_PATH,
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TERMINAL_SANDBOX_MODE,
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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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CUSTOM_TOOLS_ENABLED,
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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 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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RECENT_CONVERSATIONS_PROMPT_LIMIT_MIN,
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RECENT_CONVERSATIONS_PROMPT_LIMIT_MAX,
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RECENT_CONVERSATIONS_PROMPT_LIMIT_DEFAULT,
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)
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from modules.skills_manager import (
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get_skills_catalog,
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build_skills_list,
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merge_enabled_skills,
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build_skills_prompt,
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infer_private_skills_dir,
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)
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from modules.custom_tool_registry import CustomToolRegistry, build_default_tool_category
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from modules.custom_tool_executor import CustomToolExecutor
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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, AUTO_SHALLOW_PLACEHOLDER
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from utils.host_workspace_debug import write_host_workspace_debug
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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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from config.model_profiles import (
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get_model_profile,
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get_model_prompt_replacements,
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get_model_context_window,
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model_supports_image,
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model_supports_video,
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)
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logger = setup_logger(__name__)
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DISABLE_LENGTH_CHECK = True
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class MainTerminalContextMixin:
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# 权限模式说明（代码中存储的简要版本）
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_PERMISSION_MODE_DESC = {
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"unrestricted": "当前处于无限制模式，所有工具均可直接使用，无需额外批准。",
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"readonly": "当前处于只读模式，仅能执行不会修改工作区的读取类操作。",
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"approval": "当前处于批准模式，修改工作区的操作需要用户批准后方可执行。",
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"auto_approval": "当前处于自动审核模式，工作区内文件编辑可直接执行，高风险操作由后台审批智能体自动审核。",
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}
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_PERMISSION_MODE_LABEL = {
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"unrestricted": "无限制",
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"readonly": "只读",
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"approval": "批准",
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"auto_approval": "自动审核",
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}
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_EXECUTION_MODE_LABEL = {
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"sandbox": "沙箱",
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"direct": "完全访问权限",
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}
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def _build_permission_mode_message(self) -> Optional[str]:
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"""根据当前权限模式构建权限说明消息（从模板读取并替换占位符）"""
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template = self.load_prompt("permission_mode")
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if not template:
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return None
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mode = self.get_permission_mode()
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# 根据模式生成详细规则
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if mode == "unrestricted":
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detailed_rules = (
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"- 所有命令和工具均可直接使用，无需用户批准\n"
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"- run_command：支持任意命令，包括管道、重定向、子shell等\n"
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"- 文件操作：read_file / write_file / edit_file 可直接使用；其他文件管理请通过 run_command 执行；需要 Python 时先探测并选择合适解释器"
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)
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elif mode == "readonly":
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detailed_rules = (
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"- run_command：统一在系统只读沙箱中执行\n"
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"- 若命令触发写入，系统会直接拒绝并返回权限错误\n"
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"- 文件操作：仅允许 read_file、view_image、view_video 等读取类工具\n"
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"- 禁止：write_file、edit_file 及会修改工作区的命令操作"
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)
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elif mode == "approval":
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detailed_rules = (
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"- run_command：先在系统只读沙箱执行；仅当出现权限拒绝时才触发审批\n"
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"- 审批通过后：仅当前这一次命令会重试为可写沙箱执行\n"
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"- 需要用户批准：terminal_input、write_file、edit_file、save_webpage 及其他会修改工作区的操作\n"
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"- 被拒绝或超时：本次操作不会执行写入"
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)
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elif mode == "auto_approval":
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detailed_rules = (
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"- write_file / edit_file：若路径在当前工作区内，直接执行；工作区外路径会进入审批流程\n"
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"- run_command：先在系统只读沙箱执行；仅当出现权限拒绝时才触发自动审批\n"
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"- 自动审批由后台审批智能体执行，默认只判断危险性与越权风险，不判断任务必要性\n"
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"- 自动审批拒绝：本次工具调用会返回“拒绝+理由”，主循环继续；人工拒绝可随时接管\n"
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"- 可随时人工接管：用户在审批面板点击同意/拒绝/切换无限制后，自动审批会立即停止并以人工决策为准"
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)
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else:
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detailed_rules = ""
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return template.format(
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permission_mode=mode,
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permission_mode_label=self._PERMISSION_MODE_LABEL.get(mode, mode),
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mode_description=self._PERMISSION_MODE_DESC.get(mode, ""),
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detailed_rules=detailed_rules,
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)
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def _build_execution_mode_message(self) -> Optional[str]:
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"""根据当前执行环境模式构建提示消息。"""
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# 仅宿主机模式注入；Docker 模式不需要该提示。
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try:
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if not getattr(self, "_is_host_mode", lambda: False)():
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return None
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except Exception:
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return None
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template = self.load_prompt("execution_mode")
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if not template:
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return None
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state = {}
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if hasattr(self, "get_execution_mode_state"):
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try:
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state = self.get_execution_mode_state() or {}
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except Exception:
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state = {}
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mode = str(state.get("mode") or "sandbox").strip().lower()
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mode_label = self._EXECUTION_MODE_LABEL.get(mode, mode)
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if mode == "sandbox":
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rules = (
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"- 所有命令默认在系统 OS 沙箱中执行\n"
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"- 若操作受系统权限限制：先提供 1 个安全替代方案并执行；若仍无法满足目标，明确请求用户切换执行环境为“完全访问权限”后重试\n"
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"- 不要通过复杂绕过手段反复尝试规避沙箱限制；若任务本质需要更高权限，应直接说明并等待用户确认"
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)
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net = getattr(self, "host_network_permission", "restricted")
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if net == "restricted":
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network_rules = "- 网络：受限（仅允许 localhost，外部网络不可达）"
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elif net == "full":
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network_rules = "- 网络：完全开放"
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else:
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network_rules = ""
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else:
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rules = (
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"- 当前为宿主机直接执行模式（完全访问权限）\n"
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"- 仅在必须时执行高权限操作，保持最小化命令范围\n"
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"- 涉及删除/覆盖/系统级变更前，先说明风险再执行"
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)
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network_rules = ""
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return template.format(
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execution_mode=mode,
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execution_mode_label=mode_label,
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rules=rules,
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network_rules=network_rules,
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)
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def _get_or_init_frozen_mode_prompt(self, key: str, builder) -> Optional[str]:
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return self._get_or_init_frozen_prompt(key, builder)
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def _get_or_init_frozen_prompt(self, key: str, builder) -> Optional[str]:
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cm = getattr(self, "context_manager", None)
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meta = getattr(cm, "conversation_metadata", {}) if cm else {}
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cached = meta.get(key) if isinstance(meta, dict) else None
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if isinstance(cached, str) and cached:
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return cached
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built = builder() or ""
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conv_id = getattr(cm, "current_conversation_id", None) if cm else None
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if cm and conv_id:
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try:
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cm.conversation_manager.update_conversation_metadata(conv_id, {key: built})
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if isinstance(cm.conversation_metadata, dict):
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cm.conversation_metadata[key] = built
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except Exception:
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pass
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return built
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def build_context(self) -> Dict:
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"""构建主终端上下文"""
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# 读取记忆
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memory = self.memory_manager.read_main_memory()
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# 构建上下文
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return self.context_manager.build_main_context(memory)
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def _scan_project_memories(self):
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"""扫描 .agents/memory/*.md 并解析 frontmatter 中的 name 和 description"""
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try:
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memory_dir = Path(self.project_path) / ".agents" / "memory"
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except Exception:
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return []
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if not memory_dir.exists() or not memory_dir.is_dir():
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return []
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results = []
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for md_file in sorted(memory_dir.glob("*.md")):
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try:
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text = md_file.read_text(encoding="utf-8")
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name = None
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description = None
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if text.startswith("---"):
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end = text.find("---", 3)
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if end > 0:
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frontmatter = text[3:end]
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for line in frontmatter.strip().split("\n"):
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line_stripped = line.strip()
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if line_stripped.startswith("name:"):
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name = line_stripped.split(":", 1)[1].strip()
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elif line_stripped.startswith("description:"):
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description = line_stripped.split(":", 1)[1].strip()
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results.append({
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"file": md_file.name,
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"name": name or md_file.stem,
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"description": description or "",
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})
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except Exception:
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pass
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return results
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def _build_memory_system_content(self) -> str:
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"""构建记忆系统的 prompt 内容"""
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template = self.load_prompt("memory_system").strip()
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if not template:
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return ""
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try:
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global_memory = self.memory_manager.read_main_memory()
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global_memory_text = global_memory.strip() if global_memory else ""
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except Exception:
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global_memory_text = ""
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project_memories = self._scan_project_memories()
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if project_memories:
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lines = []
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for m in project_memories:
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desc = m.get("description", "")
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if desc:
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lines.append(f".agents/memory/{m['file']}：{desc}")
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else:
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lines.append(f".agents/memory/{m['file']}")
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project_memory_list = "\n".join(lines)
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else:
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project_memory_list = ""
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result = template
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if global_memory_text:
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result = result.replace("{global_memory}", global_memory_text)
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result = result.replace("[global_memory_empty]", "").replace("[/global_memory_empty]", "")
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else:
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result = result.replace("{global_memory}", "")
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if project_memory_list:
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result = result.replace("{project_memory_list}", project_memory_list)
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result = result.replace("[project_memory_empty]", "").replace("[/project_memory_empty]", "")
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else:
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result = result.replace("{project_memory_list}", "")
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return result.strip()
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def _build_recent_conversations_message(self, limit: int = 10) -> Optional[str]:
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"""构建最近对话提示（仅当前工作区）。"""
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try:
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manager = getattr(self.context_manager, "conversation_manager", None)
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if not manager:
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return None
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current_id = getattr(self.context_manager, "current_conversation_id", None)
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items = manager.get_recent_conversation_summaries(
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limit=limit,
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exclude_conversation_id=current_id,
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first_message_max_chars=100,
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)
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if not items:
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return None
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lines: List[str] = []
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for index, item in enumerate(items, start=1):
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title = str(item.get("title") or "未命名对话").strip()
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conv_id = str(item.get("id") or "").strip()
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first_message = str(item.get("first_user_message") or "").strip() or "（无首条用户消息）"
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updated_at = str(item.get("updated_at") or "").strip()
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lines.append(f"{index}. [{conv_id}] 标题：{title}")
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lines.append(f" 首条用户消息：{first_message}")
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if updated_at:
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lines.append(f" 更新时间：{updated_at}")
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recent_text = "\n".join(lines)
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template = self.load_prompt("recent_conversations").strip()
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if template and "{recent_conversations}" in template:
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return template.format(recent_conversations=recent_text)
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if template:
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return f"{template}\n\n{recent_text}"
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return f"## 最近对话（仅当前工作区）\n\n{recent_text}"
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except Exception:
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return None
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def _tool_calls_followed_by_tools(self, conversation: List[Dict], start_idx: int, tool_calls: List[Dict]) -> bool:
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"""判断指定助手消息的工具调用是否拥有后续的工具响应。"""
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if not tool_calls:
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return False
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expected_ids = [tc.get("id") for tc in tool_calls if tc.get("id")]
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if not expected_ids:
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return False
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matched: Set[str] = set()
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idx = start_idx + 1
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total = len(conversation)
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while idx < total and len(matched) < len(expected_ids):
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next_conv = conversation[idx]
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role = next_conv.get("role")
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if role == "tool":
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call_id = next_conv.get("tool_call_id")
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if call_id in expected_ids:
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matched.add(call_id)
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else:
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break
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elif role in ("assistant", "user"):
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break
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idx += 1
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return len(matched) == len(expected_ids)
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def build_messages(self, context: Dict, user_input: str) -> List[Dict]:
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"""构建消息列表（添加终端内容注入）"""
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try:
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file_tree_preview = (context.get("project_info", {}).get("file_tree") or "").splitlines()
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write_host_workspace_debug(
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"main_terminal.build_messages.context_snapshot",
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terminal_id=id(self),
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terminal_project_path=str(getattr(self, "project_path", "")),
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context_project_path=str(getattr(getattr(self, "context_manager", None), "project_path", "")),
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project_info_path=str(context.get("project_info", {}).get("path", "")),
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file_tree_first_line=file_tree_preview[0] if file_tree_preview else "",
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current_conversation_id=getattr(getattr(self, "context_manager", None), "current_conversation_id", None),
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)
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except Exception:
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pass
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# 根据当前模型多模态能力选择系统提示。system prompt 按对话冻结；
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# 工具 schema 保持动态，由 define_tools 每轮根据真实状态生成。
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current_model = getattr(self, "model_key", None)
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prompt_name = "main_system_qwenvl" if (model_supports_image(current_model) or model_supports_video(current_model)) else "main_system"
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model_key = getattr(self, "model_key", None)
|
||
prompt_replacements = get_model_prompt_replacements(model_key)
|
||
|
||
def _build_main_system_prompt() -> str:
|
||
system_prompt_template = self.load_prompt(prompt_name)
|
||
# main_system.txt / main_system_qwenvl.txt 仅使用 {model_description}
|
||
return system_prompt_template.format(
|
||
model_description=prompt_replacements.get("model_description", "")
|
||
)
|
||
|
||
system_prompt = self._get_or_init_frozen_prompt(
|
||
"frozen_main_system_prompt",
|
||
_build_main_system_prompt,
|
||
)
|
||
|
||
messages = [
|
||
{"role": "system", "content": system_prompt}
|
||
]
|
||
|
||
personalization_config = getattr(self.context_manager, "custom_personalization_config", None) or load_personalization_config(self.data_dir)
|
||
shallow_replace_enabled = bool(personalization_config.get("auto_shallow_compress_enabled", False)) if isinstance(personalization_config, dict) else False
|
||
|
||
# 顺序：主prompt → 权限模式 → 执行环境 → 最近对话 → 个性化配置 → 工作区信息 → AGENTS.md → skills → 记忆 → 自定义 → 禁用提示
|
||
|
||
# 权限模式
|
||
permission_mode_message = self._get_or_init_frozen_mode_prompt(
|
||
"frozen_permission_prompt",
|
||
self._build_permission_mode_message,
|
||
)
|
||
if permission_mode_message:
|
||
messages.append({"role": "system", "content": permission_mode_message})
|
||
|
||
# 执行环境
|
||
execution_mode_message = self._get_or_init_frozen_mode_prompt(
|
||
"frozen_execution_prompt",
|
||
self._build_execution_mode_message,
|
||
)
|
||
if execution_mode_message:
|
||
messages.append({"role": "system", "content": execution_mode_message})
|
||
|
||
# 最近对话
|
||
def _build_recent_conversations_prompt() -> str:
|
||
recent_conversations_enabled = (
|
||
bool(personalization_config.get("recent_conversations_prompt_enabled", False))
|
||
if isinstance(personalization_config, dict)
|
||
else False
|
||
)
|
||
if not recent_conversations_enabled:
|
||
return ""
|
||
try:
|
||
recent_limit = int(
|
||
personalization_config.get(
|
||
"recent_conversations_prompt_limit",
|
||
RECENT_CONVERSATIONS_PROMPT_LIMIT_DEFAULT,
|
||
)
|
||
)
|
||
except Exception:
|
||
recent_limit = RECENT_CONVERSATIONS_PROMPT_LIMIT_DEFAULT
|
||
recent_limit = max(
|
||
RECENT_CONVERSATIONS_PROMPT_LIMIT_MIN,
|
||
min(RECENT_CONVERSATIONS_PROMPT_LIMIT_MAX, recent_limit),
|
||
)
|
||
return self._build_recent_conversations_message(limit=recent_limit) or ""
|
||
|
||
recent_conversations_prompt = self._get_or_init_frozen_prompt(
|
||
"frozen_recent_conversations_prompt",
|
||
_build_recent_conversations_prompt,
|
||
)
|
||
if recent_conversations_prompt:
|
||
messages.append({"role": "system", "content": recent_conversations_prompt})
|
||
|
||
# 个性化配置
|
||
def _build_personalization_system_prompt() -> str:
|
||
personalization_block = build_personalization_prompt(personalization_config, include_header=False)
|
||
if not personalization_block:
|
||
return ""
|
||
personalization_template = self.load_prompt("personalization").strip()
|
||
if personalization_template and "{personalization_block}" in personalization_template:
|
||
return personalization_template.format(personalization_block=personalization_block)
|
||
if personalization_template:
|
||
return f"{personalization_template}\n{personalization_block}"
|
||
return personalization_block
|
||
|
||
personalization_text = self._get_or_init_frozen_prompt(
|
||
"frozen_personalization_prompt",
|
||
_build_personalization_system_prompt,
|
||
)
|
||
if personalization_text:
|
||
messages.append({"role": "system", "content": personalization_text})
|
||
|
||
# 工作区信息
|
||
workspace_system = self._get_or_init_frozen_prompt(
|
||
"frozen_workspace_prompt",
|
||
lambda: self.context_manager._build_workspace_system_message(context) or "",
|
||
)
|
||
if workspace_system:
|
||
messages.append({"role": "system", "content": workspace_system})
|
||
|
||
# AGENTS.md
|
||
def _build_agents_md_prompt() -> str:
|
||
agents_md_inject_enabled = bool(personalization_config.get("agents_md_auto_inject", False)) if isinstance(personalization_config, dict) else False
|
||
if not agents_md_inject_enabled:
|
||
return ""
|
||
agents_md_content = self._load_agents_md_content()
|
||
if not agents_md_content:
|
||
return ""
|
||
agents_md_template = self.load_prompt("agents_md_inject").strip()
|
||
if agents_md_template and "{{AGENTS_MD_CONTENT}}" in agents_md_template:
|
||
return agents_md_template.replace("{{AGENTS_MD_CONTENT}}", agents_md_content)
|
||
return f"【AGENTS.md 项目规范】\n\n{agents_md_content}\n\n---\n请注意：以上规范来自工作区根目录的 AGENTS.md 文件，若有冲突请以 AGENTS.md 为准。"
|
||
|
||
agents_md_text = self._get_or_init_frozen_prompt(
|
||
"frozen_agents_md_prompt",
|
||
_build_agents_md_prompt,
|
||
)
|
||
if agents_md_text:
|
||
messages.append({"role": "system", "content": agents_md_text})
|
||
|
||
# skills 列表
|
||
skills_catalog = get_skills_catalog(private_dir=infer_private_skills_dir(self.data_dir))
|
||
enabled_skills = merge_enabled_skills(
|
||
personalization_config.get("enabled_skills") if isinstance(personalization_config, dict) else None,
|
||
skills_catalog,
|
||
personalization_config.get("skills_catalog_snapshot") if isinstance(personalization_config, dict) else None,
|
||
)
|
||
def _build_skills_system_prompt() -> str:
|
||
skills_template = self.load_prompt("skills_system").strip()
|
||
skills_list = build_skills_list(skills_catalog, enabled_skills)
|
||
return build_skills_prompt(skills_template, skills_list) or ""
|
||
|
||
skills_prompt = self._get_or_init_frozen_prompt(
|
||
"frozen_skills_prompt",
|
||
_build_skills_system_prompt,
|
||
)
|
||
if skills_prompt:
|
||
messages.append({"role": "system", "content": skills_prompt})
|
||
|
||
# 记忆系统（总体长期记忆 + 项目记忆）
|
||
def _build_memory_system_prompt() -> str:
|
||
return self._build_memory_system_content()
|
||
|
||
memory_prompt = self._get_or_init_frozen_prompt(
|
||
"frozen_memory_prompt",
|
||
_build_memory_system_prompt,
|
||
)
|
||
if memory_prompt:
|
||
messages.append({"role": "system", "content": memory_prompt})
|
||
|
||
# API 自定义 system prompt
|
||
custom_system_prompt = self._get_or_init_frozen_prompt(
|
||
"frozen_custom_system_prompt",
|
||
lambda: (
|
||
getattr(self.context_manager, "custom_system_prompt", "").strip()
|
||
if isinstance(getattr(self.context_manager, "custom_system_prompt", None), str)
|
||
else ""
|
||
),
|
||
)
|
||
if custom_system_prompt:
|
||
messages.append({"role": "system", "content": custom_system_prompt})
|
||
|
||
# 禁用工具提示
|
||
disabled_notice = self._get_or_init_frozen_prompt(
|
||
"frozen_disabled_tools_prompt",
|
||
lambda: self._format_disabled_tool_notice() or "",
|
||
)
|
||
if disabled_notice:
|
||
messages.append({
|
||
"role": "system",
|
||
"content": disabled_notice
|
||
})
|
||
|
||
# 添加对话历史（保留完整结构，包括tool_calls和tool消息）
|
||
conversation = context["conversation"]
|
||
replaced_tool_count = 0
|
||
deep_compacted_skipped = 0
|
||
for idx, conv in enumerate(conversation):
|
||
metadata = conv.get("metadata") or {}
|
||
# 深压缩：被标记为 deep_compacted 的消息（整段已压缩前缀）原文保留在历史中用于展示，
|
||
# 但构建请求时整体跳过，不纳入上下文。由于按连续前缀整体标记，
|
||
# 不会出现 assistant.tool_calls 与其 tool 响应被拆散导致的配对悬空。
|
||
if metadata.get("deep_compacted"):
|
||
deep_compacted_skipped += 1
|
||
continue
|
||
if conv["role"] == "assistant":
|
||
# Assistant消息可能包含工具调用
|
||
message = {
|
||
"role": conv["role"],
|
||
"content": conv["content"]
|
||
}
|
||
# 对于思考模式（如 DeepSeek thinking），assistant 历史消息中的
|
||
# reasoning_content 即使为空字符串也需要原样回传，否则下一轮可能被
|
||
# API 判定为“未回传 reasoning_content”并返回 400。
|
||
if "reasoning_content" in conv:
|
||
message["reasoning_content"] = conv.get("reasoning_content", "")
|
||
# 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":
|
||
if shallow_replace_enabled and metadata.get("auto_shallow_compacted"):
|
||
messages.append({
|
||
"role": "tool",
|
||
"content": AUTO_SHALLOW_PLACEHOLDER,
|
||
"tool_call_id": conv.get("tool_call_id", ""),
|
||
"name": conv.get("name", "")
|
||
})
|
||
replaced_tool_count += 1
|
||
continue
|
||
# Tool消息需要保留完整结构
|
||
images = conv.get("images") or metadata.get("images") or []
|
||
videos = conv.get("videos") or metadata.get("videos") or []
|
||
media_refs = conv.get("media_refs") or metadata.get("media_refs") or []
|
||
content_value = conv.get("content")
|
||
if isinstance(content_value, list):
|
||
content_payload = content_value
|
||
elif images or videos or media_refs:
|
||
content_payload = self.context_manager._build_content_with_images(
|
||
content_value,
|
||
images,
|
||
videos,
|
||
media_refs=media_refs,
|
||
)
|
||
else:
|
||
content_payload = content_value
|
||
message = {
|
||
"role": "tool",
|
||
"content": content_payload,
|
||
"tool_call_id": conv.get("tool_call_id", ""),
|
||
"name": conv.get("name", "")
|
||
}
|
||
messages.append(message)
|
||
|
||
else:
|
||
# User 或普通 System 消息
|
||
images = conv.get("images") or metadata.get("images") or []
|
||
videos = conv.get("videos") or metadata.get("videos") or []
|
||
media_refs = conv.get("media_refs") or metadata.get("media_refs") or []
|
||
content_payload = (
|
||
self.context_manager._build_content_with_images(
|
||
conv["content"],
|
||
images,
|
||
videos,
|
||
media_refs=media_refs,
|
||
)
|
||
if (images or videos or media_refs) else conv["content"]
|
||
)
|
||
# 调试：记录所有 system 消息
|
||
if conv["role"] == "system":
|
||
logger.info(f"[DEBUG build_messages] 添加 system 消息: content前50字={conv['content'][:50]}")
|
||
messages.append({
|
||
"role": conv["role"],
|
||
"content": content_payload
|
||
})
|
||
|
||
# 当前用户输入已经在conversation中了，不需要重复添加
|
||
if shallow_replace_enabled:
|
||
print(f"[ContextCompression] build_messages 替换tool占位符: {replaced_tool_count} 条")
|
||
if deep_compacted_skipped:
|
||
print(f"[ContextCompression] build_messages 跳过已深压缩消息: {deep_compacted_skipped} 条")
|
||
return messages
|
||
|
||
def _load_agents_md_content(self) -> Optional[str]:
|
||
"""加载工作区根目录的 AGENTS.md 文件内容。
|
||
|
||
如果存在多个 AGENTS.md 文件，返回最新更新的那一个。
|
||
"""
|
||
try:
|
||
project_path = Path(self.project_path)
|
||
if not project_path.exists():
|
||
return None
|
||
|
||
# 查找所有 AGENTS.md 文件
|
||
agents_md_files = list(project_path.rglob("AGENTS.md"))
|
||
if not agents_md_files:
|
||
return None
|
||
|
||
# 找到最新更新的文件
|
||
latest_file = max(agents_md_files, key=lambda p: p.stat().st_mtime)
|
||
|
||
# 读取文件内容
|
||
content = latest_file.read_text(encoding='utf-8')
|
||
return content.strip() if content else None
|
||
except Exception as exc:
|
||
logger.warning(f"[AGENTS.md] 读取失败: {exc}")
|
||
return None
|
||
|
||
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。"
|