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@@ -1,32 +1,28 @@
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"""
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-浏览器调研示例 (支持云浏览器/本地浏览器切换)
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-
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-功能：
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-1. Agent 模式自动化调研
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-2. 手动接管：随时按 [Enter] 键暂停 Agent 并手动操作浏览器
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-3. 自动清理：无论成功或崩溃，均安全关闭浏览器进程
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-4. 灵活切换：通过配置变量选择云浏览器或本地浏览器
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-
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-浏览器模式配置：
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-- 修改下方 BROWSER_TYPE 变量来切换模式
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-- "cloud": 云浏览器模式，不占用本地资源，需要配置 browser-use 云服务
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-- "local": 本地浏览器模式，在本地运行 Chrome，速度更快，支持可视化调试
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-"""
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+示例（增强版）
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+
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+使用 Agent 模式 + Skills
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-# ===== 浏览器模式配置 =====
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-# 可选值: "cloud" (云浏览器) 或 "local" (本地浏览器)
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-BROWSER_TYPE = "cloud" # 修改这里来切换浏览器模式
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-HEADLESS = False # 是否无头模式运行
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+新增功能：
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+1. 支持命令行随时打断（输入 'p' 暂停，'q' 退出）
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+2. 暂停后可插入干预消息
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+3. 支持触发经验总结
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+4. 查看当前 GoalTree
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+5. 框架层自动清理不完整的工具调用
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+6. 支持通过 --trace <ID> 恢复已有 Trace 继续执行
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+"""
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+import argparse
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import os
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import sys
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+import select
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import asyncio
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-import logging
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-import re
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-import uuid
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from pathlib import Path
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-from datetime import datetime
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-from argparse import Namespace
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+
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+# Clash Verge TUN 模式兼容：禁止 httpx/urllib 自动检测系统 HTTP 代理
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+# TUN 虚拟网卡已在网络层接管所有流量，不需要应用层再走 HTTP 代理，
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+# 否则 httpx 检测到 macOS 系统代理 (127.0.0.1:7897) 会导致 ConnectError
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+os.environ.setdefault("no_proxy", "*")
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# 添加项目根目录到 Python 路径
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sys.path.insert(0, str(Path(__file__).parent.parent.parent))
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@@ -34,176 +30,581 @@ sys.path.insert(0, str(Path(__file__).parent.parent.parent))
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from dotenv import load_dotenv
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load_dotenv()
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-# --- 日志配置 ---
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-logging.basicConfig(level=logging.WARNING)
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-logging.getLogger("agent.core.message_manager").setLevel(logging.INFO)
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-logging.getLogger("tools").setLevel(logging.INFO)
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-
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from agent.llm.prompts import SimplePrompt
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from agent.core.runner import AgentRunner, RunConfig
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-from agent.trace import FileSystemTraceStore, Trace, Message
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+from agent.core.presets import AgentPreset, register_preset
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+from agent.trace import (
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+ FileSystemTraceStore,
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+ Trace,
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+ Message,
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+)
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from agent.llm import create_openrouter_llm_call
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-from agent.tools.builtin.browser.baseClass import kill_browser_session, init_browser_session
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+from agent.tools import get_tool_registry
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+
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+
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+# ===== 非阻塞 stdin 检测 =====
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+if sys.platform == 'win32':
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+ import msvcrt
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+
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+def check_stdin() -> str | None:
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+ """
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+ 跨平台非阻塞检查 stdin 输入。
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+ Windows: 使用 msvcrt.kbhit()
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+ macOS/Linux: 使用 select.select()
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+ """
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+ if sys.platform == 'win32':
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+ # 检查是否有按键按下
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+ if msvcrt.kbhit():
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+ # 读取按下的字符（msvcrt.getwch 是非阻塞读取宽字符）
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+ ch = msvcrt.getwch().lower()
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+ if ch == 'p':
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+ return 'pause'
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+ if ch == 'q':
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+ return 'quit'
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+ # 如果是其他按键，可以选择消耗掉或者忽略
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+ return None
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+ else:
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+ # Unix/Mac 逻辑
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+ ready, _, _ = select.select([sys.stdin], [], [], 0)
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+ if ready:
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+ line = sys.stdin.readline().strip().lower()
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+ if line in ('p', 'pause'):
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+ return 'pause'
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+ if line in ('q', 'quit'):
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+ return 'quit'
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+ return None
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+
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+
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+# ===== 交互菜单 =====
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+
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+def _read_multiline() -> str:
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+ """
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+ 读取多行输入，以连续两次回车（空行）结束。
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+
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+ 单次回车只是换行，不会提前终止输入。
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+ """
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+ print("\n请输入干预消息（连续输入两次回车结束）：")
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+ lines: list[str] = []
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+ blank_count = 0
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+ while True:
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+ line = input()
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+ if line == "":
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+ blank_count += 1
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+ if blank_count >= 2:
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+ break
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+ lines.append("") # 保留单个空行
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+ else:
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+ blank_count = 0
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+ lines.append(line)
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+
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+ # 去掉尾部多余空行
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+ while lines and lines[-1] == "":
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+ lines.pop()
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+ return "\n".join(lines)
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-# ===== 全局交互控制 =====
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-pause_event = asyncio.Event()
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-async def listen_for_interrupt():
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- """后台协程：监听标准输入，按下回车即触发暂停"""
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+async def show_interactive_menu(
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+ runner: AgentRunner,
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+ trace_id: str,
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+ current_sequence: int,
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+ store: FileSystemTraceStore,
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+):
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+ """
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+ 显示交互式菜单，让用户选择操作。
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+
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+ 进入本函数前不再有后台线程占用 stdin，所以 input() 能正常工作。
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+ """
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+ print("\n" + "=" * 60)
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+ print(" 执行已暂停")
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+ print("=" * 60)
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+ print("请选择操作：")
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+ print(" 1. 插入干预消息并继续")
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+ print(" 2. 触发经验总结（reflect）")
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+ print(" 3. 查看当前 GoalTree")
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+ print(" 4. 手动压缩上下文（compact）")
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+ print(" 5. 继续执行")
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+ print(" 6. 停止执行")
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+ print("=" * 60)
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+
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while True:
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- # 在执行器中运行同步的 readline，避免阻塞事件循环
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- await asyncio.get_event_loop().run_in_executor(None, sys.stdin.readline)
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- if not pause_event.is_set():
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- print("\n" + "!" * 40)
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- print("🛑 检测到手动干预请求！")
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- print("Agent 将在完成当前动作后暂停，请准备接管浏览器。")
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- print("!" * 40 + "\n")
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- pause_event.set()
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+ choice = input("请输入选项 (1-6): ").strip()
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+
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+ if choice == "1":
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+ text = _read_multiline()
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+ if not text:
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+ print("未输入任何内容，取消操作")
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+ continue
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+
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+ print(f"\n将插入干预消息并继续执行...")
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+ # 从 store 读取实际的 last_sequence，避免本地 current_sequence 过时
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+ live_trace = await store.get_trace(trace_id)
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+ actual_sequence = live_trace.last_sequence if live_trace and live_trace.last_sequence else current_sequence
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+ return {
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+ "action": "continue",
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+ "messages": [{"role": "user", "content": text}],
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+ "after_sequence": actual_sequence,
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+ }
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+
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+ elif choice == "2":
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+ # 触发经验总结
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+ print("\n触发经验总结...")
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+ focus = input("请输入反思重点（可选，直接回车跳过）: ").strip()
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+
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+ # 触发反思
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+ await perform_reflection(runner, store, trace_id, focus=focus)
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+ continue
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-# ===== 核心逻辑 =====
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+ elif choice == "3":
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+ goal_tree = await store.get_goal_tree(trace_id)
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+ if goal_tree and goal_tree.goals:
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+ print("\n当前 GoalTree:")
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+ print(goal_tree.to_prompt())
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+ else:
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+ print("\n当前没有 Goal")
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+ continue
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+
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+ elif choice == "4":
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+ # 手动压缩上下文
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+ print("\n正在执行上下文压缩（compact）...")
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+ try:
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+ goal_tree = await store.get_goal_tree(trace_id)
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+ trace = await store.get_trace(trace_id)
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+ if not trace:
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+ print("未找到 Trace，无法压缩")
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+ continue
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+
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+ # 重建当前 history
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+ main_path = await store.get_main_path_messages(trace_id, trace.head_sequence)
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+ history = [msg.to_llm_dict() for msg in main_path]
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+ head_seq = main_path[-1].sequence if main_path else 0
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+ next_seq = head_seq + 1
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+
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+ compact_config = RunConfig(trace_id=trace_id)
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+ new_history, new_head, new_seq = await runner._compress_history(
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+ trace_id=trace_id,
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+ history=history,
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+ goal_tree=goal_tree,
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+ config=compact_config,
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+ sequence=next_seq,
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+ head_seq=head_seq,
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+ )
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+ print(f"\n✅ 压缩完成: {len(history)} 条消息 → {len(new_history)} 条")
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+ except Exception as e:
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+ print(f"\n❌ 压缩失败: {e}")
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+ continue
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+
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+ elif choice == "5":
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+ print("\n继续执行...")
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+ return {"action": "continue"}
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+
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+ elif choice == "6":
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+ print("\n停止执行...")
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+ return {"action": "stop"}
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+
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+ else:
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+ print("无效选项，请重新输入")
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+
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+async def perform_reflection(runner: AgentRunner, store: FileSystemTraceStore, trace_id: str, focus: str = ""):
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+ """执行经验总结并保存（带结构化 YAML 解析）"""
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+ from agent.trace.compaction import build_reflect_prompt
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+ import re as _re2
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+ import uuid as _uuid2
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+ from datetime import datetime
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+
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+ trace = await store.get_trace(trace_id)
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+ if not trace:
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+ return
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+ saved_head = trace.head_sequence
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+
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+ prompt = build_reflect_prompt()
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+ if focus:
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+ prompt += f"\n\n请特别关注：{focus}"
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+
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+ print("正在生成反思...")
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+ reflect_cfg = RunConfig(trace_id=trace_id, max_iterations=1, tools=[])
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+ reflection_text = ""
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+
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+ try:
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+ result = await runner.run_result(
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+ messages=[{"role": "user", "content": prompt}],
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+ config=reflect_cfg,
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+ )
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+ reflection_text = result.get("summary", "")
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+ finally:
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+ # 恢复 head_sequence（反思消息成为侧枝，不污染主对话）
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+ await store.update_trace(trace_id, head_sequence=saved_head)
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+
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+ # 追加到 experiences 文件
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+ if reflection_text:
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+ experiences_path = runner.experiences_path or "./.cache/experiences_how.md"
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+ os.makedirs(os.path.dirname(experiences_path), exist_ok=True)
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+
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+ pattern = r"-\s*\[(?P<tags>.*?)\]\s*(?P<content>.*)"
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+ matches = list(_re2.finditer(pattern, reflection_text))
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+
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+ structured_entries = []
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+ for match in matches:
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+ tags_str = match.group("tags")
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+ content = match.group("content")
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+
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+ intent_match = _re2.search(r"intent:\s*(.*?)(?:,|$)", tags_str, _re2.IGNORECASE)
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+ state_match = _re2.search(r"state:\s*(.*?)(?:,|$)", tags_str, _re2.IGNORECASE)
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+
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+ intents = [i.strip() for i in intent_match.group(1).split(",")] if intent_match and intent_match.group(1) else []
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+ states = [s.strip() for s in state_match.group(1).split(",")] if state_match and state_match.group(1) else []
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+
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+ ex_id = f"ex_{datetime.now().strftime('%m%d%H%M')}_{_uuid2.uuid4().hex[:4]}"
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+
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+ entry = f"---\nid: {ex_id}\ntrace_id: {trace_id}\ntags: {{intent: {intents}, state: {states}}}\nmetrics: {{helpful: 1, harmful: 0}}\ncreated_at: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n---\n- {content}\n- 经验ID: [{ex_id}]"
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+ structured_entries.append(entry)
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+
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+ if structured_entries:
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+ final_output = "\n\n" + "\n\n".join(structured_entries)
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+ with open(experiences_path, "a", encoding="utf-8") as f:
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+ f.write(final_output)
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+ print(f"\n✅ 提取了 {len(structured_entries)} 条经验，已结构化并保存到: {experiences_path}")
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+ print("\n--- 反思内容（结构化后） ---")
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+ print(final_output.strip())
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+ print("--- 结束 ---\n")
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+ else:
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+ print("\n⚠️ 未能解析出符合格式的经验条目，已保存原始纯文本以供检查。")
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+ header = f"\n\n---\n\n## [Raw] {trace_id} ({datetime.now().strftime('%Y-%m-%d %H:%M')})\n\n"
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+ with open(experiences_path, "a", encoding="utf-8") as f:
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+ f.write(header + reflection_text + "\n")
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+ print(reflection_text)
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+ else:
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+ print("未生成反思内容")
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async def main():
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- # 1. 环境准备
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+ # 解析命令行参数
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+ parser = argparse.ArgumentParser(description="任务 (Agent 模式 + 交互增强)")
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+ parser.add_argument(
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+ "--trace", type=str, default=None,
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+ help="已有的 Trace ID，用于恢复继续执行（不指定则新建）",
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+ )
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+ args = parser.parse_args()
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+
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+ # 路径配置
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base_dir = Path(__file__).parent
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project_root = base_dir.parent.parent
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- trace_dir = project_root / ".trace"
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- prompt_path = base_dir / "test.prompt"
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- output_dir = base_dir / "output"
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+ prompt_path = base_dir / "research.prompt"
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+ output_dir = base_dir / "output_1"
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output_dir.mkdir(exist_ok=True)
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+ # 加载项目级 presets（examples/how/presets.json）
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+ presets_path = base_dir / "presets.json"
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+ if presets_path.exists():
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+ import json
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|
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+ with open(presets_path, "r", encoding="utf-8") as f:
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+ project_presets = json.load(f)
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+ for name, cfg in project_presets.items():
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+ register_preset(name, AgentPreset(**cfg))
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+ print(f" - 已加载项目 presets: {list(project_presets.keys())}")
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+
|
|
|
+ # Skills 目录（可选：用户自定义 skills）
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|
|
+ # 注意：内置 skills（agent/memory/skills/）会自动加载
|
|
|
+ skills_dir = str(base_dir / "skills")
|
|
|
+
|
|
|
print("=" * 60)
|
|
|
- print("🚀 交互式浏览器调研 Agent")
|
|
|
- print(f"🌐 浏览器模式: {'云浏览器 (Cloud)' if BROWSER_TYPE == 'cloud' else '本地浏览器 (Local)'}")
|
|
|
- print("👉 操作指南：")
|
|
|
- print(" - 运行中随时按下 [Enter] 键进入手动接管模式")
|
|
|
- print(" - 在浏览器完成操作后，点击页面上的 'Done' 或回车返回")
|
|
|
- print("=" * 60 + "\n")
|
|
|
-
|
|
|
- # 2. 加载任务
|
|
|
+ print("mcp/skills 发现、获取、评价 分析任务 (Agent 模式 + 交互增强)")
|
|
|
+ print("=" * 60)
|
|
|
+ print()
|
|
|
+ print("💡 交互提示：")
|
|
|
+ print(" - 执行过程中输入 'p' 或 'pause' 暂停并进入交互模式")
|
|
|
+ print(" - 执行过程中输入 'q' 或 'quit' 停止执行")
|
|
|
+ print("=" * 60)
|
|
|
+ print()
|
|
|
+
|
|
|
+ # 1. 加载 prompt
|
|
|
+ print("1. 加载 prompt 配置...")
|
|
|
prompt = SimplePrompt(prompt_path)
|
|
|
- system_prompt = prompt._messages.get("system", "")
|
|
|
- user_task = prompt._messages.get("user", "")
|
|
|
- # 默认使用 cheap 模型进行调研，如 gemini-3-flash-preview
|
|
|
- model_name = prompt.config.get('model', 'gemini-3-flash-preview')
|
|
|
- temperature = float(prompt.config.get('temperature', 0.3))
|
|
|
|
|
|
+ # 2. 构建消息（仅新建时使用，恢复时消息已在 trace 中）
|
|
|
+ print("2. 构建任务消息...")
|
|
|
messages = prompt.build_messages()
|
|
|
|
|
|
- # 3. 初始化浏览器会话
|
|
|
- browser_mode_name = "云浏览器" if BROWSER_TYPE == "cloud" else "本地浏览器"
|
|
|
- print(f"🌐 正在初始化{browser_mode_name}...")
|
|
|
- await init_browser_session(
|
|
|
- browser_type=BROWSER_TYPE,
|
|
|
- headless=HEADLESS,
|
|
|
- url="about:blank"
|
|
|
- )
|
|
|
- print(f"✅ {browser_mode_name}初始化完成\n")
|
|
|
+ # 3. 创建 Agent Runner（配置 skills）
|
|
|
+ print("3. 创建 Agent Runner...")
|
|
|
+ print(f" - Skills 目录: {skills_dir}")
|
|
|
+ print(f" - 模型: {prompt.config.get('model', 'sonnet-4.5')}")
|
|
|
+
|
|
|
+ # 加载自定义工具
|
|
|
+ print(" - 加载自定义工具: nanobanana")
|
|
|
+ import examples.how.tool # 导入自定义工具模块，触发 @tool 装饰器注册
|
|
|
|
|
|
- # 4. 初始化 Runner
|
|
|
- # 注意：确保你的 openrouter 配置正确
|
|
|
+ store = FileSystemTraceStore(base_path=".trace")
|
|
|
runner = AgentRunner(
|
|
|
- trace_store=FileSystemTraceStore(base_path=str(trace_dir)),
|
|
|
- llm_call=create_openrouter_llm_call(model=f"google/{model_name}"),
|
|
|
- skills_dir=None,
|
|
|
+ trace_store=store,
|
|
|
+ llm_call=create_openrouter_llm_call(model=f"anthropic/claude-{prompt.config.get('model', 'sonnet-4.5')}"),
|
|
|
+ skills_dir=skills_dir,
|
|
|
+ experiences_path="./.cache/experiences_how.md",
|
|
|
debug=True
|
|
|
)
|
|
|
|
|
|
- # 5. 启动监听任务
|
|
|
- interrupt_task = asyncio.create_task(listen_for_interrupt())
|
|
|
-
|
|
|
+ # 4. 判断是新建还是恢复
|
|
|
+ resume_trace_id = args.trace
|
|
|
+ if resume_trace_id:
|
|
|
+ # 验证 trace 存在
|
|
|
+ existing_trace = await store.get_trace(resume_trace_id)
|
|
|
+ if not existing_trace:
|
|
|
+ print(f"\n错误: Trace 不存在: {resume_trace_id}")
|
|
|
+ sys.exit(1)
|
|
|
+ print(f"4. 恢复已有 Trace: {resume_trace_id[:8]}...")
|
|
|
+ print(f" - 状态: {existing_trace.status}")
|
|
|
+ print(f" - 消息数: {existing_trace.total_messages}")
|
|
|
+ print(f" - 任务: {existing_trace.task}")
|
|
|
+ else:
|
|
|
+ print(f"4. 启动新 Agent 模式...")
|
|
|
+
|
|
|
+ print()
|
|
|
+
|
|
|
final_response = ""
|
|
|
- current_trace_id = None
|
|
|
+ current_trace_id = resume_trace_id
|
|
|
+ current_sequence = 0
|
|
|
+ should_exit = False
|
|
|
|
|
|
try:
|
|
|
- # 启动 Agent 迭代
|
|
|
- agent_stream = runner.run(
|
|
|
- messages=messages,
|
|
|
- config=RunConfig(
|
|
|
- system_prompt=system_prompt,
|
|
|
- model=f"google/{model_name}",
|
|
|
- temperature=temperature,
|
|
|
- max_iterations=30,
|
|
|
- name=user_task[:50],
|
|
|
- ),
|
|
|
- )
|
|
|
+ # 恢复模式：不发送初始消息，只指定 trace_id 续跑
|
|
|
+ if resume_trace_id:
|
|
|
+ initial_messages = None # None = 未设置，触发早期菜单检查
|
|
|
+ config = RunConfig(
|
|
|
+ model=f"claude-{prompt.config.get('model', 'sonnet-4.5')}",
|
|
|
+ temperature=float(prompt.config.get('temperature', 0.3)),
|
|
|
+ max_iterations=1000,
|
|
|
+ trace_id=resume_trace_id,
|
|
|
+ )
|
|
|
+ else:
|
|
|
+ initial_messages = messages
|
|
|
+ config = RunConfig(
|
|
|
+ model=f"claude-{prompt.config.get('model', 'sonnet-4.5')}",
|
|
|
+ temperature=float(prompt.config.get('temperature', 0.3)),
|
|
|
+ max_iterations=1000,
|
|
|
+ name="调研：openclaw在企业中的应用有哪些方案和经验？如何实现组织层面的知识共享？",
|
|
|
+ )
|
|
|
+
|
|
|
+ while not should_exit:
|
|
|
+ # 如果是续跑，需要指定 trace_id
|
|
|
+ if current_trace_id:
|
|
|
+ config.trace_id = current_trace_id
|
|
|
+
|
|
|
+ # 清理上一轮的响应，避免失败后显示旧内容
|
|
|
+ final_response = ""
|
|
|
|
|
|
- async for item in agent_stream:
|
|
|
- # --- 检查手动暂停信号 ---
|
|
|
- if pause_event.is_set():
|
|
|
- print("\n" + "🛠️" * 20)
|
|
|
- print(">>> 人工接管模式激活 <<<")
|
|
|
- print("1. 请在浏览器窗口进行必要操作（登录、过验证码等）")
|
|
|
- print("2. 操作完成后，请在终端按 [Enter] 或在页面点击交互按钮继续")
|
|
|
-
|
|
|
- try:
|
|
|
- # 调用内置的等待交互工具
|
|
|
- await runner.tools.execute(
|
|
|
- "browser_wait_for_user_action",
|
|
|
- {"message": "人工干预中，请完成操作后恢复 Agent"},
|
|
|
- uid="human_admin",
|
|
|
- context={"runner": runner}
|
|
|
+ # 如果 trace 已完成/失败且没有新消息，直接进入交互菜单
|
|
|
+ # 注意：initial_messages 为 None 表示未设置（首次加载），[] 表示有意为空（用户选择"继续"）
|
|
|
+ if current_trace_id and initial_messages is None:
|
|
|
+ check_trace = await store.get_trace(current_trace_id)
|
|
|
+ if check_trace and check_trace.status in ("completed", "failed"):
|
|
|
+ if check_trace.status == "completed":
|
|
|
+ print(f"\n[Trace] ✅ 已完成")
|
|
|
+ print(f" - Total messages: {check_trace.total_messages}")
|
|
|
+ print(f" - Total cost: ${check_trace.total_cost:.4f}")
|
|
|
+ else:
|
|
|
+ print(f"\n[Trace] ❌ 已失败: {check_trace.error_message}")
|
|
|
+ current_sequence = check_trace.head_sequence
|
|
|
+
|
|
|
+ menu_result = await show_interactive_menu(
|
|
|
+ runner, current_trace_id, current_sequence, store
|
|
|
)
|
|
|
- except Exception as e:
|
|
|
- print(f"⚠️ 交互工具调用失败: {e}")
|
|
|
-
|
|
|
- print(">>> 交互结束，交还控制权给 Agent <<<")
|
|
|
- print("🛠️" * 20 + "\n")
|
|
|
- pause_event.clear()
|
|
|
-
|
|
|
- # --- 正常处理 Agent 消息输出 ---
|
|
|
- if isinstance(item, Trace):
|
|
|
- current_trace_id = item.trace_id
|
|
|
- if item.status == "running":
|
|
|
- print(f"[{datetime.now().strftime('%H:%M:%S')}] 🛰️ Trace 启动: {item.trace_id[:8]}")
|
|
|
- elif item.status == "completed":
|
|
|
- print(f"\n✅ 任务圆满完成！Cost: ${item.total_cost:.4f}")
|
|
|
-
|
|
|
- elif isinstance(item, Message):
|
|
|
- if item.role == "assistant":
|
|
|
- content = item.content
|
|
|
- if isinstance(content, dict):
|
|
|
- text = content.get("text", "")
|
|
|
- tool_calls = content.get("tool_calls")
|
|
|
- if text:
|
|
|
- # 打印摘要，带点 Wit
|
|
|
- print(f"\n🤖 Agent: {text[:200]}..." if len(text) > 200 else f"\n🤖 Agent: {text}")
|
|
|
- if tool_calls:
|
|
|
- for tc in tool_calls:
|
|
|
- t_name = tc.get("function", {}).get("name", "unknown")
|
|
|
- print(f" 🛠️ 执行工具: {t_name}")
|
|
|
-
|
|
|
- elif item.role == "tool":
|
|
|
- t_content = item.content
|
|
|
- if isinstance(t_content, dict):
|
|
|
- t_name = t_content.get("tool_name", "unknown")
|
|
|
- print(f" ✅ 工具返回: {t_name}")
|
|
|
-
|
|
|
- except Exception as e:
|
|
|
- print(f"\n🔥 发生严重错误: {e}")
|
|
|
- import traceback
|
|
|
- traceback.print_exc()
|
|
|
|
|
|
- finally:
|
|
|
- # 停止监听协程
|
|
|
- interrupt_task.cancel()
|
|
|
-
|
|
|
- # 6. 强制清理浏览器环境
|
|
|
- print("\n" + "·" * 40)
|
|
|
- print("🧹 正在执行环境清理...")
|
|
|
- try:
|
|
|
- await kill_browser_session()
|
|
|
- print(f"✨ {browser_mode_name}进程已安全终止。")
|
|
|
- except Exception as err:
|
|
|
- print(f"❌ 清理失败: {err}")
|
|
|
- print("·" * 40 + "\n")
|
|
|
-
|
|
|
- # 7. 结果展示
|
|
|
+ if menu_result["action"] == "stop":
|
|
|
+ break
|
|
|
+ elif menu_result["action"] == "continue":
|
|
|
+ new_messages = menu_result.get("messages", [])
|
|
|
+ if new_messages:
|
|
|
+ initial_messages = new_messages
|
|
|
+ config.after_sequence = menu_result.get("after_sequence")
|
|
|
+ else:
|
|
|
+ # 无新消息：对 failed trace 意味着重试，对 completed 意味着继续
|
|
|
+ initial_messages = []
|
|
|
+ config.after_sequence = None
|
|
|
+ continue
|
|
|
+ break
|
|
|
+
|
|
|
+ # 对 stopped/running 等非终态的 trace，直接续跑
|
|
|
+ initial_messages = []
|
|
|
+
|
|
|
+ print(f"{'▶️ 开始执行...' if not current_trace_id else '▶️ 继续执行...'}")
|
|
|
+
|
|
|
+ # 执行 Agent
|
|
|
+ paused = False
|
|
|
+ try:
|
|
|
+ async for item in runner.run(messages=initial_messages, config=config):
|
|
|
+ # 检查用户中断
|
|
|
+ cmd = check_stdin()
|
|
|
+ if cmd == 'pause':
|
|
|
+ # 暂停执行
|
|
|
+ print("\n⏸️ 正在暂停执行...")
|
|
|
+ if current_trace_id:
|
|
|
+ await runner.stop(current_trace_id)
|
|
|
+
|
|
|
+ # 等待一小段时间让 runner 处理 stop 信号
|
|
|
+ await asyncio.sleep(0.5)
|
|
|
+
|
|
|
+ # 显示交互菜单
|
|
|
+ menu_result = await show_interactive_menu(
|
|
|
+ runner, current_trace_id, current_sequence, store
|
|
|
+ )
|
|
|
+
|
|
|
+ if menu_result["action"] == "stop":
|
|
|
+ should_exit = True
|
|
|
+ paused = True
|
|
|
+ break
|
|
|
+ elif menu_result["action"] == "continue":
|
|
|
+ # 检查是否有新消息需要插入
|
|
|
+ new_messages = menu_result.get("messages", [])
|
|
|
+ if new_messages:
|
|
|
+ # 有干预消息，需要重新启动循环
|
|
|
+ initial_messages = new_messages
|
|
|
+ after_seq = menu_result.get("after_sequence")
|
|
|
+ if after_seq is not None:
|
|
|
+ config.after_sequence = after_seq
|
|
|
+ paused = True
|
|
|
+ break
|
|
|
+ else:
|
|
|
+ # 没有新消息，需要重启执行
|
|
|
+ initial_messages = []
|
|
|
+ config.after_sequence = None
|
|
|
+ paused = True
|
|
|
+ break
|
|
|
+
|
|
|
+ elif cmd == 'quit':
|
|
|
+ print("\n🛑 用户请求停止...")
|
|
|
+ if current_trace_id:
|
|
|
+ await runner.stop(current_trace_id)
|
|
|
+ should_exit = True
|
|
|
+ break
|
|
|
+
|
|
|
+ # 处理 Trace 对象（整体状态变化）
|
|
|
+ if isinstance(item, Trace):
|
|
|
+ current_trace_id = item.trace_id
|
|
|
+ if item.status == "running":
|
|
|
+ print(f"[Trace] 开始: {item.trace_id[:8]}...")
|
|
|
+ elif item.status == "completed":
|
|
|
+ print(f"\n[Trace] ✅ 完成")
|
|
|
+ print(f" - Total messages: {item.total_messages}")
|
|
|
+ print(f" - Total tokens: {item.total_tokens}")
|
|
|
+ print(f" - Total cost: ${item.total_cost:.4f}")
|
|
|
+ elif item.status == "failed":
|
|
|
+ print(f"\n[Trace] ❌ 失败: {item.error_message}")
|
|
|
+ elif item.status == "stopped":
|
|
|
+ print(f"\n[Trace] ⏸️ 已停止")
|
|
|
+
|
|
|
+ # 处理 Message 对象（执行过程）
|
|
|
+ elif isinstance(item, Message):
|
|
|
+ current_sequence = item.sequence
|
|
|
+
|
|
|
+ if item.role == "assistant":
|
|
|
+ content = item.content
|
|
|
+ if isinstance(content, dict):
|
|
|
+ text = content.get("text", "")
|
|
|
+ tool_calls = content.get("tool_calls")
|
|
|
+
|
|
|
+ if text and not tool_calls:
|
|
|
+ # 纯文本回复（最终响应）
|
|
|
+ final_response = text
|
|
|
+ print(f"\n[Response] Agent 回复：")
|
|
|
+ print(text)
|
|
|
+ elif text:
|
|
|
+ preview = text[:150] + "..." if len(text) > 150 else text
|
|
|
+ print(f"[Assistant] {preview}")
|
|
|
+
|
|
|
+ if tool_calls:
|
|
|
+ for tc in tool_calls:
|
|
|
+ tool_name = tc.get("function", {}).get("name", "unknown")
|
|
|
+ print(f"[Tool Call] 🛠️ {tool_name}")
|
|
|
+
|
|
|
+ elif item.role == "tool":
|
|
|
+ content = item.content
|
|
|
+ if isinstance(content, dict):
|
|
|
+ tool_name = content.get("tool_name", "unknown")
|
|
|
+ print(f"[Tool Result] ✅ {tool_name}")
|
|
|
+ if item.description:
|
|
|
+ desc = item.description[:80] if len(item.description) > 80 else item.description
|
|
|
+ print(f" {desc}...")
|
|
|
+
|
|
|
+ except Exception as e:
|
|
|
+ print(f"\n执行出错: {e}")
|
|
|
+ import traceback
|
|
|
+ traceback.print_exc()
|
|
|
+
|
|
|
+ # paused → 菜单已在暂停时内联显示过
|
|
|
+ if paused:
|
|
|
+ if should_exit:
|
|
|
+ break
|
|
|
+ continue
|
|
|
+
|
|
|
+ # quit → 直接退出
|
|
|
+ if should_exit:
|
|
|
+ break
|
|
|
+
|
|
|
+ # Runner 退出（完成/失败/停止/异常）→ 显示交互菜单
|
|
|
+ if current_trace_id:
|
|
|
+ # 🌟 新增：自动触发反思的生命周期钩子
|
|
|
+ check_trace = await store.get_trace(current_trace_id)
|
|
|
+ if check_trace and check_trace.status in ("completed", "failed"):
|
|
|
+ print(f"\n⚙️ 任务已结束 (状态: {check_trace.status})，正在自动触发经验总结...")
|
|
|
+
|
|
|
+ # 如果是失败状态，自动带上针对性的 focus 提示
|
|
|
+ auto_focus = "本次任务执行失败了，请重点反思失败的原因、踩坑点以及未来应如何避免。" if check_trace.status == "failed" else ""
|
|
|
+
|
|
|
+ await perform_reflection(runner, store, current_trace_id, focus=auto_focus)
|
|
|
+
|
|
|
+ # 自动反思结束后，依然弹出菜单，让用户决定是彻底退出(6)还是查看总结(3)
|
|
|
+ menu_result = await show_interactive_menu(
|
|
|
+ runner, current_trace_id, current_sequence, store
|
|
|
+ )
|
|
|
+
|
|
|
+ if menu_result["action"] == "stop":
|
|
|
+ break
|
|
|
+ elif menu_result["action"] == "continue":
|
|
|
+ new_messages = menu_result.get("messages", [])
|
|
|
+ if new_messages:
|
|
|
+ initial_messages = new_messages
|
|
|
+ config.after_sequence = menu_result.get("after_sequence")
|
|
|
+ else:
|
|
|
+ initial_messages = []
|
|
|
+ config.after_sequence = None
|
|
|
+ continue
|
|
|
+ break
|
|
|
+
|
|
|
+ except KeyboardInterrupt:
|
|
|
+ print("\n\n用户中断 (Ctrl+C)")
|
|
|
+ if current_trace_id:
|
|
|
+ await runner.stop(current_trace_id)
|
|
|
+
|
|
|
+ # 6. 输出结果
|
|
|
+ if final_response:
|
|
|
+ print()
|
|
|
+ print("=" * 60)
|
|
|
+ print("Agent 响应:")
|
|
|
+ print("=" * 60)
|
|
|
+ print(final_response)
|
|
|
+ print("=" * 60)
|
|
|
+ print()
|
|
|
+
|
|
|
+ # 7. 保存结果
|
|
|
+ output_file = output_dir / "result.txt"
|
|
|
+ with open(output_file, 'w', encoding='utf-8') as f:
|
|
|
+ f.write(final_response)
|
|
|
+
|
|
|
+ print(f"✓ 结果已保存到: {output_file}")
|
|
|
+ print()
|
|
|
+
|
|
|
+ # 可视化提示
|
|
|
if current_trace_id:
|
|
|
- print(f"🔍 任务 Trace ID: {current_trace_id}")
|
|
|
- print(f"📊 访问可视化面板查看详情。")
|
|
|
+ print("=" * 60)
|
|
|
+ print("可视化 Step Tree:")
|
|
|
+ print("=" * 60)
|
|
|
+ print("1. 启动 API Server:")
|
|
|
+ print(" python3 api_server.py")
|
|
|
+ print()
|
|
|
+ print("2. 浏览器访问:")
|
|
|
+ print(" http://localhost:8000/api/traces")
|
|
|
+ print()
|
|
|
+ print(f"3. Trace ID: {current_trace_id}")
|
|
|
+ print("=" * 60)
|
|
|
+
|
|
|
|
|
|
if __name__ == "__main__":
|
|
|
- try:
|
|
|
- asyncio.run(main())
|
|
|
- except KeyboardInterrupt:
|
|
|
- print("\n👋 收到退出信号，程序已停止。")
|
|
|
+ asyncio.run(main())
|
Talegorithm