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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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+
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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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+
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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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+from pathlib import Path
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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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+
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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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+
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+from dotenv import load_dotenv
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+load_dotenv()
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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.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 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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+
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+
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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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+ 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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+ from agent.trace.compaction import build_reflect_prompt
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+
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+ # 保存当前 head_sequence
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+ trace = await store.get_trace(trace_id)
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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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+
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+ reflection_text = ""
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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）
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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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+ from datetime import datetime
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+ experiences_path = runner.experiences_path or "./.cache/experiences_find.md"
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+ os.makedirs(os.path.dirname(experiences_path), exist_ok=True)
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+ header = f"\n\n---\n\n## {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(f"\n反思已保存到: {experiences_path}")
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+ print("\n--- 反思内容 ---")
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+ print(reflection_text)
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+ print("--- 结束 ---\n")
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+ else:
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+ print("未生成反思内容")
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+
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+ continue
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+
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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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+
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+async def main():
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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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+ prompt_path = base_dir / "production.prompt"
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+
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+ # 为每次运行创建独立的输出目录（基于时间戳或 trace_id）
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+ if args.trace:
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+ # 恢复模式：使用已有 trace_id 作为目录名
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+ output_dir = base_dir / "outputs" / args.trace[:8]
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+ else:
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+ # 新建模式：使用时间戳
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+ from datetime import datetime
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+ timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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+ output_dir = base_dir / "outputs" / timestamp
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+ output_dir.mkdir(parents=True, exist_ok=True)
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+
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+ print(f"📁 输出目录: {output_dir}")
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+ print()
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+
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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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+ 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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+
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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
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+ skills_dir = str(base_dir / "skills")
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+
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+ print("=" * 60)
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+ print("mcp/skills 发现、获取、评价 分析任务 (Agent 模式 + 交互增强)")
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+ print("=" * 60)
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+ print()
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+ print("💡 交互提示：")
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+ print(" - 执行过程中输入 'p' 或 'pause' 暂停并进入交互模式")
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+ print(" - 执行过程中输入 'q' 或 'quit' 停止执行")
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+ print("=" * 60)
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+ print()
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+
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+ # 1. 加载 prompt
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+ print("1. 加载 prompt 配置...")
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+ prompt = SimplePrompt(prompt_path)
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+
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+ # 2. 构建消息（仅新建时使用，恢复时消息已在 trace 中）
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+ print("2. 构建任务消息...")
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+ # 注入输出目录到 prompt 变量
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+ messages = prompt.build_messages(variables={
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+ "output_dir": str(output_dir.relative_to(base_dir))
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+ })
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+
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+ # 3. 创建 Agent Runner（配置 skills）
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+ print("3. 创建 Agent Runner...")
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+ print(f" - Skills 目录: {skills_dir}")
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+ print(f" - 模型: {prompt.config.get('model', 'sonnet-4.5')}")
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+
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+ # 加载自定义工具
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+ print(" - 加载自定义工具: nanobanana")
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+ import examples.how.tool # 导入自定义工具模块，触发 @tool 装饰器注册
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+
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+ store = FileSystemTraceStore(base_path=".trace")
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+ runner = AgentRunner(
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+ trace_store=store,
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+ llm_call=create_openrouter_llm_call(model=f"anthropic/claude-{prompt.config.get('model', 'sonnet-4.5')}"),
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+ skills_dir=skills_dir,
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+ experiences_path="./.cache/experiences_find.md",
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+ debug=True
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+ )
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+
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+ # 4. 判断是新建还是恢复
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+ resume_trace_id = args.trace
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+ if resume_trace_id:
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+ # 验证 trace 存在
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+ existing_trace = await store.get_trace(resume_trace_id)
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+ if not existing_trace:
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+ print(f"\n错误: Trace 不存在: {resume_trace_id}")
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+ sys.exit(1)
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+ print(f"4. 恢复已有 Trace: {resume_trace_id[:8]}...")
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+ print(f" - 状态: {existing_trace.status}")
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+ print(f" - 消息数: {existing_trace.total_messages}")
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+ print(f" - 任务: {existing_trace.task}")
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+ else:
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+ print(f"4. 启动新 Agent 模式...")
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+
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+ print()
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+
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+ final_response = ""
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+ current_trace_id = resume_trace_id
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+ current_sequence = 0
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+ should_exit = False
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+
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+ try:
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+ # 恢复模式：不发送初始消息，只指定 trace_id 续跑
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+ if resume_trace_id:
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+ initial_messages = None # None = 未设置，触发早期菜单检查
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+ config = RunConfig(
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+ model=f"claude-{prompt.config.get('model', 'sonnet-4.5')}",
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+ temperature=float(prompt.config.get('temperature', 0.3)),
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+ max_iterations=1000,
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+ trace_id=resume_trace_id,
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+ )
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+ else:
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+ initial_messages = messages
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+ config = RunConfig(
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+ model=f"claude-{prompt.config.get('model', 'sonnet-4.5')}",
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+ temperature=float(prompt.config.get('temperature', 0.3)),
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+ max_iterations=1000,
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+ name="社交媒体内容解构、建构、评估任务",
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+ )
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+
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+ while not should_exit:
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+ # 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 = ""
|
|
|
+
|
|
|
+ # 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
|
|
|
+ )
|
|
|
+
|
|
|
+ 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:
|
|
|
+ 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("=" * 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__":
|
|
|
+ asyncio.run(main())
|
guantao
