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@@ -1,378 +0,0 @@
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-"""
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-示例（简化版 - 使用框架交互功能）
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-
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-使用 Agent 模式 + Skills + 框架交互控制器
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-
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-新功能：
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-1. 使用框架提供的 InteractiveController
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-2. 使用配置文件管理运行参数
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-3. 支持命令行随时打断（输入 'p' 暂停，'q' 退出）
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-4. 暂停后可插入干预消息
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-5. 支持触发经验总结
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-6. 查看当前 GoalTree
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-7. 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 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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-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.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_qwen_llm_call
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-from agent.cli import InteractiveController
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-from agent.utils import setup_logging
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-from agent.tools.builtin.browser.baseClass import init_browser_session, kill_browser_session
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-
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-# 导入自定义工具（触发 @tool 注册）
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-from tools.reflect import reflect
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-
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-# 导入项目配置
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-from config import RUN_CONFIG, SKILLS_DIR, TRACE_STORE_PATH, DEBUG, LOG_LEVEL, LOG_FILE, BROWSER_TYPE, HEADLESS, INPUT_DIR, OUTPUT_DIR
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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 / "requirement.prompt"
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- output_dir = project_root / OUTPUT_DIR
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- output_dir.mkdir(parents=True, exist_ok=True)
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-
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- # 1. 配置日志
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- setup_logging(level=LOG_LEVEL, file=LOG_FILE)
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-
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- # 2. 加载项目级 presets
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- print("2. 加载 presets...")
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- presets_path = base_dir / "presets.json"
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- if presets_path.exists():
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- from agent.core.presets import load_presets_from_json
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- load_presets_from_json(str(presets_path))
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- print(f" - 已加载项目 presets")
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- else:
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- print(f" - 未找到 presets.json，跳过")
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-
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- # 3. 加载 prompt
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- print("3. 加载 prompt...")
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- prompt = SimplePrompt(prompt_path)
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-
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- # 4. 构建任务消息
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- print("4. 构建任务消息...")
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- print(f" - 输入目录: {INPUT_DIR}")
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- print(f" - 输出 ID: {OUTPUT_DIR}")
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- messages = prompt.build_messages(input_dir=INPUT_DIR, output_dir=OUTPUT_DIR)
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-
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- # 5. 初始化浏览器
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- browser_mode_names = {"cloud": "云浏览器", "local": "本地浏览器", "container": "容器浏览器"}
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- browser_mode_name = browser_mode_names.get(BROWSER_TYPE, BROWSER_TYPE)
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- print(f"5. 正在初始化{browser_mode_name}...")
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- await init_browser_session(
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- browser_type=BROWSER_TYPE,
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- headless=HEADLESS,
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- url="https://www.google.com/",
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- profile_name=""
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- )
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- print(f" ✅ {browser_mode_name}初始化完成\n")
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-
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- # 6. 创建 Agent Runner
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- print("6. 创建 Agent Runner...")
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- print(f" - Skills 目录: {SKILLS_DIR}")
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-
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- # 从 prompt 的 frontmatter 中提取模型配置（优先于 config.py）
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- prompt_model = prompt.config.get("model", None)
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- if prompt_model:
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- model_for_llm = prompt_model
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- print(f" - 模型 (from prompt): {model_for_llm}")
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- else:
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- model_for_llm = RUN_CONFIG.model
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- print(f" - 模型 (from config): {model_for_llm}")
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-
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- store = FileSystemTraceStore(base_path=TRACE_STORE_PATH)
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- runner = AgentRunner(
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- trace_store=store,
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- llm_call=create_qwen_llm_call(model=model_for_llm),
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- skills_dir=SKILLS_DIR,
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- debug=DEBUG
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- )
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-
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- # 7. 创建交互控制器
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- interactive = InteractiveController(
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- runner=runner,
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- store=store,
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- enable_stdin_check=True
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- )
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- # 将 stdin 检查回调注入 runner，供子 agent 执行期间使用
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- runner.stdin_check = interactive.check_stdin
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-
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- # 8. 任务信息
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- task_name = RUN_CONFIG.name or base_dir.name
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- print("=" * 60)
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- print(f"{task_name}")
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- print("=" * 60)
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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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- # 9. 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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- 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"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"\n💡 提示：恢复 Trace 时会先进入交互菜单，您可以选择从指定消息续跑")
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- else:
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- print(f"启动新 Agent...")
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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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- # 配置
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- run_config = RUN_CONFIG
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- if resume_trace_id:
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- initial_messages = None
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- run_config.trace_id = resume_trace_id
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- else:
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- initial_messages = messages
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- run_config.name = f"{task_name}：调研任务"
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-
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- while not should_exit:
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- if current_trace_id:
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- run_config.trace_id = current_trace_id
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-
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- final_response = ""
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-
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- # 如果是恢复 trace 或 trace 已完成/失败且没有新消息，进入交互菜单
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- if current_trace_id and initial_messages is None:
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- check_trace = await store.get_trace(current_trace_id)
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- if check_trace:
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- # 显示 trace 状态
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- if check_trace.status == "completed":
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- print(f"\n[Trace] ✅ 已完成")
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- print(f" - Total messages: {check_trace.total_messages}")
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- print(f" - Total cost: ${check_trace.total_cost:.4f}")
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- elif check_trace.status == "failed":
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- print(f"\n[Trace] ❌ 已失败: {check_trace.error_message}")
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- elif check_trace.status == "stopped":
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- print(f"\n[Trace] ⏸️ 已停止")
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- print(f" - Total messages: {check_trace.total_messages}")
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- else:
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- print(f"\n[Trace] 📊 状态: {check_trace.status}")
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- print(f" - Total messages: {check_trace.total_messages}")
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-
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- current_sequence = check_trace.head_sequence
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-
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- menu_result = await interactive.show_menu(current_trace_id, current_sequence)
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-
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- if menu_result["action"] == "stop":
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- break
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- elif menu_result["action"] == "continue":
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- new_messages = menu_result.get("messages", [])
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- if new_messages:
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- initial_messages = new_messages
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- run_config.after_sequence = menu_result.get("after_sequence")
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- else:
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- initial_messages = []
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- run_config.after_sequence = None
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- continue
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- break
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-
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- # 如果没有进入菜单（新建 trace），设置初始消息
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- if initial_messages is None:
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- initial_messages = []
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-
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- print(f"{'▶️ 开始执行...' if not current_trace_id else '▶️ 继续执行...'}")
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-
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- # 执行 Agent
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- paused = False
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- try:
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- async for item in runner.run(messages=initial_messages, config=run_config):
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- # 检查用户中断
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- cmd = interactive.check_stdin()
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- if cmd == 'pause':
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- print("\n⏸️ 正在暂停执行...")
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- if current_trace_id:
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- await runner.stop(current_trace_id)
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- await asyncio.sleep(0.5)
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-
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- menu_result = await interactive.show_menu(current_trace_id, current_sequence)
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-
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- if menu_result["action"] == "stop":
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- should_exit = True
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- paused = True
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- break
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- elif menu_result["action"] == "continue":
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- new_messages = menu_result.get("messages", [])
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- if new_messages:
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- initial_messages = new_messages
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- after_seq = menu_result.get("after_sequence")
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- if after_seq is not None:
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- run_config.after_sequence = after_seq
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- paused = True
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- break
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- else:
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- initial_messages = []
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- run_config.after_sequence = None
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- paused = True
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- break
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-
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- elif cmd == 'quit':
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- print("\n🛑 用户请求停止...")
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- if current_trace_id:
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- await runner.stop(current_trace_id)
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- should_exit = True
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- break
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-
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- # 处理 Trace 对象
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- if isinstance(item, Trace):
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- current_trace_id = item.trace_id
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- if item.status == "running":
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- print(f"[Trace] 开始: {item.trace_id[:8]}...")
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- elif item.status == "completed":
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- print(f"\n[Trace] ✅ 完成")
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- print(f" - Total messages: {item.total_messages}")
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- print(f" - Total cost: ${item.total_cost:.4f}")
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- elif item.status == "failed":
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- print(f"\n[Trace] ❌ 失败: {item.error_message}")
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- elif item.status == "stopped":
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- print(f"\n[Trace] ⏸️ 已停止")
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-
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- # 处理 Message 对象
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- elif isinstance(item, Message):
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- current_sequence = item.sequence
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-
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- if item.role == "assistant":
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- content = item.content
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- if isinstance(content, dict):
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- text = content.get("text", "")
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- tool_calls = content.get("tool_calls")
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-
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- if text and not tool_calls:
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- final_response = text
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- print(f"\n[Response] Agent 回复：")
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- print(text)
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- elif text:
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- preview = text[:150] + "..." if len(text) > 150 else text
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- print(f"[Assistant] {preview}")
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-
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- elif item.role == "tool":
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- content = item.content
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- tool_name = "unknown"
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- if isinstance(content, dict):
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- tool_name = content.get("tool_name", "unknown")
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-
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- if item.description and item.description != tool_name:
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- desc = item.description[:80] if len(item.description) > 80 else item.description
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- print(f"[Tool Result] ✅ {tool_name}: {desc}...")
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- else:
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- print(f"[Tool Result] ✅ {tool_name}")
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-
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- except Exception as e:
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- print(f"\n执行出错: {e}")
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- import traceback
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- traceback.print_exc()
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-
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- if paused:
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- if should_exit:
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- break
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- continue
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-
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- if should_exit:
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- break
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-
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- # Runner 退出后显示交互菜单
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- if current_trace_id:
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- menu_result = await interactive.show_menu(current_trace_id, current_sequence)
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-
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- if menu_result["action"] == "stop":
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- break
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- elif menu_result["action"] == "continue":
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- new_messages = menu_result.get("messages", [])
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- if new_messages:
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- initial_messages = new_messages
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- run_config.after_sequence = menu_result.get("after_sequence")
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- else:
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- initial_messages = []
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- run_config.after_sequence = None
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- continue
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- break
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-
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- except KeyboardInterrupt:
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- print("\n\n用户中断 (Ctrl+C)")
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- if current_trace_id:
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- await runner.stop(current_trace_id)
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- finally:
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- # 清理浏览器会话
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- try:
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- await kill_browser_session()
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- except Exception:
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- pass
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-
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- # 7. 输出结果
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- if final_response:
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- print()
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- print("=" * 60)
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- print("Agent 响应:")
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- print("=" * 60)
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- print(final_response)
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- print("=" * 60)
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- print()
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-
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- output_file = output_dir / "result.txt"
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- with open(output_file, 'w', encoding='utf-8') as f:
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- f.write(final_response)
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-
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- print(f"✓ 结果已保存到: {output_file}")
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- print()
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-
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- # 可视化提示
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- if current_trace_id:
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- print("=" * 60)
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- print("可视化 Step Tree:")
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- print("=" * 60)
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- print("1. 启动 API Server:")
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- print(" python3 api_server.py")
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- print()
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- print("2. 浏览器访问:")
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- print(" http://localhost:8000/api/traces")
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- print()
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- print(f"3. Trace ID: {current_trace_id}")
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- print("=" * 60)
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-
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-
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-if __name__ == "__main__":
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- asyncio.run(main())
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Talegorithm