run.py 15 KB

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  1. """
  2. 图片模态特征提取研究示例
  3. 使用 Agent 模式 + Skills,研究应该提取什么样的图片模态特征
  4. """
  5. import argparse
  6. import os
  7. import sys
  8. import select
  9. import asyncio
  10. from pathlib import Path
  11. # Clash Verge TUN 模式兼容:禁止 httpx/urllib 自动检测系统 HTTP 代理
  12. # os.environ.setdefault("no_proxy", "*")
  13. # 添加项目根目录到 Python 路径
  14. sys.path.insert(0, str(Path(__file__).parent.parent.parent))
  15. from dotenv import load_dotenv
  16. load_dotenv()
  17. from agent.llm.prompts import SimplePrompt
  18. from agent.core.runner import AgentRunner, RunConfig
  19. from agent.trace import (
  20. FileSystemTraceStore,
  21. Trace,
  22. Message,
  23. )
  24. from agent.llm import create_openrouter_llm_call
  25. # 导入自定义工具模块,触发 @tool 装饰器注册
  26. sys.path.insert(0, str(Path(__file__).parent))
  27. import tool # noqa: E402
  28. def check_stdin() -> str | None:
  29. """非阻塞检查 stdin 是否有输入"""
  30. ready, _, _ = select.select([sys.stdin], [], [], 0)
  31. if ready:
  32. line = sys.stdin.readline().strip().lower()
  33. if line in ('p', 'pause'):
  34. return 'pause'
  35. if line in ('q', 'quit'):
  36. return 'quit'
  37. return None
  38. def _read_multiline() -> str:
  39. """读取多行输入,以连续两次回车(空行)结束"""
  40. print("\n请输入干预消息(连续输入两次回车结束):")
  41. lines: list[str] = []
  42. blank_count = 0
  43. while True:
  44. line = input()
  45. if line == "":
  46. blank_count += 1
  47. if blank_count >= 2:
  48. break
  49. lines.append("")
  50. else:
  51. blank_count = 0
  52. lines.append(line)
  53. while lines and lines[-1] == "":
  54. lines.pop()
  55. return "\n".join(lines)
  56. async def show_interactive_menu(
  57. runner: AgentRunner,
  58. trace_id: str,
  59. current_sequence: int,
  60. store: FileSystemTraceStore,
  61. ):
  62. """显示交互式菜单"""
  63. print("\n" + "=" * 60)
  64. print(" 执行已暂停")
  65. print("=" * 60)
  66. print("请选择操作:")
  67. print(" 1. 插入干预消息并继续")
  68. print(" 2. 查看当前 GoalTree")
  69. print(" 3. 继续执行")
  70. print(" 4. 停止执行")
  71. print("=" * 60)
  72. while True:
  73. choice = input("请输入选项 (1-4): ").strip()
  74. if choice == "1":
  75. text = _read_multiline()
  76. if not text:
  77. print("未输入任何内容,取消操作")
  78. continue
  79. print(f"\n将插入干预消息并继续执行...")
  80. live_trace = await store.get_trace(trace_id)
  81. actual_sequence = live_trace.last_sequence if live_trace and live_trace.last_sequence else current_sequence
  82. return {
  83. "action": "continue",
  84. "messages": [{"role": "user", "content": text}],
  85. "after_sequence": actual_sequence,
  86. }
  87. elif choice == "2":
  88. goal_tree = await store.get_goal_tree(trace_id)
  89. if goal_tree and goal_tree.goals:
  90. print("\n当前 GoalTree:")
  91. print(goal_tree.to_prompt())
  92. else:
  93. print("\n当前没有 Goal")
  94. continue
  95. elif choice == "3":
  96. print("\n继续执行...")
  97. return {"action": "continue"}
  98. elif choice == "4":
  99. print("\n停止执行...")
  100. return {"action": "stop"}
  101. else:
  102. print("无效选项,请重新输入")
  103. async def main():
  104. parser = argparse.ArgumentParser(description="图片模态特征提取研究")
  105. parser.add_argument(
  106. "--trace", type=str, default=None,
  107. help="已有的 Trace ID,用于恢复继续执行",
  108. )
  109. args = parser.parse_args()
  110. # 路径配置
  111. base_dir = Path(__file__).parent
  112. project_root = base_dir.parent.parent
  113. prompt_path = base_dir / "test.prompt"
  114. output_dir = base_dir / "output"
  115. output_dir.mkdir(exist_ok=True)
  116. # 确保 input 和 knowledge 目录存在
  117. input_dir = base_dir / "input"
  118. knowledge_dir = base_dir / "knowledge"
  119. input_dir.mkdir(exist_ok=True)
  120. knowledge_dir.mkdir(exist_ok=True)
  121. print("=" * 60)
  122. print("图片模态特征提取研究 (Agent 模式)")
  123. print("=" * 60)
  124. print()
  125. print("💡 交互提示:")
  126. print(" - 执行过程中输入 'p' 或 'pause' 暂停并进入交互模式")
  127. print(" - 执行过程中输入 'q' 或 'quit' 停止执行")
  128. print("=" * 60)
  129. print()
  130. # 加载 prompt
  131. print("1. 加载 prompt 配置...")
  132. prompt = SimplePrompt(prompt_path)
  133. # 构建消息
  134. print("2. 构建任务消息...")
  135. messages = prompt.build_messages()
  136. # 创建 Agent Runner
  137. print("3. 创建 Agent Runner...")
  138. print(f" - 模型: {prompt.config.get('model', 'sonnet-4.6')}")
  139. store = FileSystemTraceStore(base_path=".trace")
  140. runner = AgentRunner(
  141. trace_store=store,
  142. llm_call=create_openrouter_llm_call(model=f"anthropic/claude-{prompt.config.get('model', 'sonnet-4.6')}"),
  143. skills_dir=None,
  144. debug=True
  145. )
  146. # 判断是新建还是恢复
  147. resume_trace_id = args.trace
  148. if resume_trace_id:
  149. existing_trace = await store.get_trace(resume_trace_id)
  150. if not existing_trace:
  151. print(f"\n错误: Trace 不存在: {resume_trace_id}")
  152. sys.exit(1)
  153. print(f"4. 恢复已有 Trace: {resume_trace_id[:8]}...")
  154. print(f" - 状态: {existing_trace.status}")
  155. print(f" - 消息数: {existing_trace.total_messages}")
  156. else:
  157. print(f"4. 启动新 Agent 模式...")
  158. print()
  159. final_response = ""
  160. current_trace_id = resume_trace_id
  161. current_sequence = 0
  162. should_exit = False
  163. try:
  164. if resume_trace_id:
  165. initial_messages = None
  166. config = RunConfig(
  167. model=f"anthropic/claude-{prompt.config.get('model', 'sonnet-4.6')}",
  168. temperature=float(prompt.config.get('temperature', 0.3)),
  169. max_iterations=1000,
  170. trace_id=resume_trace_id,
  171. )
  172. else:
  173. initial_messages = messages
  174. config = RunConfig(
  175. model=f"anthropic/claude-{prompt.config.get('model', 'sonnet-4.6')}",
  176. temperature=float(prompt.config.get('temperature', 0.3)),
  177. max_iterations=1000,
  178. name="图片模态特征提取研究",
  179. )
  180. while not should_exit:
  181. if current_trace_id:
  182. config.trace_id = current_trace_id
  183. final_response = ""
  184. # 检查 trace 状态
  185. if current_trace_id and initial_messages is None:
  186. check_trace = await store.get_trace(current_trace_id)
  187. if check_trace and check_trace.status in ("completed", "failed"):
  188. if check_trace.status == "completed":
  189. print(f"\n[Trace] ✅ 已完成")
  190. print(f" - Total messages: {check_trace.total_messages}")
  191. print(f" - Total cost: ${check_trace.total_cost:.4f}")
  192. else:
  193. print(f"\n[Trace] ❌ 已失败: {check_trace.error_message}")
  194. current_sequence = check_trace.head_sequence
  195. menu_result = await show_interactive_menu(
  196. runner, current_trace_id, current_sequence, store
  197. )
  198. if menu_result["action"] == "stop":
  199. break
  200. elif menu_result["action"] == "continue":
  201. new_messages = menu_result.get("messages", [])
  202. if new_messages:
  203. initial_messages = new_messages
  204. config.after_sequence = menu_result.get("after_sequence")
  205. else:
  206. initial_messages = []
  207. config.after_sequence = None
  208. continue
  209. break
  210. initial_messages = []
  211. print(f"{'▶️ 开始执行...' if not current_trace_id else '▶️ 继续执行...'}")
  212. # 执行 Agent
  213. paused = False
  214. try:
  215. async for item in runner.run(messages=initial_messages, config=config):
  216. # 检查用户中断
  217. cmd = check_stdin()
  218. if cmd == 'pause':
  219. print("\n⏸️ 正在暂停执行...")
  220. if current_trace_id:
  221. await runner.stop(current_trace_id)
  222. await asyncio.sleep(0.5)
  223. menu_result = await show_interactive_menu(
  224. runner, current_trace_id, current_sequence, store
  225. )
  226. if menu_result["action"] == "stop":
  227. should_exit = True
  228. paused = True
  229. break
  230. elif menu_result["action"] == "continue":
  231. new_messages = menu_result.get("messages", [])
  232. if new_messages:
  233. initial_messages = new_messages
  234. after_seq = menu_result.get("after_sequence")
  235. if after_seq is not None:
  236. config.after_sequence = after_seq
  237. paused = True
  238. break
  239. else:
  240. initial_messages = []
  241. config.after_sequence = None
  242. paused = True
  243. break
  244. elif cmd == 'quit':
  245. print("\n🛑 用户请求停止...")
  246. if current_trace_id:
  247. await runner.stop(current_trace_id)
  248. should_exit = True
  249. break
  250. # 处理 Trace 对象
  251. if isinstance(item, Trace):
  252. current_trace_id = item.trace_id
  253. if item.status == "running":
  254. print(f"[Trace] 开始: {item.trace_id[:8]}...")
  255. elif item.status == "completed":
  256. print(f"\n[Trace] ✅ 完成")
  257. print(f" - Total messages: {item.total_messages}")
  258. print(f" - Total tokens: {item.total_tokens}")
  259. print(f" - Total cost: ${item.total_cost:.4f}")
  260. elif item.status == "failed":
  261. print(f"\n[Trace] ❌ 失败: {item.error_message}")
  262. elif item.status == "stopped":
  263. print(f"\n[Trace] ⏸️ 已停止")
  264. # 处理 Message 对象
  265. elif isinstance(item, Message):
  266. current_sequence = item.sequence
  267. if item.role == "assistant":
  268. content = item.content
  269. if isinstance(content, dict):
  270. text = content.get("text", "")
  271. tool_calls = content.get("tool_calls")
  272. if text and not tool_calls:
  273. final_response = text
  274. print(f"\n[Response] Agent 回复:")
  275. print(text)
  276. elif text:
  277. preview = text[:150] + "..." if len(text) > 150 else text
  278. print(f"[Assistant] {preview}")
  279. if tool_calls:
  280. for tc in tool_calls:
  281. tool_name = tc.get("function", {}).get("name", "unknown")
  282. print(f"[Tool Call] 🛠️ {tool_name}")
  283. elif item.role == "tool":
  284. content = item.content
  285. if isinstance(content, dict):
  286. tool_name = content.get("tool_name", "unknown")
  287. print(f"[Tool Result] ✅ {tool_name}")
  288. if item.description:
  289. desc = item.description[:80] if len(item.description) > 80 else item.description
  290. print(f" {desc}...")
  291. except Exception as e:
  292. print(f"\n执行出错: {e}")
  293. import traceback
  294. traceback.print_exc()
  295. if paused:
  296. if should_exit:
  297. break
  298. continue
  299. if should_exit:
  300. break
  301. # Runner 退出后显示交互菜单
  302. if current_trace_id:
  303. menu_result = await show_interactive_menu(
  304. runner, current_trace_id, current_sequence, store
  305. )
  306. if menu_result["action"] == "stop":
  307. break
  308. elif menu_result["action"] == "continue":
  309. new_messages = menu_result.get("messages", [])
  310. if new_messages:
  311. initial_messages = new_messages
  312. config.after_sequence = menu_result.get("after_sequence")
  313. else:
  314. initial_messages = []
  315. config.after_sequence = None
  316. continue
  317. break
  318. except KeyboardInterrupt:
  319. print("\n\n用户中断 (Ctrl+C)")
  320. if current_trace_id:
  321. await runner.stop(current_trace_id)
  322. # 输出结果
  323. if final_response:
  324. print()
  325. print("=" * 60)
  326. print("Agent 响应:")
  327. print("=" * 60)
  328. print(final_response)
  329. print("=" * 60)
  330. print()
  331. # 保存结果
  332. output_file = output_dir / "result.txt"
  333. with open(output_file, 'w', encoding='utf-8') as f:
  334. f.write(final_response)
  335. print(f"✓ 结果已保存到: {output_file}")
  336. print()
  337. # 可视化提示
  338. if current_trace_id:
  339. print("=" * 60)
  340. print("可视化 Step Tree:")
  341. print("=" * 60)
  342. print("1. 启动 API Server:")
  343. print(" python3 api_server.py")
  344. print()
  345. print("2. 浏览器访问:")
  346. print(" http://localhost:8000/api/traces")
  347. print()
  348. print(f"3. Trace ID: {current_trace_id}")
  349. print("=" * 60)
  350. if __name__ == "__main__":
  351. asyncio.run(main())