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