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+"""
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+Agent SDK 入口 —— 统一调用 remote / 本地 Agent 的公开 API。
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+
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+使用方式（任何进程，只要装了 cyber-agent 包）：
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+
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+ import asyncio
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+ from agent import invoke_agent
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+
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+ # 远端（HTTP 调用 KnowHub 服务器）
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+ result = asyncio.run(invoke_agent(
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+ agent_type="remote_librarian",
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+ task="ControlNet 相关的工具知识",
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+ skills=["ask_strategy"],
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+ ))
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+
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+ # 本地（在当前进程起 AgentRunner）
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+ result = asyncio.run(invoke_agent(
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+ agent_type="deconstruct",
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+ task="...",
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+ project_root="./examples/production_plan",
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+ ))
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+
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+skill 脚本只需要 `from agent import invoke_agent` 然后透传命令行参数即可——
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+不依赖仓库相对路径，也不会触发 `agent.tools.builtin` 的 eager tool registry 加载。
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+"""
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+
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+import importlib
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+import importlib.util
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+import logging
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+import os
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+import sys
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+from pathlib import Path
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+from typing import Any, Dict, List, Optional
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+
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+logger = logging.getLogger(__name__)
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+
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+
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+async def invoke_agent(
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+ agent_type: str,
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+ task: str,
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+ skills: Optional[List[str]] = None,
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+ continue_from: Optional[str] = None,
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+ messages: Optional[List[Dict[str, Any]]] = None,
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+ project_root: Optional[str] = None,
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+) -> Dict[str, Any]:
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+ """
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+ 统一调用远端或本地 Agent。
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+
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+ Args:
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+ agent_type: Agent 类型。以 "remote_" 开头 → HTTP 调用 KnowHub；否则本地执行。
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+ task: 任务描述
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+ skills: 指定 skill 列表（远端由服务器白名单过滤；本地覆盖项目 RUN_CONFIG.skills）
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+ continue_from: 已有 sub_trace_id，传入则续跑
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+ messages: 预置 OpenAI 格式消息（远端 1D、本地 1D）
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+ project_root: 本地 agent 必填——项目目录（含 config.py / presets.json / tools/）
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+
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+ Returns:
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+ {"mode", "agent_type", "sub_trace_id", "status", "summary", "stats", "error"?}
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+ """
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+ if agent_type.startswith("remote_"):
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+ # 懒 import，避免加载整个 tool registry（远端调用只需要 httpx）
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+ from agent.tools.builtin.subagent import _run_remote_agent
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+ return await _run_remote_agent(
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+ agent_type=agent_type,
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+ task=task,
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+ messages=messages,
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+ continue_from=continue_from,
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+ skills=skills,
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+ )
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+
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+ if not project_root:
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+ return {
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+ "mode": "local",
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+ "agent_type": agent_type,
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+ "status": "failed",
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+ "error": "本地 agent 需要 project_root 指定项目目录（含 config.py）",
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+ }
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+
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+ return await _run_local_agent(
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+ agent_type=agent_type,
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+ task=task,
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+ skills=skills,
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+ continue_from=continue_from,
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+ messages=messages,
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+ project_root=project_root,
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+ )
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+
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+
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+async def _run_local_agent(
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+ agent_type: str,
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+ task: str,
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+ skills: Optional[List[str]],
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+ continue_from: Optional[str],
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+ messages: Optional[List[Dict[str, Any]]],
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+ project_root: str,
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+) -> Dict[str, Any]:
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+ """
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+ 在当前进程中起 AgentRunner 跑本地 agent。
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+
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+ 项目目录约定：
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+ project_root/
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+ ├── config.py # 必需：定义 RUN_CONFIG（RunConfig 实例），可选 SKILLS_DIR / TRACE_STORE_PATH
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+ ├── presets.json # 可选：agent_type preset
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+ └── tools/ # 可选：项目自定义工具（有 __init__.py 则 import 触发 @tool 注册）
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+
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+ .env 会自动从 project_root 或上两级目录查找并加载。
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+ """
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+ root = Path(project_root).resolve()
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+ if not root.is_dir():
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+ return {"mode": "local", "agent_type": agent_type, "status": "failed",
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+ "error": f"project_root 不存在: {root}"}
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+
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+ # 1. 把项目根加入 sys.path（让 `import config` / `import tools` 能找到）
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+ if str(root) not in sys.path:
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+ sys.path.insert(0, str(root))
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+
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+ # 2. 加载 .env：依次查项目根、两级父目录（兼容 monorepo）、cyber-agent 仓库根
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+ try:
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+ from dotenv import load_dotenv
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+ import agent as _agent_pkg
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+ agent_repo_root = Path(_agent_pkg.__file__).parent.parent
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+ for candidate in (
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+ root / ".env",
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+ root.parent / ".env",
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+ root.parent.parent / ".env",
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+ agent_repo_root / ".env",
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+ ):
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+ if candidate.exists():
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+ load_dotenv(candidate)
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+ break
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+ except ImportError:
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+ pass
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+
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+ # 3. 加载项目 config
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+ config_path = root / "config.py"
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+ if not config_path.exists():
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+ return {"mode": "local", "agent_type": agent_type, "status": "failed",
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+ "error": f"缺少 {config_path}"}
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+
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+ try:
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+ spec = importlib.util.spec_from_file_location("_project_config", config_path)
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+ cfg_mod = importlib.util.module_from_spec(spec)
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+ spec.loader.exec_module(cfg_mod)
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+ except Exception as e:
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+ return {"mode": "local", "agent_type": agent_type, "status": "failed",
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+ "error": f"加载 {config_path} 失败: {e}"}
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+
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+ run_config = getattr(cfg_mod, "RUN_CONFIG", None)
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+ if run_config is None:
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+ return {"mode": "local", "agent_type": agent_type, "status": "failed",
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+ "error": f"{config_path} 未定义 RUN_CONFIG"}
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+
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+ # 覆盖 agent_type / skills / continue_from
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+ run_config.agent_type = agent_type
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+ if skills is not None:
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+ run_config.skills = skills
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+ if continue_from:
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+ run_config.trace_id = continue_from
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+
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+ # 4. 加载项目 presets.json（如果有）
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+ presets_path = root / "presets.json"
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+ if presets_path.exists():
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+ try:
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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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+ except Exception as e:
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+ logger.warning(f"加载 presets.json 失败: {e}")
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+
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+ # 5. 触发项目自定义工具注册（约定：project_root/tools/__init__.py）
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+ if (root / "tools" / "__init__.py").exists():
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+ try:
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+ importlib.import_module("tools")
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+ except Exception as e:
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+ logger.warning(f"加载 tools 包失败: {e}")
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+
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+ # 6. 创建 AgentRunner
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+ from agent.core.runner import AgentRunner
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+ from agent.trace import FileSystemTraceStore
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+ from agent.llm import create_qwen_llm_call
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+
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+ trace_store_path = getattr(cfg_mod, "TRACE_STORE_PATH", ".trace")
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+ skills_dir = getattr(cfg_mod, "SKILLS_DIR", "./skills")
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+
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+ # 相对路径以 project_root 为基准
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+ if not os.path.isabs(trace_store_path):
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+ trace_store_path = str(root / trace_store_path)
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+ if not os.path.isabs(skills_dir):
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+ skills_dir = str(root / skills_dir)
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+
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+ runner = AgentRunner(
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+ trace_store=FileSystemTraceStore(base_path=trace_store_path),
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+ llm_call=create_qwen_llm_call(model=run_config.model),
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+ skills_dir=skills_dir,
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+ )
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+
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+ # 7. 构建消息
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+ msgs = list(messages) if messages else []
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+ msgs.append({"role": "user", "content": task})
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+
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+ # 8. 运行
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+ try:
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+ result = await runner.run_result(messages=msgs, config=run_config)
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+ except Exception as e:
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+ logger.exception("本地 agent 运行失败")
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+ return {"mode": "local", "agent_type": agent_type, "status": "failed",
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+ "error": f"{type(e).__name__}: {e}"}
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+
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+ return {
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+ "mode": "local",
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+ "agent_type": agent_type,
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+ "sub_trace_id": result.get("trace_id"),
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+ "status": result.get("status", "unknown"),
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+ "summary": result.get("summary", ""),
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+ "stats": result.get("stats", {}),
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+ "error": result.get("error"),
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+ }
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Talegorithm