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ThearchyHelios
964eeaa829
在画布上拖拽编排 agent 工作流，并实时看着它执行。 后端 FastAPI + LangGraph：把画布 JSON 编译成 StateGraph，15 种节点 （模型/Agent/多Agent、工具/沙箱、分支/循环/子图、记忆/检索/整形、 人工介入/结构校验）。选 LangGraph 是因为可视化编排真正难的是暂停、 恢复和回放，而 checkpointer + interrupt() 正好把这几件事做在了底层。 前端 React + React Flow：节点元数据驱动属性面板与连接桩，运行时 节点高亮、边流动画、卡片内流式 token 全部由同一份事件流驱动。 关键实现： - Agent 内工具审批用 @task 缓存模型调用，interrupt 重放时不重复计费 - 沙箱保持只读根文件系统，代码经 exec+base64 写入（put_archive 会被 只读容器拒绝），断网、非 root、内存/CPU/超时限额 - 检索为向量与 BM25 混合，本地哈希 embedding 零配置可用 - 分支条件走 AST 白名单求值器；HTTP 工具逐 IP 拦截内网与元数据地址 - Mock provider 让无 API Key 也能跑通完整链路 7 个内置模板全部冒烟通过，含真实模型端到端验证。
76 lines
2.1 KiB
Python
76 lines
2.1 KiB
Python
from __future__ import annotations
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import abc
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from typing import Any
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from pydantic import BaseModel, Field
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from app.core.config import settings
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class SandboxLimits(BaseModel):
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timeout: int = Field(default_factory=lambda: settings.sandbox_timeout)
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memory_mb: int = Field(default_factory=lambda: settings.sandbox_memory_mb)
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cpus: float = Field(default_factory=lambda: settings.sandbox_cpus)
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network: bool = Field(default_factory=lambda: settings.sandbox_network)
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max_output: int = Field(default_factory=lambda: settings.sandbox_max_output)
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class ExecResult(BaseModel):
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ok: bool = True
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exit_code: int = 0
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stdout: str = ""
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stderr: str = ""
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duration_ms: int = 0
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timed_out: bool = False
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truncated: bool = False
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backend: str = ""
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files_written: list[str] = Field(default_factory=list)
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error: str | None = None
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def summary(self) -> str:
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if self.timed_out:
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return f"执行超时（>{'?'}s）"
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if self.error:
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return self.error
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return self.stdout or self.stderr or "(无输出)"
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class Sandbox(abc.ABC):
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"""代码执行后端的统一接口。"""
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name: str = "base"
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@abc.abstractmethod
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async def run(
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self,
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code: str,
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*,
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language: str = "python",
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limits: SandboxLimits | None = None,
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session_id: str | None = None,
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env: dict[str, str] | None = None,
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files: dict[str, str] | None = None,
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) -> ExecResult:
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"""执行一段代码。session_id 相同的调用共享同一个文件系统，
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这样 agent 可以先写文件、再在下一步读回来。"""
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async def health(self) -> dict[str, Any]:
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return {"backend": self.name, "available": True}
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async def cleanup(self, session_id: str) -> None:
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return None
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async def close(self) -> None:
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return None
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def truncate(text: str, limit: int) -> tuple[str, bool]:
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if len(text) <= limit:
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return text, False
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half = limit // 2
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return (
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text[:half] + f"\n\n…（省略 {len(text) - limit} 字符）…\n\n" + text[-half:],
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True,
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)
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