atac 1.0.0

Graph-first tool runtime for agent workflows.

English | 中文

中文

ATaC 1.0.0 是一个面向 Agent 工作流的工具运行时，帮助 Agent 通过编排图代码复用资产。

它主要提供三类能力：

• 工具注册：统一注册 Agent 内置工具和 MCP 工具
• 工具调用：在 graph 节点里通过 tool_call(...) 按名字调用工具
• Python SDK：让 Agent 在 graph 代码里直接调用已注册工具

你可以把常用能力沉淀为已注册工具，再在新的图里直接复用它们，把任务经验持续积累成可维护的工作流代码。

🛠 核心能力

• Agent 工具注册：把 Agent 内置工具统一注册到 AtacService。
• MCP 工具注册：把外部 MCP 工具接入同一套工具空间中复用。
• 图代码调用 SDK：在 graph 节点里直接使用 get_service().tool_call(...)。
• 资产复用导向：Agent 通过编排图代码，把已有工具资产重新组织成新的工作流。
• LangGraph 编排友好：直接在 LangGraph graph 代码中组合和复用这些工具资产。

🤖 最小接入示例

1. 注册 Agent 内置工具

from atac import AtacService, set_service
from atac.wrapper.langgraph import tool
import atac.subprocess as subprocess

service = AtacService()
set_service(service)


@tool(name="bash")
def bash_tool(command: str) -> str:
    completed = subprocess.run(
        command,
        shell=True,
        capture_output=True,
        text=True,
    )
    if completed.returncode != 0:
        raise RuntimeError(completed.stderr.strip() or "bash failed")
    return completed.stdout.rstrip("\n")


def get_service() -> AtacService:
    return service

2. 在 graph 代码里调用 ATaC SDK

from langgraph.graph import START, END, StateGraph

from atac import get_service


def run_bash(state: dict) -> dict:
    output = get_service().tool_call("bash", {"command": f"echo {state['who']}"})
    return {"output": output}


def build_graph():
    graph = StateGraph(dict)
    graph.add_node("run_bash", run_bash)
    graph.add_edge(START, "run_bash")
    graph.add_edge("run_bash", END)
    return graph.compile()

🚀 快速开始

1. 安装

uv tool install .

2. Python SDK

from myapp.bootstrap import get_service

service = get_service()
result = service.run_graph("myapp.graphs:build_graph", {"who": "mob"})

3. 示例

• bootstrap.py
• tool_call_graph.py
• agent_workflow.py
• run_graph_demo.sh
• run_graph_sdk.py

---

English

ATaC 1.0.0 is a tool runtime for agent workflows, helping agents reuse assets through graph-based workflow code.

It focuses on:

• built-in agent tool registration
• MCP tool registration
• named tool invocation from graph nodes
• a Python SDK for calling registered tools from graph code

You can keep reusable capabilities behind registered tools, then compose new workflows by calling those assets directly from graph code.

🛠 Key Features

• Built-In Agent Tool Registration: Register agent-native tools on AtacService.
• MCP Tool Registration: Bring external MCP tools into the same reusable tool space.
• SDK Calls from Graph Code: Graph nodes can call get_service().tool_call(...).
• Asset Reuse Through Graphs: Agents build new workflows by composing graph code around existing registered tool assets.
• LangGraph-Friendly Composition: Reuse those assets directly inside LangGraph workflow code.

🤖 Minimal Integration

1. Register Built-In Agent Tools

from atac import AtacService, set_service
from atac.wrapper.langgraph import tool
import atac.subprocess as subprocess

service = AtacService()
set_service(service)


@tool(name="bash")
def bash_tool(command: str) -> str:
    completed = subprocess.run(
        command,
        shell=True,
        capture_output=True,
        text=True,
    )
    if completed.returncode != 0:
        raise RuntimeError(completed.stderr.strip() or "bash failed")
    return completed.stdout.rstrip("\n")


def get_service() -> AtacService:
    return service

2. Call the ATaC SDK from Graph Code

from langgraph.graph import START, END, StateGraph

from atac import get_service


def run_bash(state: dict) -> dict:
    output = get_service().tool_call("bash", {"command": f"echo {state['who']}"})
    return {"output": output}


def build_graph():
    graph = StateGraph(dict)
    graph.add_node("run_bash", run_bash)
    graph.add_edge(START, "run_bash")
    graph.add_edge("run_bash", END)
    return graph.compile()

🚀 Quick Start

1. Install

uv tool install .

2. Run via Python SDK

from myapp.bootstrap import get_service

service = get_service()
result = service.run_graph("myapp.graphs:build_graph", {"who": "mob"})

3. Examples

• bootstrap.py
• tool_call_graph.py
• agent_workflow.py
• run_graph_demo.sh
• run_graph_sdk.py