手把手教你掌握新一代 AI 工具：从 Spec Coding 到多智能体编排

# Spec: 订单查询接口

## 业务规则
- 仅返回当前租户订单
- 状态枚举: pending/paid/shipped
- 分页默认 20，最大 100

## 技术约束
- Spring Boot 3 + MyBatis-Plus
- 响应包装统一 ApiResponse
- 缓存: Caffeine, 5分钟过期

## 验收标准
- 空结果返回空数组，不返回 404
- 非法 pageSize 返回 400

from langgraph.graph import StateGraph, START, END
from typing import TypedDict, Annotated
import operator

class RouterState(TypedDict):
    question: str
    source: str          # github | notion | slack
    answer: str

def classify(state: RouterState) -> RouterState:
    q = state["question"].lower()
    if any(k in q for k in ["代码", "issue", "pr", "commit"]):
        return {"source": "github"}
    if any(k in q for k in ["文档", "wiki", "规范"]):
        return {"source": "notion"}
    return {"source": "slack"}

def github_agent(state: RouterState) -> RouterState:
    return {"answer": f"[GitHub] 检索到与'{state['question']}'相关的 3 个 PR"}

def notion_agent(state: RouterState) -> RouterState:
    return {"answer": f"[Notion] 找到 2 篇相关文档"}

def slack_agent(state: RouterState) -> RouterState:
    return {"answer": f"[Slack] 匹配到 5 条讨论"}

builder = StateGraph(RouterState)
builder.add_node("classify", classify)
builder.add_node("github", github_agent)
builder.add_node("notion", notion_agent)
builder.add_node("slack", slack_agent)

builder.add_edge(START, "classify")
builder.add_conditional_edges("classify",
    lambda s: s["source"],
    {"github": "github", "notion": "notion", "slack": "slack"})
builder.add_edge("github", END)
builder.add_edge("notion", END)
builder.add_edge("slack", END)

graph = builder.compile()
result = graph.invoke({"question": "UserService 的缓存策略文档在哪？"})
print(result["answer"])

from ractogateway import ToolRegistry
from ractogateway.mcp import RactoMCPServer

registry = ToolRegistry()

@registry.register
def search_docs(query: str) -> str:
    """检索内部文档"""
    return f"关于'{query}'的文档内容..."

server = RactoMCPServer.from_registry(registry, name="docs-tools")
# server.run(transport="stdio")  # 启动 MCP 服务