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博客园 - 荣锋亮

agno workflow 模式简单说明 agno team agent 简单说明 agno remote agent 简单说明 agno agent 使用 agno agent 平台 sshpiper 简单试用 sshpiper ssh 的反向代理服务 context-propagation spring reactor 的上下文传递包 nginx 发布1.31.2 了 reductstore 的一些部署模式 reductstore 数据写入模式 reductstore bridge 方便reductstore数据bridge 扩展 reductstore zenoh 集成 zenoh 1.9.x 一些新特性 ladybugdb嵌入式图数据库 BlockHound 检测 reactor阻塞调用的agent reductstore 高性能面向机器人以及IOT场景的存储以及流数据基石 zerofs 一些新功能 java nats request-many 支持的一些模式 java nats RequestMany context7 面向llm 以及ai代码编辑器的依赖包更新平台 NATS Agents Protocol nats 团队提出的agent 通信协议 metamcp mcp聚合&调度工具 llama-agents 的server 服务 mcp-proxy 桥接streamable http 以及stdio mcp 的工具 GhidraMCP Ghidra 的mcp服务 mcpcute 聚合mcp的工具 agent-tool-protocol 与mcp的集成 llama-agents 执行流程图查看 llama-agents 的异常处理 通过dbos 解决llama-agents workflow 持久执行问题 llama-agents workflow 持久化运行的一些玩法 llama-agents 状态管理 llama-agents stream events 处理 zerofs v1.1.1 aarch64 支持16k-64k page llama-agents step执行的一些模式 llmaindex workflows-py 变更为了llama-agents agent-tool-protocol 代码优先的agent tool 协议 ZeroFS 1.1.0 发布 chicory 原生jvm webassembly runtime quickjs4j 包含的几个模块 quickjs4j java 中安全运行js 的沙箱 supergateway 将stdio server 暴露为sse服务的ai gateway nats-server 2.14.0 发布 nuitka python 模块转so 模块 - 荣锋亮 llama-agents 的resource对象 turndown html 转markdown npm包 @langchain/node-vfs 简单试用
agno agentos 简单说明
荣锋亮 · 2026-06-29 · via 博客园 - 荣锋亮

agno agentos 实际上就是将agent,team,workflow,scheduler,直接暴露为可以提供服务访问的能力,内部基于了fastapi 进行的包装,同时提供了基于rbac的能力,agno 的一些remote 能力,也是基于此的(remote agent,remote team,remote workflow)

agentos 启动

from agno.os import AgentOS

agent_os = AgentOS(
    name="My AgentOS",
    agents=[my_agent],
    teams=[my_team],
    workflows=[my_workflow],
    tracing=True
)

app = agent_os.get_app()

if __name__ == "__main__":
    agent_os.serve(app="my_os:app", reload=True)

扩展路由

因为是基于了fast API 可以灵活扩展

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.anthropic import Claude
from agno.os import AgentOS
from agno.tools.hackernews import HackerNewsTools
from fastapi import FastAPI

# Create custom FastAPI app
app: FastAPI = FastAPI(
    title="Custom FastAPI App",
    version="1.0.0",
)


# Custom landing page (conflicts with AgentOS home route)
@app.get("/")
async def get_custom_home():
    return {
        "message": "Custom FastAPI App",
        "note": "Using on_route_conflict=\"preserve_base_app\" to preserve custom routes",
    }


# Custom health endpoint (conflicts with AgentOS health route)
@app.get("/health")
async def get_custom_health():
    return {"status": "custom_ok", "note": "This is your custom health endpoint"}


# Set up the AgentOS app by passing your FastAPI app
# Use on_route_conflict="preserve_base_app" to preserve your custom routes over AgentOS routes
agent_os = AgentOS(
    description="Example app with route replacement",
    agents=[web_research_agent],
    base_app=app,
    on_route_conflict="preserve_base_app",  # Skip conflicting AgentOS routes, keep your custom routes
)

app = agent_os.get_app()

暴露mcp服务

agent_os = AgentOS(
    description="Example app with MCP enabled",
    agents=[web_research_agent],
    enable_mcp_server=True,  # This enables a LLM-friendly MCP server at /mcp
)

动态agent 能力

通过factory 可以进行扩展

def build_tenant_agent(ctx: RequestContext) -> Agent:
    user_id = ctx.user_id or "anonymous"
    return Agent(
        model=OpenAIResponses(id="gpt-5.4"),
        db=db,
        instructions=f"You are a helpful assistant for tenant {user_id}. Be concise.",
        markdown=True,
    )


tenant_factory = AgentFactory(
    id="tenant-agent",
    db=db,
    factory=build_tenant_agent,
    name="Per-tenant assistant",
    description="Builds a personalized agent per tenant on each request.",
)

agent_os = AgentOS(agents=[tenant_factory])
app = agent_os.get_app()

说明

agno 的agentos 是将agno 能力暴露服务的一个能力,扩展点不少,是快速提供agent 能力一个不错的选择

参考资料

https://docs.agno.com/agent-os/run-your-os