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cloudbase-agent-python

Build AI agent backends with the CloudBase Agent Python SDK.

Updated Mar 10, 2026
Search Tags:#middleware#streaming#observability#server#langgraph#openai#ai-agent
One-click install
npx skills add https://github.com/xongtao/openclaw-backup --skill cloudbase-agent-python-xongtao
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cloudbase-agent-python
Source: https://github.com/xongtao/openclaw-backup/tree/main/skills/cloudbase/references/cloudbase-agent/py
Command: npx skills add https://github.com/xongtao/openclaw-backup --skill cloudbase-agent-python-xongtao

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Build production-ready AI agent backends using the CloudBase Agent Python SDK to standardize agent lifecycles, protocol streaming, and OpenAI-compatible endpoints.

Core Features & Use Cases

  • Create multi-framework agents (LangGraph, CrewAI, LlamaIndex) and serve them via FastAPI with AG-UI streaming.
  • Integrate tools (bash, filesystem, MCP, code execution) and memory backends to persist conversations.
  • Add observability and middleware (auth, logging) and deploy robust APIs for AI agents.

Quick Start

Start the server by calling AgentServiceApp with a per-request agent factory and a chosen port.

Frequently Asked Questions about cloudbase-agent-python

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a production-ready AI agent server with LangGraph and FastAPI?▼

Build production-ready AI agent servers using the CloudBase Agent Python SDK to serve LangGraph, CrewAI, or LlamaIndex workflows via FastAPI with AG-UI streaming and OpenAI-compatible endpoints. It standardizes agent lifecycles, protocol streaming, and observability features.

What is the AG-UI protocol for streaming AI agent responses?▼

The AG-UI protocol enables streaming for AI agent servers. The CloudBase Agent Python SDK implements AG-UI streaming to standardize protocol streaming across multi-framework agents, allowing real-time response delivery via OpenAI-compatible endpoints built with FastAPI.

Can I integrate external tools and memory backends with my AI agent server?▼

Yes, you can integrate tools like bash, filesystem, MCP, and code execution alongside memory backends to persist conversations. The SDK supports adding these tools and memory backends to multi-framework agents served via FastAPI.

Does the CloudBase Agent Python SDK support observability and middleware features?▼

The CloudBase Agent Python SDK supports observability and middleware features including authentication and logging. These features integrate across memory, tools, and middleware to deploy robust APIs for AI agents with standardized monitoring.

What are the Python version requirements for deploying an AI agent server with this SDK?▼

Deploying an AI agent server requires Python 3.10. The SDK enforces a blocking deployment pipeline with atomic environment builds and verification steps across a four-step process to ensure robust API deployment for AI agents.

How do I serve OpenAI-compatible endpoints for my CrewAI agent?▼

Serve OpenAI-compatible endpoints for CrewAI agents by using the CloudBase Agent Python SDK. It wraps CrewAI workflows with FastAPI, providing AG-UI protocol streaming and standardized agent lifecycle management for production deployment.

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