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cloudbase-agent-python

Build AI agent backends with multi-framework support and streaming protocol.

Updated Mar 7, 2026
Search Tags:#ai agent#langgraph#crewai#llamaindex#cloudbase
One-click install
npx skills add https://github.com/dang0705/planting --skill cloudbase-agent-python-dang0705
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cloudbase-agent-python
Source: https://github.com/dang0705/planting/tree/main/.agents/skills/cloudbase/references/cloudbase-agent/py
Command: npx skills add https://github.com/dang0705/planting --skill cloudbase-agent-python-dang0705

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires cloudbase-agent-core, cloudbase-agent-server, cloudbase-agent-langgraph, cloudbase-agent-crewai, cloudbase-agent-llamaindex, cloudbase-agent-coze, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a comprehensive solution for building production-ready AI agent backends. It addresses the challenges of integrating various AI frameworks, managing complex workflows, and deploying robust, observable AI services.

Core Features & Use Cases

  • Multi-Framework Support: Integrate with LangGraph, CrewAI, LlamaIndex, and custom frameworks to build flexible AI agents.
  • Streaming Protocol: Utilize AG-UI protocol for real-time communication and event streaming between the agent and the client.
  • Rich Tools & Storage: Leverage tools for system access, file manipulation, and code execution, and persistent storage options for data retention.
  • Observability: Implement logging, tracing, and monitoring to gain insights into agent behavior and performance.
  • Use Case: Develop a chatbot backend using LangGraph for conversational AI, or integrate with Coze for building AI agents with multi-agent collaboration capabilities.

Quick Start

To get started, install the dependencies for your desired framework and create an agent. Then, deploy the agent server to CloudBase following the 4-step deployment pipeline.

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 backend with LangGraph or CrewAI?▼

Multi-framework AI agents are supported through native integration with LangGraph, CrewAI, LlamaIndex, and Coze. This allows you to build flexible conversational AI or complex multi-agent collaboration workflows on a unified backend.

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

Yes, you can deploy AI agents to CloudBase by following the provided 4-step deployment pipeline. It requires Python 3.10 and the CloudBase Agent Python SDK to configure, package, and launch your agent server.

Can I deploy LangGraph or CrewAI agents to CloudBase using Python?▼

Rich tools available include system access, file manipulation, and code execution capabilities. The Skill also provides persistent storage options for data retention and full observability through logging, tracing, and monitoring.

Does the CloudBase Agent Python SDK support persistent memory and observability?▼

The AG-UI protocol is a streaming protocol used for real-time communication and event streaming between the AI agent and the client. It enables interactive, low-latency responses in chatbot backends and complex AI workflows.

What Python version is required to set up the CloudBase Agent SDK?▼

Python 3.10 is required to set up and run the CloudBase Agent SDK. You need to install dependencies for your desired framework and configure the environment before deploying the agent server.

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