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CodeRabbitBuild stateful, multi-actor AI agents with LangGraph.
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Build stateful, multi-actor AI agents with LangGraph.
{"id":"12397213-5757-4452-87c1-6c0bd9b1e0ee","title":"LangGraph Agent Template","description":"LangGraph is a framework for building robust, stateful multi-actor applications with LLMs, ideal for creating conversational agents, task-driven automation, and interactive data processing pipelines. This template provides a foundational structure for developing sophisticated AI agents, integrating various tools and memory components to manage complex interactions and maintain context over extended dialogues. It enables rapid prototyping and deployment of agent-based systems, enhancing productivity for developers.","dateModified":"2026-04-03","difficulty":"intermediate","tags":["langgraph","agent-template","llm-framework","python","multi-agent"],"tokenImpact":"Moderate — 1,000–3,000 tokens per call, monitor quota during lockouts.","setupCommand":"git clone https://github.com/langchain-ai/langgraph.git && cd langgraph/examples/agents && pip install -r requirements.txt","copyButtonText":"Copy setup command","faq":[{"question":"What is included in this boilerplate?","answer":"This boilerplate provides a foundational structure for building sophisticated AI agents using LangGraph, including examples of multi-actor setups, state management, and tool integration. It offers a clear starting point for developing conversational interfaces, autonomous task execution systems, and data processing pipelines."},{"question":"What are the prerequisites?","answer":"To use this boilerplate, you need Python 3.8+, pip, and an understanding of Python programming. Familiarity with LangChain concepts and large language models is beneficial. Access to an LLM provider (e.g., OpenAI API key) is also typically required for agent functionality."},{"question":"How do I set up this boilerplate locally?","answer":"First, clone the LangGraph repository: `git clone https://github.com/langchain-ai/langgraph.git`. Then navigate to the examples directory, choose an agent example, and install its dependencies: `cd langgraph/examples/agents/<agent-example> && pip install -r requirements.txt`."}]}Gin Vue Admin — Resource. 🚀Vite+Vue3+Gin拥有AI辅助的基础开发平台，企业级业务AI+开发解决方案，内置mcp辅助服务，内置skills管理，支持TS和JS混用。它集成了JWT鉴权、权限管理、动态路由、显隐可控组件、分页封装、多点登录拦截、资源权限、上传下载、代码生成器、表单生成器和可配置的导入导出等开发必备功能。
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