🚀 LangGraph: 8500⭐ 状态化智能体编排框架
LangGraph 是一个低级别的编排框架，专门用于构建有状态的智能体和工作流。它来自 LangChain 团队，已经被 Klarna、Replit、Elastic 等公司实际使用。
核心卖点
LangGraph 最大的特色是持久化执行能力。你可以构建能够通过故障并长时间运行的智能体，它们会从上次中断的地方自动恢复。这对于需要长时间运行的复杂任务特别有用。
安装使用
pip install -U langgraph
主要特性
实际应用
LangGraph 可以独立使用，也可以与任何 LangChain 产品无缝集成。它提供了完整的智能体构建工具套件。
对于想要快速构建智能体的开发者，还有一个更高层级的包叫做 Deep Agents，它基于 LangGraph 构建，支持规划、使用子智能体和利用文件系统处理复杂任务。
为什么选择 LangGraph
与其他框架不同，LangGraph 专注于状态管理和持久化执行。这意味着你的智能体可以在长时间运行过程中保持状态，即使遇到故障也能恢复。这对于需要持续学习、记忆和适应的复杂 AI 应用来说至关重要。
如果你正在构建需要长期运行、有状态的 AI 智能体，LangGraph 绝对值得考虑。
🚀 LangGraph: 8500⭐ Stateful Agent Orchestration Framework
LangGraph is a low-level orchestration framework specifically designed for building stateful agents and workflows. From the LangChain team, it's already being used by companies like Klarna, Replit, and Elastic.
Key Features
The biggest highlight of LangGraph is its durable execution capability. You can build agents that persist through failures and run for extended periods, automatically resuming from exactly where they left off. This is particularly useful for complex tasks that need to run long-term.
Installation & Usage
pip install -U langgraph
Main Capabilities
Real-world Applications
LangGraph can be used standalone or integrates seamlessly with any LangChain product, providing a complete toolkit for building agents.
For developers who want to quickly build agents, there's also a higher-level package called Deep Agents built on LangGraph, supporting planning, using sub-agents, and leveraging file systems for complex tasks.
Why Choose LangGraph
Unlike other frameworks, LangGraph focuses on state management and durable execution. This means your agents can maintain state during long-running operations and recover from failures. This is crucial for complex AI applications that need to learn, remember, and adapt over time.
If you're building long-running, stateful AI agents, LangGraph is definitely worth considering.