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Graph-Based Agentic AI with LangGraph: Workflow Pathways for Long-Running Stateful Business Processes
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Researchers published a practitioner guide to LangGraph, a framework for building stateful multi-step AI agents that handle long-running business workflows with explicit state management and routing.
- 为何重要
- Backend engineers building production AI systems need this when orchestrating complex, multi-step processes like SQL repair loops, retrieval-augmented generation, or human-in-the-loop approval workflows.
- 注意
- LangGraph adds overhead; simpler ReAct loops, schema-first tools, or DSPy may be better depending on workflow complexity and whether optimization or structured extraction is the actual goal.
收听本摘要
- agent
- agentic
- retrieval
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