新闻
Building Long-Running Agents with ScaleDown and Deep Agents
LangChain · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- LangChain released langchain-scaledown integration and LangSmith support for ScaleDown's constrained decoding models to optimize long-running agents.
- 为何重要
- Engineers building agents that manage large context windows need cheaper, faster alternatives to frontier LLMs for summarization, compression, and extraction tasks.
- 注意
- ScaleDown models are task-specific and narrower than general LLMs; they excel at constrained tasks but cannot replace the main agent reasoning model.
- agent
- coding model
- constrained decoding
这条新闻背后的模式
每个模式都讲清楚技术如何运作、何时值得投入，以及在哪里会失效。
The Agent Architect
每周一个模式、一个权衡、一个生产事故案例。为构建智能体系统的人准备的每周简报。
每周一封邮件,一键退订。您的地址仅用于发送简报。