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PROMPT ENGINEERING 已死;使用 DSPY 框架构建 LLM 应用程序.pdf

上传人: 张** 编号:167519 2024-06-15 24页 1.41MB

1、2024 Databricks Inc.All rights reservedPROMPT PROMPT ENGINEERING ENGINEERING ISISDEADDEADA practitioners approach to building LLM AppsA practitioners approach to building LLM AppsPresented June 12,2024Presented June 12,202412024 Databricks Inc.All rights reserved Im a practitioner with over 15 years

2、 of business,technology and data science experience.My primary focus today will be to present methods to help other practitioners.Im not a researcher or affiliated with the amazing folks who do the real work behind the insights and tools were discussing today.I will footnote many sources in this pre

3、sentation-as not to take credit from whom its due.The views expressed and examples are my own.I will not cover any exact use cases from my current or former employers.2HI.IM MATTHI.IM MATTToday well dig into exciting research and tools to build better LLM appsToday well dig into exciting research an

4、d tools to build better LLM apps2024 Databricks Inc.All rights reserved3AGENDAAGENDA1.Why build agents2.Prompting strategies&evaluating prompt quality3.Why I love DSPy framework&using it with Databricks4.Demonstration2024 Databricks Inc.All rights reserved2024 Databricks Inc.All rights reserved4BUIL

5、DING AGENTS BUILDING AGENTS LEVERAGING LEVERAGING LANGUAGE MODELSLANGUAGE MODELS2024 Databricks Inc.All rights reservedDont be fooled,a single LLM call(or RAG)and a magic prompt may get you 80%of the way to a great app,but the last 20%the last 20%require a different approachrequire a different appro

6、achThere will be a future LLM abstraction,years from now,that only requires a single call to a black box.Todays practical Todays practical application of LLMs require application of LLMs require more.more.5THE BLACK BOX APPROACHTHE BLACK BOX APPROACHUsers may see the black box magic and assume we ju

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本文主要介绍了构建大型语言模型应用程序的方法。作者强调,虽然单个大型语言模型调用可能足以实现80%的应用程序效果,但剩下的20%需要采用不同的方法。文章提到了“黑盒方法”和“代理方法”两种策略。黑盒方法依赖于单个模型调用,而代理方法则涉及模型与其他系统和世界的交互。作者认为,代理方法是实现人工智能的真正潜力所在。文章还讨论了提示工程的重要性,以及如何使用DSPy框架和Databricks来优化代理。作者指出,数据是最重要的,大型语料库的扩展对于提高自然语言处理准确性至关重要。文章最后提供了一个关于如何使用DSPy框架在Databricks上设置代理的示例。
"如何构建更好的LLM应用?" "Prompt Engineering真的死亡了吗?" "DSPy框架如何改变LLM应用开发?"
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