原文towardsdatascience.com/evaluating-rag-applications-with-ragas-81d67b0ee31a 一个包含指标和 LLM 生成的数据的框架,用于评估检索-增强生成流程的性能 到目前为止,我们知道为检索增强生成 (RAG) 的应用程序构建概念验证很容易,但要将其实际应用到生产环境中则非常困难。由于 RAG 流程中包含不同的组件,因此要...
Enhancing rag pipelines in haystack: Introducing diversityranker and lostinthemiddleranker. towardsdatascience.com/, 2023. [Borgeaud等人,2022] Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George Bm Van Den Driessche, Jean-Baptiste Lespiau, Bogdan ...
towardsdatascience.com/ 4— 改善预检索 在query到达RAG系统之前,可以通过额外的处理步骤对其进行细化。这些步骤称为预检索:它们优化输入查询,确保系统检索到最相关和高质量的文档。以下是一些需要考虑的主要预检索步骤 : 查询重写 当用户提出问题时,他们往往没有像他们应该的那样清楚地表达自己。他们的意图可能模棱两...
原文链接：https://towardsdatascience.com/visualize-your-rag-data-evaluate-your-retrieval-augmented-ge...
近日,英伟达生成式AI高级解决方案架构师Wenqi Glantz 在 Towards Data Science 发布了一篇文章,梳理了 12 个 RAG 的痛点并给出了相应的解决方案。 检索增强式生成(RAG)是一种使用检索提升语言模型的技术。具体来说,就是在语言模型生成答案之前,先从广泛的文档数据库中检索相关信息,然后利用这些信息来引导生成过程。
RAG OVERVIEW https://opendatascience.com/getting-started-with-multimodal-retrieval-augmented-generation/ What is RAG? RAG is an architectural framework for LLM-powered applications which consists of two main steps: Retrieval. In this stage, the system has the task of retrieving from the provided ...
https://medium.com/data-science-at-microsoft/creating-a-metadata-graph-structure-for-in-memory-optimization-2902e1b9b254 https://neo4j.com/developer-blog/knowledge-graphs-llms-multi-hop-question-answering/ https://medium.com/@haiyangli38602/make-meaningful-knowledge-graph-from-opensource-rebel-mod...
Data Science Journalist & Independent Consultant https://www.linkedin.com/in/thuwarakesh/ END 🔗文中链接🔗 [1]https://unsplash.com/@travelnow_or_crylater?utm_source=medium&utm_medium=referral [2]https://unsplash.com/?utm_source=medium&utm_medium=referral ...
19. Advanced Retrieval-Augmented Generation: From Theory to LlamaIndex Implementation:https://towardsdatascience.com/advanced-retrieval-augmented-generation-from-theory-to-llamaindex-implementation-4de1464a9930 20. RAGFlow:https://github.com/infiniflow/ragflow ...
Bio: Laurie Voss is VP of Developer Relations at LlamaIndex, the framework for connecting your data to LLMs. He has been a developer for 27 years and was co-founder of npm, Inc.. He believes passionately in making the web bigger, better, and more accessible for everyone. ...