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4 giorni fa · Here is a basic overview of the RAG structure: RAG structure, image by the author. The Retriever is part of the system that searches for information relevant to your query (similarly to how you would search in your own wiki, company documents, or on Google).
6 giorni fa · Retrieval Augmented Generation (RAG) is a technique for adding extra “knowledge” to systems built on LLMs, allowing them to answer questions against custom information not included in their training data.
3 giorni fa · Focusing on key Metrics. There is no single metric that can fully capture the functionality of Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) systems. In this document, we...
During data preparation, the RAG application data pipeline takes raw unstructured data and transforms it into discrete chunks that can be queried based on their relevance to a user’s query. The key steps in data preprocessing are outlined below.
These docs cover evaluation in much more detail in Evaluate RAG quality. The article describes the data pipeline and the steps for processing data for retrieval augmented generation (RAG).
This article provides an overview of how you can refine each component to increase the quality of your retrieval augmented generation (RAG) application. There are myriad “knobs” to tune at every point in both the offline data pipeline, and online RAG chain.
4 giorni fa · In this article, we delve into the evolution of Retrieval Augmented Generation (RAG) technique within the LLM ecosystem. As we all know, currently, there are primarily two approaches to inject...
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