KomangAndika/Improved-RAG-Architecture
Improved RAG Architecture using semantic chunker, query input rewriter, and prompt engineering
This helps developers build more effective Retrieval-Augmented Generation (RAG) applications without needing to run large language models locally. It takes user queries and source documents, processes them using advanced techniques, and outputs more accurate, contextually relevant answers. Developers who want to integrate powerful AI question-answering capabilities into their applications would use this.
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Use this if you are a developer building a RAG application and want to leverage external LLM APIs and sophisticated text processing for better accuracy and retrieval.
Not ideal if you need extremely fast document chunking or prefer to run all components, including the language models, entirely on local hardware.
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Sep 30, 2024
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