Mastering RAG Applications: DeepSeek and AMA Embedding Guide
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In this thrilling episode on Krish Naik's channel, viewers are taken on an exhilarating journey into the world of creating an end-to-end RAG application using cutting-edge technology. With the help of DeepSeek and AMA embedding, Krish demonstrates the process of installing these powerful tools locally to unleash their full potential. The sheer excitement of witnessing vectors being generated and stored locally is matched only by the impressive accuracy achieved when interacting with the RAG application. Step by step, Krish dives into the coding intricacies, showcasing the exceptional performance and accuracy of the application.
Viewers are treated to a riveting display of Krish's expertise as he deftly imports essential libraries like PDF plumber and skillfully manipulates PDF content. The meticulous process of text splitting, converting text to embeddings using AMA, and setting up a prompt template for user queries unfolds with precision. Krish's attention to detail is evident as he establishes a document store for PDF uploads, defines crucial paths for PDF storage, and initializes an in-memory vector store. The stage is set for a high-octane demonstration of saving uploaded files, loading PDF documents, and indexing them for efficient retrieval.
With a UI configuration that promises seamless interaction with the RAG application, Krish invites viewers to partake in the excitement of uploading PDFs, executing functions, and witnessing the magic of accurate answer generation. The open-source nature of the application ensures data privacy, adding a layer of trust to the already impressive functionality. As Krish delves into querying about prerequisites and syllabus details from an uploaded PDF, the sheer power and efficiency of the RAG application come to life. This episode is a testament to Krish's prowess in the field, leaving viewers on the edge of their seats with anticipation for the next thrilling installment.
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