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Retrieval Augmented Generation (RAG)
2 articles
- 01
Vector Database - Pinecone
In this article, we delve into Vector Databases by using Pinecone and explore the fundamentals of vector embeddings, indexes, and essential components of these databases. Furthermore, it will provide a guide on setting up a Vector Database on Pinecone, walking through the installation process, obtaining API keys, and initializing client connections.
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Retrieval Augmented Generation (RAG) with Vector Databases
The article delves into Retrieval-Augmented Generation (RAG), which integrates retrieval and generative models to enhance GenAI applications efficiently. It highlights the architecture of RAG, utilizing vector databases for data retrieval and response generation.
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