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Document Q&A System with Voyage-Context-3 Embeddings and MongoDB Atlas

On my never-ending quest to find the best embeddings model, I was intrigued to come across Voyage-Context-3 by MongoDB and was excited to give it a try.

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On my never-ending quest to find the best embeddings model, I was intrigued to come across Voyage-Context-3 by MongoDB and was excited to give it a try. This template implements the embedding model on a Arxiv research paper and stores the results in a Vector store. It was only fitting to use Mongo Atlas from the same parent company. This template also includes a RAG-based Q&A agent which taps into the vector store as a test to helps qualify if the embeddings are any good and if this is even not

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