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Cohere

Build state-of-the-art RAG and search on your MongoDB data with LLMs from Cohere
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MongoDB and Cohere Overview

MongoDB and Cohere allow you to unlock the potential of your data with Generative AI.

Cohere’s leading embedding and rerank models can be used with MongoDB Atlas vector search to convert your MongoDB data to vectors and build a state-of-the-art semantic search system. Search results can also be passed to Cohere’s Command R series of models for retrieval augmented generation with citations.

Articles & Docs

How to Use Cohere Embeddings and Rerank Modules with MongoDB Atlas
Combine Cohere’s Embed and Rerank models with MondoDB Atlas to build a semantic search system utilizing your MongoDB data.
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How to Index Vector Embeddings for Vector Search
A step-by-step overview on how to conduct semantic search with MongoDB Atlas Vector Search including how to create a vector search index, run vector search queries, and a tutorial on how to run semantic search queries.
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