GitHub - bclavie/RAGatouille: Easily use and train state of the art late-interaction retrieval methods (ColBERT) in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.

GitHub - bclavie/RAGatouille: Easily use and train state of the art late-interaction retrieval methods (ColBERT) in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.

github.com
Thumbnail of GitHub - bclavie/RAGatouille: Easily use and train state of the art late-interaction retrieval methods (ColBERT) in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.

Google Search

Matei Zaharia, Omar Khattab, Lingjiao Chen, et al. The Shift From Models to Compound AI Systems

An Overview of Cohere's RAG Connectors (v1 API) — Cohere

docs.cohere.com
Thumbnail of An Overview of Cohere's RAG Connectors (v1 API) — Cohere

A Beginner's Guide to Website Chunking and Embedding for Your RAG Applications - Zilliz Learn

Ruben Winastwanzilliz.com
Thumbnail of A Beginner's Guide to Website Chunking and Embedding for Your RAG Applications - Zilliz Learn

voyage-multimodal-3: all-in-one embedding model for interleaved text, images, and screenshots

Voyage AIblog.voyageai.com
Thumbnail of voyage-multimodal-3: all-in-one embedding model for interleaved text, images, and screenshots

Sahar Mor on Substack

substack.com
Thumbnail of Sahar Mor on Substack