The Golden RAGtriever: Weaviate, OpenAI, Hugging Face, Cohere

Ah, the great digital hunt: sifting through folders, hard drives, or diving into the depths of cloud storages, all in search of ‘that’ one important document.

It’s the same feeling every time... You search for it, and you think to yourself, “IT MUST BE HERE, SOMEWHERE” —and maybe it’s, maybe not, who the !@$# knows, right?

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It’s not just you… from solo hackers to corporate giants: storing, searching and effectively utilizing data in semantic and lexical contexts, is an extremely overwhelming task. Whether it’s over a pile of documents or massive data lakes, the pain is universal.

The modern Retrieval-Augmented Generation (RAG) applications that leverage LLMs are built to soothe some of that pain. These applications let you interact with your data and sources through a chat interface that’s so intuitive, it feels like you’re just having a conversation with a friend. But I think the better part is, the more you talk, the smarter it gets in finding what you need.

The cool people at Weaviate, AI native open-source vector database, recently released Verba, a.k.a. The Golden RAGtriever, an open-source application designed to offer an end-to-end, streamlined, and user-friendly interface for RAG applications.

Right out of the box, it sets up data loaders, embedding models, Weaviate vector database, and OpenAI or Hugging Face…