I was confused for a bit but there is no relation to https://haystack.deepset.ai/. - Source: Hacker News / about 1 month ago

People like to be on the AI bandwagon, but to have good AI models, you need good LLM (large language models). Welcome to Haystack, it's an end-to-end LLM framework that allows you to build applications powered by LLMs, Transformer models, vector search and more. The latest version is a rewrite of the Haystack framework, and includes a new package, powerful pipelines, customisable components, prompt templating, and... - Source: dev.to / about 2 months ago

Haystack can be classified as an end-to-end framework for building applications powered by various NLP technologies, including but not limited to generative AI. While it doesn't directly focus on building generative models from scratch, it provides a robust platform for:. - Source: dev.to / 6 months ago

But if you want an API that you can use to develop your own flow, Haystack from Deepset could be worth a look. Source: 6 months ago

Haystack for production. We cannot afford breaking changes in our production apps. Its stable, documentation is excellent and did I mention its' STABLE!?? Source: 6 months ago

The focus on the top 10 in vector search is a product of wanting to prove value over keyword search. Keyword search is going to miss some conceptual matches. You can try to work around that with tokenization and complex queries with all variations but it's not easy. Vector search isn't all that new a concept. For example, the annoy library (https://github.com/spotify/annoy), an open source embeddings database. - Source: Hacker News / 9 months ago

If you want to go larger you could still use some simple setup in conjunction with faiss, annoy or hnsw. Source: 11 months ago

I then use annoy to compare them. Annoy can use different measures for distance, like cosine, euclidean and more. Source: 12 months ago

Yes you can do this for equality predicates if your row groups are sorted . This blog post (that I didn't write) might add more color. You can't do this for any kind of text searching. If you need to do this with file based storage I'd recommend using a vector based text search and utilize a ANN index library like Annoy. Source: about 1 year ago

If you need large scale (1000+ dimension, millions+ source points, >1000 queries per second) and accept imperfect results / approximate nearest neighbors, then other people have already mentioned some of the best libraries (FAISS, Annoy). Source: about 1 year ago