autofaiss
awesome-vector-search
autofaiss | awesome-vector-search | |
---|---|---|
3 | 20 | |
748 | 1,275 | |
1.7% | 2.5% | |
5.6 | 6.1 | |
6 days ago | 21 days ago | |
Python | ||
Apache License 2.0 | MIT License |
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autofaiss
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You Don't Need LangChain;
I might be wrong here. I just know some product quantization techniques, but you can reduce the index by a lot! However, from my research, the more size you reduce, the more retrieval quality is also reduced.
Quoting from https://github.com/criteo/autofaiss
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Cheapest Vector Database
Autofaiss - https://github.com/criteo/autofaiss can be configured to make extremely tiny and efficient indexes.
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Vector database built for scalable similarity search
Don't start with mullivus if you're learning. Too much yak shaving. Try https://github.com/criteo/autofaiss.
Also, TBH, it is a lot cheaper to run a simple faiss index.
awesome-vector-search
- Show HN: SimSIMD vs. SciPy: How AVX-512 and SVE make SIMD cleaner and ML faster
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Reality check on good embedding model (and this idea in general)
Probably. But there are a number of free open source ones. For example, I've got a document that I'm doing embedding-keys for that has about 8000 sentences. Here's a list of some [ https://github.com/currentslab/awesome-vector-search ]
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Rye, meet GPT3 ... and vice versa :)
note: search for vector databases not written in Go but with Go clients, in case there is anything more local/lightweight: https://github.com/currentslab/awesome-vector-search
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Vector database built for scalable similarity search
https://github.com/currentslab/awesome-vector-search
I was surprised to see Elastic actually has ok support for some of this stuff, though it appears slower for most of the tasks.
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[P] My co-founder and I quit our engineering jobs at AWS to build “Tensor Search”. Here is why.
Supporting sequence of vectors does seems like a fresh air to the vector search service. I have added marqo to the list of awesome vector search (disclosure: I am the maintainer of the list) to increase your exposure.
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What are vector search engines?
If you want a proper curated list of various libraries and standalone services of vector search engines, refer to this awesome GitHub repository by Currents API.
- List of vector search libraries
- List of curated vector search libraries
- A GitHub repository that collects awesome vector search framework/engine, library, cloud service, and research papers
- Find anything fast with Google's vector search technology
What are some alternatives?
vespa - AI + Data, online. https://vespa.ai
pgvector - Open-source vector similarity search for Postgres
sqlite-vss - A SQLite extension for efficient vector search, based on Faiss!
annoy - Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk
milvus-lite - A lightweight version of Milvus wrapped with Python.
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
typesense-instantsearch-semantic-search-demo - A demo that shows how to build a semantic search experience with Typesense's vector search feature and Instantsearch.js
Milvus - A cloud-native vector database, storage for next generation AI applications
towhee - Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
hnswlib - Header-only C++/python library for fast approximate nearest neighbors
featureform - The Virtual Feature Store. Turn your existing data infrastructure into a feature store.