similarity-search-kit
hnsqlite
| similarity-search-kit | hnsqlite | |
|---|---|---|
| 4 | 6 | |
| 278 | 144 | |
| - | 2.1% | |
| 6.5 | 5.5 | |
| about 1 month ago | 11 months ago | |
| Swift | Python | |
| Apache License 2.0 | Apache License 2.0 |
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similarity-search-kit
- Similarity-search-kit: on-device text embeddings and semantic search in Swift
- Show HN: SimilaritySearchKit – A package for local text embeddings with CoreML
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What Is a Vector Database
How are you guys thinking about the embedding generation side of things? It seems like that part has a generally hefty compute cost before it even gets into the index - I just open sourced a swift package to try to make that part as easy as possible, the example project exports directly to pinecone. https://github.com/ZachNagengast/similarity-search-kit
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I built a knowledge retrieval library in Swift, looking for feedback 🕵️
Check it out here: https://github.com/ZachNagengast/similarity-search-kit
hnsqlite
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LangChain: The Missing Manual
For anyone thinking about applications of langchain and pinecone but who are looking for something more turn-key check out https://jiggy.ai
The core is actually open source as well, allowing you to take your data back out via sqlite and hnswlib (https://github.com/jiggy-ai/hnsqlite)
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I built an open source website that lets you upload large files, such as in-depth novels or academic papers, and ask ChatGPT questions based on your specific knowledge base. So far, I've tested it with long books like the Odyssey and random research papers that I like, and it works shockingly well.
We are built on open core https://github.com/jiggy-ai. Our open source hnsqlite is light weight, easy to use. And best of all, we make it easy for you to get your data out of JiggyBase. You can download a sqlite file that contains your document text data, metadata, embedding vectors, and embedding index. This can be used directly in the open source hnsqlite package.
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What Is a Vector Database
After working through several projects that utilized local hnswlib and different databases for text and vector persistence, I integrated open source hnswlib with sqlite to create an embedded vector search engine that can easily scale up to millions of embeddings. For self-hosted situations of under 10M embeddings and less than insane throughput I think this combo is hard to beat.
https://github.com/jiggy-ai/hnsqlite
- Show HN: Hnsqlite: hnswlib and SQLite integrated for text embedding search
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Faiss: A library for efficient similarity search
Thanks Leobg!
For anyone else: you pass it directly in metadata see https://github.com/jiggy-ai/hnsqlite/blob/main/test/test_col...
What are some alternatives?
chroma - the AI-native open-source embedding database
langchainrb - Build LLM-powered applications in Ruby
pgvector - Open-source vector similarity search for Postgres
NeMo-Guardrails - NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
Victor - What's our vector, Victor? Victor is a toy vector database written in Go.
guidance - A guidance language for controlling large language models. [Moved to: https://github.com/guidance-ai/guidance]
lucene - Apache Lucene open-source search software
annoy - Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk
GPT4Memory
faiss - A library for efficient similarity search and clustering of dense vectors.
raft - RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.