https://github.com/asg017/sqlite-vec

Work-in-progress vector search SQLite extension that runs anywhere.
https://github.com/asg017/sqlite-vec

Last synced: about 2 months ago
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Work-in-progress vector search SQLite extension that runs anywhere.

• Host: GitHub
• URL: https://github.com/asg017/sqlite-vec
• Owner: asg017
• License: apache-2.0
• Created: 2024-04-20T20:43:01.000Z (2 months ago)
• Default Branch: main
• Last Pushed: 2024-05-11T07:22:19.000Z (about 2 months ago)
• Last Synced: 2024-05-12T04:17:40.098Z (about 2 months ago)
• Language: C
• Homepage:
• Size: 300 KB
• Stars: 448
• Watchers: 27
• Forks: 6
• Open Issues: 3
• Metadata Files:
  • Readme: README.md

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• awesome-stars - asg017/sqlite-vec - Work-in-progress vector search SQLite extension that runs anywhere. (C)
• my-stars - asg017/sqlite-vec - Work-in-progress vector search SQLite extension that runs anywhere. (C)
• awesome-stars - asg017/sqlite-vec - Work-in-progress vector search SQLite extension that runs anywhere. (C)

README

        
# `sqlite-vec`

An extremely small, "fast enough" vector search SQLite extension that runs

anywhere! A successor to [sqlite-vss](https://github.com/asg017/sqlite-vss)

> [!IMPORTANT]

> *`sqlite-vec` is a work-in-progress and not ready for general usage! I plan to launch a "beta" version in the next month or so. Watch this repo for updates, and read [this blog post](https://alexgarcia.xyz/blog/2024/building-new-vector-search-sqlite/index.html) for more info.*

- Store and query float, int8, and binary vectors in `vec0` virtual tables

- Pre-filter vectors with `rowid IN (...)` subqueries

- Written in pure C, no dependencies,

  runs anywhere SQLite runs (Linux/MacOS/Windows, in the browser with WASM,

  Raspberry Pis, etc.)

## Sample usage

```sql

.load ./vec0

create virtual table vec_examples using vec0(

  sample_embedding float[8]

);

-- vectors can be provided as JSON or in a compact binary format

insert into vec_examples(rowid, sample_embedding)

  values

    (1, '[-0.200, 0.250, 0.341, -0.211, 0.645, 0.935, -0.316, -0.924]'),

    (2, '[0.443, -0.501, 0.355, -0.771, 0.707, -0.708, -0.185, 0.362]'),

    (3, '[0.716, -0.927, 0.134, 0.052, -0.669, 0.793, -0.634, -0.162]'),

    (4, '[-0.710, 0.330, 0.656, 0.041, -0.990, 0.726, 0.385, -0.958]');

-- KNN style query goes brrrr

select

  rowid,

  distance

from vec_examples

where sample_embedding match '[0.890, 0.544, 0.825, 0.961, 0.358, 0.0196, 0.521, 0.175]'

order by distance

limit 2;

/*

┌───────┬──────────────────┐

│ rowid │     distance     │

├───────┼──────────────────┤

│ 2     │ 2.38687372207642 │

│ 1     │ 2.38978505134583 │

└───────┴──────────────────┘

*/

```

## Roadmap

Not currently implemented, but planned in the future (after initial beta version):

- Approximate nearest neighbors search (IVF and HNSW)

- Metadata filtering + custom internal partitioning

- More vector types (float16, int16, sparse, etc.) and distance functions

Additionally, there will be pre-compiled and pre-packaged packages of `sqlite-vec` for the following platforms:

- `pip` for Python

- `npm` for Node.js / Deno / Bun

- `gem` for Ruby

- `cargo` for Rust

- A single `.c` and `.h` amalgammation for C/C++

- Go module for Golang (requires CGO)

- Datasette and sqlite-utils plugins

- Pre-compiled loadable extensions on Github releases

## Support

Is your company interested in sponsoring `sqlite-vec` development? Send me an email to get more info: https://alexgarcia.xyz