## Installing
See [Installing `sqlite-vec`](https://alexgarcia.xyz/sqlite-vec/installation.html)
for more details.
| Language | Install | More Info | |
| -------------- | ---------------------------------------------------- | ------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Python | `pip install sqlite-vec` | [`sqlite-vec` with Python](https://alexgarcia.xyz/sqlite-vec/python.html) | [](https://pypi.org/project/sqlite-vec/) |
| Node.js | `npm install sqlite-vec` | [`sqlite-vec` with Node.js](https://alexgarcia.xyz/sqlite-vec/js.html) | [](https://www.npmjs.com/package/sqlite-vec) |
| Ruby | `gem install sqlite-vec` | [`sqlite-vec` with Ruby](https://alexgarcia.xyz/sqlite-vec/ruby.html) |  |
| Go | `go get -u github.com/asg017/sqlite-vec/bindings/go` | [`sqlite-vec` with Go](https://alexgarcia.xyz/sqlite-vec/go.html) | [](https://pkg.go.dev/github.com/asg017/asg017/sqlite-vec-go-bindings/cgo) |
| Rust | `cargo add sqlite-vec` | [`sqlite-vec` with Rust](https://alexgarcia.xyz/sqlite-vec/rust.html) | [](https://crates.io/crates/sqlite-vec) |
| Datasette | `datasette install datasette-sqlite-vec` | [`sqlite-vec` with Datasette](https://alexgarcia.xyz/sqlite-vec/datasette.html) | [](https://datasette.io/plugins/datasette-sqlite-vec) |
| rqlite | `rqlited -extensions-path=sqlite-vec.tar.gz` | [`sqlite-vec` with rqlite](https://alexgarcia.xyz/sqlite-vec/rqlite.html) | [](https://rqlite.io/docs/guides/extensions/) |
| `sqlite-utils` | `sqlite-utils install sqlite-utils-sqlite-vec` | [`sqlite-vec` with sqlite-utils](https://alexgarcia.xyz/sqlite-vec/sqlite-utils.html) | [](https://datasette.io/plugins/datasette-sqlite-vec) |
| Github Release | | |  |
## 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
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 │
└───────┴──────────────────┘
*/
```
## Sponsors
Development of `sqlite-vec` is supported by multiple generous sponsors! Mozilla
is the main sponsor through the new Builders project.
`sqlite-vec` is also sponsored by the following companies:
As well as multiple individual supporters on
[Github sponsors](https://github.com/sponsors/asg017/)!
If your company interested in sponsoring `sqlite-vec` development, send me an
email to get more info: https://alexgarcia.xyz
## See Also
- [**`sqlite-ecosystem`**](https://github.com/asg017/sqlite-ecosystem), Maybe
more 3rd party SQLite extensions I've developed
- [**`sqlite-rembed`**](https://github.com/asg017/sqlite-rembed), Generate text
embeddings from remote APIs like OpenAI/Nomic/Ollama, meant for testing and
SQL scripts
- [**`sqlite-lembed`**](https://github.com/asg017/sqlite-lembed), Generate text
embeddings locally from embedding models in the `.gguf` format
SQLite Cloud.
See the Sponsors section for more details.
