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A vector search SQLite extension that runs anywhere!
cdbc34785f
- fuzz.yaml: embed rpath to Homebrew LLVM's libc++ so macOS binaries can find the right C++ runtime at load time (fixes dyld weak-def crash) - fuzz.yaml: add `make sqlite-vec.h` step on all platforms before building fuzz targets (the header is generated from a template, not checked in) - fuzz.yaml: drop llvm version pin on Windows so choco succeeds when a newer LLVM is already installed on the runner - sqlite-vec.c: change fvec_cleanup / fvec_cleanup_noop to take void* instead of f32* so they are ABI-compatible with vector_cleanup; removes UBSAN indirect-call errors at many call sites - sqlite-vec.c: copy BLOB data into sqlite3_malloc'd buffer in fvec_from_value instead of aliasing the raw blob pointer, fixing UBSAN misaligned-load errors when SQLite hands us an unaligned blob - sqlite-vec.c: guard npy_token_next string scan with ptr < end check before the closing-quote dereference (heap-buffer-overflow) - sqlite-vec.c: clamp vec_quantize_int8 intermediate value to [-128, 127] before casting to i8 (UBSAN out-of-range conversion) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> |
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| .github | ||
| benchmarks | ||
| bindings | ||
| examples | ||
| scripts | ||
| site | ||
| tests | ||
| .gitignore | ||
| ARCHITECTURE.md | ||
| LICENSE-APACHE | ||
| LICENSE-MIT | ||
| Makefile | ||
| README.md | ||
| reference.yaml | ||
| SECURITY.md | ||
| sqlite-dist.toml | ||
| sqlite-vec.c | ||
| sqlite-vec.h.tmpl | ||
| test.sql | ||
| tmp-static.py | ||
| TODO | ||
| VERSION | ||
sqlite-vec
An extremely small, "fast enough" vector search SQLite extension that runs
anywhere! A successor to sqlite-vss
Important
sqlite-vecis a pre-v1, so expect breaking changes!
- Store and query float, int8, and binary vectors in
vec0virtual tables - Written in pure C, no dependencies, runs anywhere SQLite runs (Linux/MacOS/Windows, in the browser with WASM, Raspberry Pis, etc.)
- Store non-vector data in metadata, auxiliary, or partition key columns
sqlite-vec is a
Mozilla Builders project,
with additional sponsorship from
SQLite Cloud, and
Shinkai.
See the Sponsors section for more details.
Installing
See Installing sqlite-vec
for more details.
| Language | Install | More Info | |
|---|---|---|---|
| Python | pip install sqlite-vec |
sqlite-vec with Python |
 |
| Node.js | npm install sqlite-vec |
sqlite-vec with Node.js |
 |
| Ruby | gem install sqlite-vec |
sqlite-vec with Ruby |
 |
| Go | go get -u github.com/asg017/sqlite-vec/bindings/go |
sqlite-vec with Go |
 |
| Rust | cargo add sqlite-vec |
sqlite-vec with Rust |
 |
| Datasette | datasette install datasette-sqlite-vec |
sqlite-vec with Datasette |
 |
| rqlite | rqlited -extensions-path=sqlite-vec.tar.gz |
sqlite-vec with rqlite |
 |
sqlite-utils |
sqlite-utils install sqlite-utils-sqlite-vec |
sqlite-vec with sqlite-utils |
 |
| Github Release |  |
Sample usage
.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!
If your company interested in sponsoring sqlite-vec development, send me an
email to get more info: https://alexgarcia.xyz
See Also
sqlite-ecosystem, Maybe more 3rd party SQLite extensions I've developedsqlite-rembed, Generate text embeddings from remote APIs like OpenAI/Nomic/Ollama, meant for testing and SQL scriptssqlite-lembed, Generate text embeddings locally from embedding models in the.ggufformat