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misc docs
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6 changed files with 113 additions and 24 deletions
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@ -8,35 +8,71 @@ functions:
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vec_version:
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params: []
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section: meta
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desc: Returns a version string of the current `sqlite-vec` version.
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desc: Returns a version string of the current `sqlite-vec` installation.
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example: select vec_version();
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vec_debug:
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params: []
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section: meta
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desc: x
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example: x
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desc: Returns debugging information of the current `sqlite-vec` installation.
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example: select vec_debug();
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vec_bit:
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params: []
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params: [vector]
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section: constructor
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desc: x
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example: x
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desc: Creates a binary vector from a BLOB.
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example:
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- select vec_bit(X'F0');
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- select subtype(vec_bit(X'F0'));
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- select vec_to_json(vec_bit(X'F0'));
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vec_f32:
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params: []
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params: [vector]
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section: constructor
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desc: x
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example: x
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desc: |
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Creates a float vector from a BLOB or JSON text. If a BLOB is provided,
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the length must be divisible by 4, as a float takes up 4 bytes of space each.
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example:
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- select vec_float32('[.1, .2, .3, 4]');
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- select subtype(vec_float32('[.1, .2, .3, 4]'));
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- select vec_float32(X'AABBCCDD');
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- select vec_to_json(vec_float32(X'AABBCCDD'));
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- select vec_float32(X'AA');
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vec_int8:
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params: []
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params: [vector]
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section: constructor
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desc: x
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example: x
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desc: |
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Creates a 8-bit integer vector from a BLOB or JSON text. If a BLOB is provided,
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the length must be divisible by 4, as a float takes up 4 bytes of space each.
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If JSON text is provided, each element must be an integer between -128 and 127 inclusive.
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example:
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- select vec_int8('[1, 2, 3, 4]');
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- select subtype(vec_int8('[1, 2, 3, 4]'));
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- select vec_int8(X'AABBCCDD');
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- select vec_to_json(vec_int8(X'AABBCCDD'));
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- select vec_int8('[999]');
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vec_add:
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params: []
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params: [a, b]
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section: op
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desc: x
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example: x
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desc: |
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Adds each element in vector `a` with vector `b`, returning a new vector `c`. Both vectors
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must be of the same type, and can only be a `float32` or `int8` vector.
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example: |
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- select vec_add(
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'[.1, .2, .3]',
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'[.4, .5, .6]'
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);
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- |
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select vec_to_json(
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vec_add(
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'[.1, .2, .3]',
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'[.4, .5, .6]'
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)
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);
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- |
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select vec_to_json(
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vec_int8('[1, 2, 3]'),
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vec_int8('[4, 5, 6]')
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)
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vec_length:
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params: []
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section: op
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@ -118,4 +154,5 @@ entrypoints:
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compile_options:
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- SQLITE_VEC_ENABLE_AVX
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- SQLITE_VEC_ENABLE_NEON
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- SQLITE_VEC_OMIT_FS
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@ -48,6 +48,7 @@ const guides = {
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collapsed: true,
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items: [
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{ text: "Performance", link: "/guides/performance" },
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{
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text: "Vector operations",
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items: [
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@ -136,10 +137,16 @@ function sidebar(): DefaultTheme.SidebarItem[] {
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text: "Installation",
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link: "/installation",
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},
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{
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text: "Quick Start",
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link: "/quickstart",
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},
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],
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},
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{
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text: "Features",
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collapsed: true,
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items: [
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{ text: "Vector formats", link: "/vector-formats" },
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{ text: "KNN queries", link: "/knn" },
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{ text: "vec0 virtual vables", link: "/vec0" },
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{ text: "Static blobs", link: "/numpy" },
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],
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},
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{
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@ -24,13 +24,13 @@ binary quantized 8-dimensional vector can be stored in a single byte — one bit
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per element. For 1 million vectors, that would be just `1MB`, a 32x reduction!
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Though keep in mind, you're bound to lose a lot quality when reducing 32 bits of
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information to 1 bit. [Over-sampling and re-scoring](#re-scoring) will help a
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information to 1 bit. [Oversampling and re-scoring](#re-scoring) will help a
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lot.
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The main goal of BQ is to dramatically reduce the size of your vector index,
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resulting in faster searches and less resources. This is especially useful in
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resulting in faster searches with less resources. This is especially useful in
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`sqlite-vec`, which is (currently) brute-force only and meant to run on small
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devices. BQ is an easy low-cost method to make larger vector datasets easy to
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devices. BQ is an easy low-cost method to make larger vector datasets easier to
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manage.
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## Binary Quantization `sqlite-vec`
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@ -41,7 +41,9 @@ element in a given vector, it will apply `0` to negative values and `1` to
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positive values, and pack them into a `BLOB`.
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```sqlite
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select vec_quantize_binary('[-0.73, -0.80, 0.12, -0.73, 0.79, -0.11, 0.23, 0.97]');
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select vec_quantize_binary(
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'[-0.73, -0.80, 0.12, -0.73, 0.79, -0.11, 0.23, 0.97]'
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);
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-- X'd4`
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```
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@ -51,6 +53,9 @@ The single byte `0xd4` in hexadecimal is `11010100` in binary.
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## Demo
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Here's an end-to-end example of using binary quantization with `vec0` virtual
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tables in `sqlite-vec`.
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```sqlite
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create virtual table vec_movies using vec0(
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synopsis_embedding bit[768]
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@ -1,7 +1,21 @@
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# Using `sqlite-vec` in Go
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There are two ways you can embed `sqlite-vec` into Go applications: a CGO option
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for libraries like
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[`github.com/mattn/go-sqlite3`](https://github.com/mattn/go-sqlite3), or a
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WASM-based option with
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[`github.com/ncruces/go-sqlite3`](https://github.com/ncruces/go-sqlite3).
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## Option 1: CGO
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```bash
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go get -u github.com/asg017/sqlite-vec/bindings/go/cgo
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```
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## Option 2: WASM based with `ncruces/go-sqlite3`
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```
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go
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```
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## Working with vectors in Go
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@ -1,7 +1,33 @@
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# Using `sqlite-vec` in Rust
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You can embed `sqlite-vec` into your Rust projects using the official
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[`sqlite-vec` crate](https://crates.io/crates/sqlite-vec).
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```bash
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cargo add sqlite-vec
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```
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The crate embeds the `sqlite-vec` C source code, and uses the
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[`cc` crate](https://crates.io/crates/sqlite-vec) to compile and statically link
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`sqlite-vec` at build-time.
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The `sqlite-vec` crate exposes a single function `sqlite3_vec_init`, which is
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the C entrypoint for the SQLite extension. You can "register" with your Rust
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SQLite library's `sqlite3_auto_extension()` function. Here's an example with
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`rusqlite`:
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```rs
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use sqlite_vec::sqlite3_vec_init;
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use rusqlite::{ffi::sqlite3_auto_extension};
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fn main() {
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unsafe {
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sqlite3_auto_extension(Some(std::mem::transmute(sqlite3_vec_init as *const ())));
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}
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// future database connection will now automatically include sqlite-vec functions!
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}
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```
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A full [`sqlite-vec` Rust demo](#TODO) is also available.
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## Working with vectors in Rust
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