doc updates

reference.yaml

@@ -8,8 +8,8 @@ functions:
   vec_version:
     params: []
     section: meta
-    desc: x
-    example: x
+    desc: Returns a version string of the current `sqlite-vec` version.
+    example: select vec_version();
   vec_debug:
     params: []
     section: meta
@@ -118,4 +118,4 @@ entrypoints:
 compile_options:
   - SQLITE_VEC_ENABLE_AVX
   - SQLITE_VEC_ENABLE_NEON
-  
+

site/using/js.md

@@ -1,5 +1,7 @@
 # Using `sqlite-vec` in Node.js, Deno, and Bun
 
+[![npm](https://img.shields.io/npm/v/sqlite-vec.svg?color=green&logo=nodedotjs&logoColor=white)](https://www.npmjs.com/package/sqlite-vec)
+
 To use `sqlite-vec` in Node.js, Deno or Bun, install the
 [`sqlite-vec` NPM package](https://npmjs.com/package/sqlite-vec) using your
 favorite package manager:
@@ -40,26 +42,55 @@ console.log(`vec_version=${vec_version}`);
 The `load()` function is compatable with
 [`better-sqlite3`](https://github.com/WiseLibs/better-sqlite3),
 [`node-sqlite3`](https://github.com/TryGhost/node-sqlite3),
-[`js:@db/sqlite`](https://jsr.io/@db/sqlite) (Deno), and
+[`jsr:@db/sqlite`](https://jsr.io/@db/sqlite) (Deno), and
 [`bun:sqlite`](https://bun.sh/docs/api/sqlite).
 
 ## Working with vectors in JavaScript
 
-if your vectors are represented as an array of numbers, use
-[Float32Array](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Float32Array),
-use the
+if your vectors are represented as an array of numbers, wrap it in a
+[`Float32Array`](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Float32Array),
+and use
 [`.buffer`](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray/buffer)
-accessor to insert the underlying ArrayBuffer.
+accessor to bind as a parameter to `sqlite-vec` SQL functions.
 
 ```js
-const embedding = new Float32Array([0.1, 0.2, 0.3]);
+// TODO
+const embedding = new Float32Array([0.1, 0.2, 0.3, 0.4]);
 const stmt = db.prepare("INSERT INTO vss_demo VALUES (?)");
 stmt.run(embedding.buffer);
-
+```
 
 ## Node.js
 
+Here's a quick recipe of using `sqlite-vec` with [`better-sqlite3`](https://github.com/WiseLibs/better-sqlite3) in Node.js.
+
+```js
+
+```
+
+See [`simple-node/demo.mjs`](https://github.com/asg017/sqlite-vec/blob/main/examples/simple-node/demo.mjs)
+for a more complete Node.js demo.
+
 ## Deno
 
+Here's a quick recipe of using `sqlite-vec` with [`jsr:@db/sqlite`](https://jsr.io/@db/sqlite) in Deno. It will only work on Deno version `1.44` or greater, because of a bug in previous Deno version.
+
+ Keep in mind, the `better-sqlite3` example above also works in Deno, you just need to prefix the `better-sqlite3` import with `npm:`, like `import * from "npm:better-sqlite3"`.
+
+```ts
+
+```
+
+See [`simple-deno/demo.ts`](https://github.com/asg017/sqlite-vec/blob/main/examples/simple-deno/demo.ts)
+for a more complete Deno demo.
+
 ## Bun
+
+Here's a quick recipe of using `sqlite-vec` with [`bun:sqlite`](https://bun.sh/docs/api/sqlite) in Bun.  The `better-sqlite3` example above also works with Bun.
+
+```ts
+
 ```
+
+See [`simple-bun/demo.ts`](https://github.com/asg017/sqlite-vec/blob/main/examples/simple-bun/demo.ts)
+for a more complete Bun demo.

site/using/python.md

@@ -57,10 +57,20 @@ If your vectors are from `numpy` arrays, the Python SQLite package allows you to
 
 ```python
 import numpy as np
+import sqlite3
+import sqlite_vec
+
+db = sqlite3.connect(":memory:")
+db.enable_load_extension(True)
+sqlite_vec.load(db)
+db.enable_load_extension(False)
+
+db.execute("CREATE VIRTUAL TABLE vec_demo(sample_embedding float[4])")
 
 embedding = np.array([0.1, 0.2, 0.3, 0.4])
-result = db.execute('select vec_length(?)', [embedding.astype(np.float32)]).fetchone()[0]
-print(result) # 4
+db.execute(
+    "INSERT INTO vec_demo(sample_embedding) VALUES (?)", [embedding.astype(np.float32)]
+)
 ```
 
 ## Recipes