Merge pull request #262 from tursodatabase/upgrade-to-0.4.4

upgrade libsql-js: 0.4.1 -> 0.4.4

CHANGELOG.md

@@ -1,5 +1,9 @@
 # Changelog
 
+## 0.11.0 -- 2024-09-13
+
+-   Upgrade `libsql-js` to latest 0.4.4 version which brings full vector search support for embedded replicas (see vector search documentation here: https://docs.turso.tech/features/ai-and-embeddings)
+
 ## 0.10.0 -- 2024-08-26
 
 -   Add a migrate() API that can be used to do migrations on both schema databases and regular databases. It is mostly dedicated to schema migration tools.

packages/libsql-client-wasm/package.json

@@ -1,6 +1,6 @@
 {
     "name": "@libsql/client-wasm",
-    "version": "0.10.0",
+    "version": "0.11.0",
     "keywords": [
         "libsql",
         "database",
@@ -56,7 +56,7 @@
         "typedoc": "rm -rf ./docs && typedoc"
     },
     "dependencies": {
-        "@libsql/core": "^0.10.0",
+        "@libsql/core": "^0.11.0",
         "@libsql/libsql-wasm-experimental": "^0.0.2",
         "js-base64": "^3.7.5"
     },

packages/libsql-client/examples/sync_vector.js

@@ -0,0 +1,51 @@
+import { createClient } from "@libsql/client";
+import reader from "readline-sync";
+
+async function example() {
+    const config = {
+        url: process.env.URL ?? "file:local.db",
+        syncUrl: process.env.SYNC_URL,
+        authToken: process.env.AUTH_TOKEN,
+    };
+    const db = createClient(config);
+    await db.sync();
+    await db.execute(
+        "CREATE TABLE IF NOT EXISTS movies (title TEXT, embedding FLOAT32(4))",
+    );
+    await db.execute(
+        "CREATE INDEX IF NOT EXISTS movies_idx ON movies (libsql_vector_idx(embedding))",
+    );
+    await db.sync();
+
+    const title = reader.question("Add movie (title): ");
+    const embedding = reader.question(
+        "Add movie (embedding, e.g. [1,2,3,4]): ",
+    );
+
+    await db.execute({
+        sql: "INSERT INTO movies (title, embedding) VALUES (?, vector32(?))",
+        args: [title, embedding],
+    });
+
+    await db.sync();
+
+    const all = await db.execute(
+        "SELECT title, vector_extract(embedding) as embedding FROM movies",
+    );
+    console.info("all movies:");
+    for (const row of all.rows) {
+        console.log(" - " + row.title + ": " + row.embedding);
+    }
+
+    const query = reader.question("KNN query (e.g. [1,2,3,4]): ");
+    const nn = await db.execute({
+        sql: "SELECT title, vector_extract(embedding) as embedding FROM vector_top_k('movies_idx', vector32(?), 2) as knn JOIN movies ON knn.id = movies.rowid",
+        args: [query],
+    });
+    console.info("nearest neighbors:");
+    for (const row of nn.rows) {
+        console.log(" - " + row.title + ": " + row.embedding);
+    }
+}
+
+example();

packages/libsql-client/package.json

@@ -1,6 +1,6 @@
 {
     "name": "@libsql/client",
-    "version": "0.10.0",
+    "version": "0.11.0",
     "keywords": [
         "libsql",
         "database",
@@ -102,10 +102,10 @@
         "lint-staged": "lint-staged"
     },
     "dependencies": {
-        "@libsql/core": "^0.10.0",
+        "@libsql/core": "^0.11.0",
         "@libsql/hrana-client": "^0.6.2",
         "js-base64": "^3.7.5",
-        "libsql": "^0.4.1",
+        "libsql": "^0.4.4",
         "promise-limit": "^2.7.0"
     },
     "devDependencies": {

packages/libsql-core/package.json

@@ -1,6 +1,6 @@
 {
     "name": "@libsql/core",
-    "version": "0.10.0",
+    "version": "0.11.0",
     "keywords": [
         "libsql",
         "database",