fix(packages/node): update package README and replace NPM_TOKEN with OIDC auth

Author: Gioee

.github/workflows/main.yml

@@ -5,7 +5,7 @@ on:
 
 permissions:
   contents: write
-  # id-token: write  # TODO: Enable after first release for npm provenance with OIDC
+  id-token: write
 
 jobs:
   build:
@@ -328,10 +328,11 @@ jobs:
           node-version: '20'
           registry-url: 'https://registry.npmjs.org'
 
+      - name: update npm # npm 11.5.1 is required for OIDC auth https://docs.npmjs.com/trusted-publishers
+        run: npm install -g [email protected]
+
       - name: build and publish npm packages
         if: steps.tag.outputs.version != ''
-        env:
-          NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}
         run: |
           cd packages/node
 
@@ -377,17 +378,15 @@ jobs:
             platform_name=$(basename "$platform_dir")
             echo "  Publishing @sqliteai/sqlite-vector-${platform_name}..."
             cd "$platform_dir"
-            npm publish --access public
-            # TODO: Add --provenance flag after switching to OIDC (requires package to exist first)
+            npm publish --provenance --access public
             cd ..
             echo "  ✓ Published @sqliteai/sqlite-vector-${platform_name}"
           done
           cd ..
 
           # Publish main package
           echo "Publishing main package to npm..."
-          npm publish --access public
-          # TODO: Add --provenance flag after switching to OIDC (requires package to exist first)
+          npm publish --provenance --access public
           echo "✓ Published @sqliteai/sqlite-vector@${{ steps.tag.outputs.version }}"
 
           echo ""

packages/node/README.md

@@ -1,19 +1,19 @@
 # @sqliteai/sqlite-vector
 
 [![npm version](https://badge.fury.io/js/@sqliteai%2Fsqlite-vector.svg)](https://www.npmjs.com/package/@sqliteai/sqlite-vector)
-[![License](https://img.shields.io/badge/license-Elastic%202.0-blue.svg)](../../../LICENSE.md)
+[![License](https://img.shields.io/badge/license-Elastic%202.0-blue.svg)](LICENSE.md)
 
-> SQLite Vector extension for Node.js - Cross-platform vector embeddings and similarity search
+> SQLite Vector extension packaged for Node.js
 
-**SQLite Vector** brings powerful vector search capabilities to SQLite in Node.js. Perfect for Edge AI, semantic search, RAG applications, and similarity matching - all running locally without external dependencies.
+**SQLite Vector** is a cross-platform, ultra-efficient SQLite extension that brings vector search capabilities to your embedded database. It works seamlessly on **iOS, Android, Windows, Linux, and macOS**, using just **30MB of memory** by default. With support for **Float32, Float16, BFloat16, Int8, and UInt8**, and **highly optimized distance functions**, it's the ideal solution for **Edge AI** applications.
 
 ## Features
 
 - ✅ **Cross-platform** - Works on macOS, Linux (glibc/musl), and Windows
 - ✅ **Zero configuration** - Automatically detects and loads the correct binary for your platform
 - ✅ **TypeScript native** - Full type definitions included
 - ✅ **Modern ESM + CJS** - Works with both ES modules and CommonJS
-- ✅ **Small footprint** - Only downloads binaries for your platform (~30MB)
+- ✅ **Small footprint** - Only downloads binaries for your platform
 - ✅ **Offline-ready** - No external services required
 
 ## Installation
@@ -36,61 +36,16 @@ The package automatically downloads the correct native extension for your platfo
 | Linux | x86_64 (musl/Alpine) | `@sqliteai/sqlite-vector-linux-x86_64-musl` |
 | Windows | x86_64 | `@sqliteai/sqlite-vector-win32-x86_64` |
 
-## Usage
+## sqlite-vector API
+
+For detailed information on how to use the vector extension features, see the [main documentation](https://github.com/sqliteai/sqlite-vector/blob/main/README.md).
 
-### Basic Usage
+## Usage
 
 ```typescript
 import { getExtensionPath } from '@sqliteai/sqlite-vector';
 import Database from 'better-sqlite3';
 
-// Get the path to the vector extension
-const extensionPath = getExtensionPath();
-
-// Load it into your SQLite database
-const db = new Database(':memory:');
-db.loadExtension(extensionPath);
-
-// Use vector functions
-db.exec(`
-  CREATE TABLE embeddings (
-    id INTEGER PRIMARY KEY,
-    vector BLOB,
-    text TEXT
-  );
-`);
-
-// Initialize vector search
-db.prepare("SELECT vector_init('embeddings', 'vector', 'type=FLOAT32,dimension=384')").run();
-
-// Insert vectors (using your embedding model)
-const embedding = new Float32Array(384);
-// ... fill embedding with your model's output
-
-db.prepare('INSERT INTO embeddings (vector, text) VALUES (?, ?)').run(
-  Buffer.from(embedding.buffer),
-  'Sample text'
-);
-
-// Perform similarity search
-const query = new Float32Array(384); // Your query embedding
-const results = db.prepare(`
-  SELECT e.id, e.text, v.distance
-  FROM embeddings AS e
-  JOIN vector_quantize_scan('embeddings', 'vector', ?, 10) AS v
-  ON e.id = v.rowid
-  ORDER BY v.distance ASC
-`).all(Buffer.from(query.buffer));
-
-console.log(results);
-```
-
-### CommonJS
-
-```javascript
-const { getExtensionPath } = require('@sqliteai/sqlite-vector');
-const Database = require('better-sqlite3');
-
 const db = new Database(':memory:');
 db.loadExtension(getExtensionPath());
 
@@ -99,28 +54,9 @@ const version = db.prepare('SELECT vector_version()').pluck().get();
 console.log('Vector extension version:', version);
 ```
 
-### Get Extension Information
-
-```typescript
-import { getExtensionInfo } from '@sqliteai/sqlite-vector';
-
-const info = getExtensionInfo();
-console.log(info);
-// {
-//   platform: 'darwin-arm64',
-//   packageName: '@sqliteai/sqlite-vector-darwin-arm64',
-//   binaryName: 'vector.dylib',
-//   path: '/path/to/node_modules/@sqliteai/sqlite-vector-darwin-arm64/vector.dylib'
-// }
-```
-
 ## Examples
 
-For complete, runnable examples, see the [sqlite-extensions-guide](https://github.com/sqliteai/sqlite-extensions-guide/tree/main/examples/node):
-
-- **[basic-usage.js](https://github.com/sqliteai/sqlite-extensions-guide/blob/main/examples/node/basic-usage.js)** - Generic extension loading for any @sqliteai extension
-- **[semantic-search.js](https://github.com/sqliteai/sqlite-extensions-guide/blob/main/examples/node/semantic-search.js)** - Complete semantic search with OpenAI or on-device embeddings
-- **[with-multiple-extensions.js](https://github.com/sqliteai/sqlite-extensions-guide/blob/main/examples/node/with-multiple-extensions.js)** - Loading multiple extensions together (vector + sync + AI + js)
+For complete, runnable examples, see the [sqlite-extensions-guide](https://github.com/sqliteai/sqlite-extensions-guide/tree/main/examples/node).
 
 These examples are generic and work with all SQLite extensions: `sqlite-vector`, `sqlite-sync`, `sqlite-js`, and `sqlite-ai`.
 
@@ -196,131 +132,23 @@ Detects if the system uses musl libc (Alpine Linux, etc.).
 
 Error thrown when the SQLite Vector extension cannot be found for the current platform.
 
-## Vector Search Guide
-
-For detailed information on how to use the vector search features, see the [main documentation](https://github.com/sqliteai/sqlite-vector/blob/main/README.md).
-
-### Quick Reference
-
-```sql
--- Initialize vector column
-SELECT vector_init('table', 'column', 'type=FLOAT32,dimension=384');
-
--- Quantize vectors for faster search
-SELECT vector_quantize('table', 'column');
-
--- Preload into memory for 4-5x speedup
-SELECT vector_quantize_preload('table', 'column');
-
--- Search for similar vectors
-SELECT * FROM table AS t
-JOIN vector_quantize_scan('table', 'column', <query_vector>, <limit>) AS v
-ON t.rowid = v.rowid
-ORDER BY v.distance;
-```
-
-### Distance Metrics
-
-Specify the distance metric during initialization:
-
-```sql
--- L2 (Euclidean) - default
-SELECT vector_init('table', 'column', 'type=FLOAT32,dimension=384,distance=L2');
-
--- Cosine similarity
-SELECT vector_init('table', 'column', 'type=FLOAT32,dimension=384,distance=COSINE');
-
--- Dot product
-SELECT vector_init('table', 'column', 'type=FLOAT32,dimension=384,distance=DOT');
-
--- L1 (Manhattan)
-SELECT vector_init('table', 'column', 'type=FLOAT32,dimension=384,distance=L1');
-```
-
-## Troubleshooting
-
-### Extension Not Found
-
-If you get `ExtensionNotFoundError`, try:
-
-```bash
-# Force reinstall dependencies
-npm install --force
-
-# Or manually install the platform package
-npm install @sqliteai/sqlite-vector-darwin-arm64  # Replace with your platform
-```
-
-### Platform Not Detected
-
-The package should automatically detect your platform. If detection fails, please [open an issue](https://github.com/sqliteai/sqlite-vector/issues) with:
-- Your OS and architecture
-- Node.js version
-- Output of `node -p "process.platform + '-' + process.arch"`
-
-### Alpine Linux / musl
-
-On Alpine Linux or other musl-based systems, the package automatically detects musl and installs the correct variant. If you encounter issues:
-
-```bash
-# Verify musl detection
-node -e "console.log(require('@sqliteai/sqlite-vector').isMusl())"
-
-# Should print: true
-```
-
-## Development
-
-### Building from Source
-
-```bash
-# Clone the repository
-git clone https://github.com/sqliteai/sqlite-vector.git
-cd sqlite-vector/packages/node
-
-# Install dependencies
-npm install
-
-# Build TypeScript
-npm run build
-
-# Run tests
-npm test
-```
-
-### Project Structure
-
-```
-packages/node/
-├── src/
-│   ├── index.ts                     # Main entry point
-│   ├── platform.ts                  # Platform detection logic
-│   └── index.test.ts                # Test suite
-├── dist/                            # Compiled JavaScript (generated)
-├── generate-platform-packages.js   # Platform package generator
-├── package.json
-├── tsconfig.json
-└── README.md
-```
-
 ## Related Projects
 
-- **[SQLite-AI](https://github.com/sqliteai/sqlite-ai)** - On-device AI inference and embedding generation
-- **[SQLite-Sync](https://github.com/sqliteai/sqlite-sync)** - Sync on-device databases with the cloud
-- **[SQLite-JS](https://github.com/sqliteai/sqlite-js)** - Define SQLite functions in JavaScript
+- **[@sqliteai/sqlite-ai](https://www.npmjs.com/package/@sqliteai/sqlite-ai)** - On-device AI inference and embedding generation
+- **[@sqliteai/sqlite-sync](https://www.npmjs.com/package/@sqliteai/sqlite-sync)** - Sync on-device databases with the cloud
+- **[@sqliteai/sqlite-js](https://www.npmjs.com/package/@sqliteai/sqlite-js)** - Define SQLite functions in JavaScript
 
 ## License
 
-This project is licensed under the [Elastic License 2.0](../../../LICENSE.md).
+This project is licensed under the [Elastic License 2.0](LICENSE.md).
 
 For production or managed service use, please [contact SQLite Cloud, Inc](mailto:[email protected]) for a commercial license.
 
 ## Contributing
 
-Contributions are welcome! Please see the [main repository](https://github.com/sqliteai/sqlite-vector) for contribution guidelines.
+Contributions are welcome! Please see the [main repository](https://github.com/sqliteai/sqlite-vector) to open an issue.
 
 ## Support
 
 - 📖 [Documentation](https://github.com/sqliteai/sqlite-vector/blob/main/API.md)
 - 🐛 [Report Issues](https://github.com/sqliteai/sqlite-vector/issues)
-- 💬 [Discussions](https://github.com/sqliteai/sqlite-vector/discussions)

src/sqlite-vector.h

@@ -24,7 +24,7 @@
 extern "C" {
 #endif
 
-#define SQLITE_VECTOR_VERSION "0.9.46"
+#define SQLITE_VECTOR_VERSION "0.9.47"
 
 SQLITE_VECTOR_API int sqlite3_vector_init (sqlite3 *db, char **pzErrMsg, const sqlite3_api_routines *pApi);