fix node release

Author: nicoloboschi

.github/workflows/release.yml

@@ -41,10 +41,19 @@ jobs:
         with:
           packages-dir: python-api/dist/
 
+      - name: Create GitHub Release
+        uses: softprops/action-gh-release@v1
+        with:
+          files: python-api/dist/*
+          generate_release_notes: true
+
   release-nodejs:
     name: Release Node.js to npm
     runs-on: ubuntu-latest
     if: startsWith(github.ref, 'refs/tags/node-')
+    permissions:
+      id-token: write  # Required for trusted publishing (provenance)
+      contents: read
     steps:
       - uses: actions/checkout@v4
 
@@ -65,11 +74,15 @@ jobs:
           npm run build
 
       - name: Publish to npm
-        env:
-          NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}
         run: |
           cd nodejs-api
-          npm publish --access public
+          npm publish --access public --provenance
+
+      - name: Create GitHub Release
+        uses: softprops/action-gh-release@v1
+        with:
+          files: nodejs-api/dist/*
+          generate_release_notes: true
 
   build-rust-binaries:
     name: Build Rust CLI - ${{ matrix.target }}

RELEASE.md

@@ -49,13 +49,17 @@ PyPI uses **Trusted Publishing** (OIDC), which requires no tokens or passwords:
 
 For more info: https://docs.pypi.org/trusted-publishers/
 
-### 2. npm Token (for Node.js releases)
+### 2. npm Trusted Publishing (for Node.js releases)
 
-1. Log in to npm: `npm login`
-2. Generate a new access token: https://www.npmjs.com/settings/YOUR_USERNAME/tokens
-3. Create a "Automation" token (or "Publish" token)
-4. In your GitHub repository, go to Settings > Secrets and variables > Actions
-5. Create a new secret named `NPM_TOKEN` and paste the token
+npm uses **Provenance** (similar to PyPI's Trusted Publishing), which requires no tokens:
+
+1. Make sure you have publishing rights to the `@vectorize-io/iris` package on npm
+2. The package must already exist on npm (do a manual publish first if needed)
+3. Once published, npm automatically trusts releases from GitHub Actions with `--provenance` flag
+
+**No additional setup required** - npm will automatically verify the GitHub Actions identity using OIDC.
+
+For more info: https://docs.npmjs.com/generating-provenance-statements
 
 ### 3. Update install.sh
 
@@ -142,7 +146,7 @@ npm install vectorize-iris
 
 ### Rust CLI (via install script)
 ```bash
-curl -sSL https://raw.githubusercontent.com/YOUR_USERNAME/vectorize-iris/main/install.sh | bash
+curl -fsSL https://raw.githubusercontent.com/vectorize-io/vectorize-iris/refs/heads/main/install.sh | sh
 ```
 
 Or download binaries directly from the [GitHub Releases page](https://github.com/YOUR_USERNAME/vectorize-iris/releases).
@@ -194,6 +198,7 @@ git push origin py-0.1.0
 cd nodejs-api
 npm run build
 npm publish --access public  # Required for scoped packages (@vectorize-io/iris)
+# Note: Add --provenance flag when publishing from CI for trusted publishing
 
 # Create and push tag
 git tag node-0.2.0

nodejs-api/README.md

@@ -1,20 +1,55 @@
-# Node.js/TypeScript API - Examples
+# Vectorize Iris Node.js SDK
 
-Simple TypeScript library for extracting text from documents using Vectorize Iris.
+**AI-powered document text extraction for Node.js & TypeScript**
 
-## Installation
+Extract text, tables, and structured data from PDFs, images, and documents with a single async function. Built on Vectorize Iris, the industry-leading AI extraction service.
+
+[![npm version](https://badge.fury.io/js/@vectorize-io%2Firis.svg)](https://badge.fury.io/js/@vectorize-io%2Firis)
+[![TypeScript](https://img.shields.io/badge/TypeScript-Ready-blue.svg)](https://www.typescriptlang.org/)
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+
+## Why Iris?
+
+Traditional OCR tools struggle with complex layouts, poor scans, and structured data. Iris uses advanced AI to deliver:
+
+- ✨ **High accuracy** - Even with poor quality or complex documents
+- 📊 **Structure preservation** - Maintains tables, lists, and formatting
+- 🎯 **Smart chunking** - Semantic splitting perfect for RAG pipelines
+- 🔍 **Metadata extraction** - Extract specific fields using natural language
+- 🚀 **TypeScript native** - Full type safety with built-in types
+- ⚡ **Async-first** - Promise-based API for modern Node.js
+
+## Quick Start
+
+### Installation
 
 ```bash
 npm install @vectorize-io/iris
 ```
 
-Set your credentials:
+### Authentication
+
+Set your credentials (get them at [vectorize.io](https://vectorize.io)):
+
 ```bash
 export VECTORIZE_API_TOKEN="your-token"
 export VECTORIZE_ORG_ID="your-org-id"
 ```
 
-## Basic Text Extraction
+### Basic Usage
+
+```typescript
+import { extractTextFromFile } from '@vectorize-io/iris';
+
+const result = await extractTextFromFile('document.pdf');
+console.log(result.text);
+```
+
+That's it! Iris handles file upload, extraction, and polling automatically.
+
+## Features
+
+### Basic Text Extraction
 
 ```typescript
 import { extractTextFromFile } from '@vectorize-io/iris';

python-api/README.md

@@ -1,20 +1,54 @@
-# Python API - Examples
+# Vectorize Iris Python SDK
 
-Simple Python library for extracting text from documents using Vectorize Iris.
+**AI-powered document text extraction for Python**
 
-## Installation
+Extract text, tables, and structured data from PDFs, images, and documents with a single function call. Built on Vectorize Iris, the industry-leading AI extraction service.
+
+[![PyPI version](https://badge.fury.io/py/vectorize-iris.svg)](https://badge.fury.io/py/vectorize-iris)
+[![Python](https://img.shields.io/pypi/pyversions/vectorize-iris.svg)](https://pypi.org/project/vectorize-iris/)
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+
+## Why Iris?
+
+Traditional OCR tools struggle with complex layouts, poor scans, and structured data. Iris uses advanced AI to deliver:
+
+- ✨ **High accuracy** - Even with poor quality or complex documents
+- 📊 **Structure preservation** - Maintains tables, lists, and formatting
+- 🎯 **Smart chunking** - Semantic splitting perfect for RAG pipelines
+- 🔍 **Metadata extraction** - Extract specific fields using natural language
+- ⚡ **Simple API** - One line of code to extract text
+
+## Quick Start
+
+### Installation
 
 ```bash
 pip install vectorize-iris
 ```
 
-Set your credentials:
+### Authentication
+
+Set your credentials (get them at [vectorize.io](https://vectorize.io)):
+
 ```bash
 export VECTORIZE_API_TOKEN="your-token"
 export VECTORIZE_ORG_ID="your-org-id"
 ```
 
-## Basic Text Extraction
+### Basic Usage
+
+```python
+from vectorize_iris import extract_text_from_file
+
+result = extract_text_from_file('document.pdf')
+print(result.text)
+```
+
+That's it! Iris handles file upload, extraction, and polling automatically.
+
+## Features
+
+### Basic Text Extraction
 
 ```python
 from vectorize_iris import extract_text_from_file

rust-cli/README.md

@@ -1,22 +1,64 @@
-# Rust CLI - Examples
+# Vectorize Iris CLI
 
-Beautiful command-line tool for extracting text from documents using Vectorize Iris.
+**⚡ Lightning-fast AI document extraction from your terminal**
 
-## Installation
+A beautiful, cross-platform CLI for extracting text, tables, and structured data from PDFs, images, and documents. Powered by Vectorize Iris AI.
+
+[![Crates.io](https://img.shields.io/crates/v/vectorize-iris.svg)](https://crates.io/crates/vectorize-iris)
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+
+## Why Use the CLI?
+
+- 🎨 **Beautiful output** - Color-coded, formatted terminal display
+- ⚡ **Blazing fast** - Native Rust performance
+- 🔧 **Scriptable** - JSON/YAML output for automation
+- 📦 **Zero dependencies** - Single binary, no runtime needed
+- 🌍 **Cross-platform** - Works on Linux, macOS, and Windows
+- 🔌 **Pipeline-ready** - Perfect for shell scripts and CI/CD
+
+## Quick Start
+
+### Installation
 
 ```bash
-curl -fsSL https://install.vectorize.io/iris | sh
+curl -fsSL https://raw.githubusercontent.com/vectorize-io/vectorize-iris/refs/heads/main/install.sh | sh
 ```
 
-Or install manually from [releases](https://github.com/vectorize/vectorize-iris/releases).
+**Alternative methods:**
+- Download from [GitHub Releases](https://github.com/vectorize-io/vectorize-iris/releases)
+- Install with `cargo install vectorize-iris` (requires Rust)
+
+### Authentication
+
+Set your credentials (get them at [vectorize.io](https://vectorize.io)):
 
-Set your credentials:
 ```bash
 export VECTORIZE_API_TOKEN="your-token"
 export VECTORIZE_ORG_ID="your-org-id"
 ```
 
-## Basic Text Extraction
+### Basic Usage
+
+```bash
+vectorize-iris document.pdf
+```
+
+That's it! Get beautiful, formatted output in your terminal.
+
+## Output Formats
+
+The CLI supports multiple output formats for different use cases:
+
+| Format | Use Case | Command |
+|--------|----------|---------|
+| **Pretty** (default) | Interactive use, beautiful terminal output | `vectorize-iris doc.pdf` |
+| **JSON** | Scripting, piping to `jq` | `vectorize-iris doc.pdf -o json` |
+| **YAML** | Config files, human-readable data | `vectorize-iris doc.pdf -o yaml` |
+| **Text** | Plain text only, no formatting | `vectorize-iris doc.pdf -o text` |
+
+## Examples
+
+### Basic Text Extraction
 
 ```bash
 vectorize-iris document.pdf