Add PDF data extractor demo (#206)

* feat(demo): add PDF data extractor demo with upload and extraction features

* fix(pdf-extraction): improve file cleanup and error handling for PDF uploads

* fix(pdf-extraction): improve file cleanup and error handling for PDF uploads

Author: ilopezluna

demos/extractor/.gitignore

@@ -0,0 +1,20 @@
+# Dependencies
+node_modules/
+package-lock.json
+
+# Upload directory
+uploads/
+
+# Logs
+*.log
+npm-debug.log*
+
+# OS files
+.DS_Store
+Thumbs.db
+
+# IDE
+.vscode/
+.idea/
+*.swp
+*.swo

demos/extractor/README.md

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+# PDF Data Extractor Demo
+
+This demo application allows you to extract structured data from PDF documents using JSON schemas and AI models.
+
+## Features
+
+- 📄 Upload and process PDF files
+- 📋 Define custom JSON schemas for data extraction
+- 🎯 Pre-built schema examples (Invoice, Receipt, Form)
+- 📊 View extracted data with token usage statistics
+- ⚙️ Configurable temperature and model selection
+
+## Prerequisites
+
+Before running this demo, you need:
+
+1. **Node.js** (version 18 or higher)
+2. **Docker Model Runner**
+3. **A suitable AI model** for text extraction
+
+## Setup Instructions
+
+### 1. Enable Docker Model Runner
+
+**Using Docker Desktop:**
+- Open Docker Desktop settings
+- Go to the **AI** tab
+- Select **Enable Docker Model Runner**
+- Enable **host-side TCP support** on port `12434` (default)
+
+For detailed instructions, see the [Docker Model Runner documentation](https://docs.docker.com/ai/model-runner/get-started/#enable-docker-model-runner).
+
+**Using Standalone Docker Engine:**
+TCP support is enabled by default on port `12434`.
+
+#### 2. Pull a Suitable Model
+
+You'll need a model capable of understanding and extracting text. Recommended models:
+
+```bash
+# Pull a general-purpose model
+docker model pull ai/gemma3
+```
+
+To see available models, visit [Docker Hub - AI Models](https://hub.docker.com/r/ai).
+
+## Installation
+
+1. **Navigate to the demo directory:**
+   ```bash
+   cd demos/extractor
+   ```
+
+2. **Install dependencies:**
+   ```bash
+   npm install
+   ```
+
+3. **Start the server:**
+   ```bash
+   npm start
+   ```
+
+   The server will start on `http://localhost:3000`
+
+4. **Open the demo:**
+   Open `demo.html` in your web browser (you can simply double-click the file or serve it with a local server)
+
+## Usage Guide
+
+### Basic Workflow
+
+1. **Configure API Settings**
+   - **Base API URL**: Set to `http://127.0.0.1:12434/engines/v1` for Docker Model Runner
+   - **Model**: Select from available models
+
+2. **Define Your Schema**
+   - Use the provided examples (Invoice, Receipt, Form) or create your own
+   - The schema defines what data to extract from the PDF
+   - Use standard JSON Schema format with `type`, `properties`, etc.
+
+3. **Upload a PDF**
+   - Click "Choose File" and select your PDF document
+   - Supported: Any text-based PDF (not scanned images without OCR)
+   - You can use sample PDFs [invoice.pdf](invoice.pdf)
+
+4. **Extract Data**
+   - Click "Extract Data" button
+   - Wait for processing (may take 10-30 seconds depending on PDF size and model)
+   - View extracted data in the result section