PDF Analyzer

An intelligent PDF analysis tool that leverages AI to extract, analyze, and provide insights from PDF documents.

Project Structure

pdf-analyzer/
├── api/              # Serverless API endpoints
│   └── health.js     # Health check endpoint
├── public/           # Static files
│   ├── css/          # Stylesheets
│   │   └── styles.css # Main stylesheet
│   └── index.html    # Landing page
├── index.js          # Express server configuration
├── package.json      # Project dependencies
├── vercel.json       # Vercel deployment configuration
└── README.md         # Project documentation

Local Development

1. Install Dependencies

   npm install

2. Environment Variables Create a .env file in the root directory with:

   PORT=3004
   GEMINI_API_KEY=your_api_key_here
   GEMINI_API_ENDPOINT=your_api_endpoint_here
   

3. Start Development Server

   npm run dev

   The server will start on http://localhost:3004

4. View Landing Page

   • Open your browser and navigate to http://localhost:3004
   • You should see the PDF Analyzer landing page
   • The page is responsive and will adapt to different screen sizes
   • When deployed, the landing page will be accessible at https://parsepdf.io

Deployment to Vercel (parsepdf.io)

1. Install Vercel CLI

   npm install -g vercel

2. Configure Domain

   • Log into your Vercel account
   • Add parsepdf.io as a custom domain
   • Configure DNS settings as provided by Vercel

3. Environment Variables Set the following environment variables in your Vercel project settings:

   • GEMINI_API_KEY: Your Google Gemini API key
   • GEMINI_API_ENDPOINT: Your Google Gemini API endpoint

4. Deploy

   vercel

   For production deployment:

   vercel --prod

Environment Variables

Required Variables

• PORT: Server port (default: 3004)
• GEMINI_API_KEY: Your Gemini API key (get it from Google AI Studio)
• NODE_ENV: Environment setting (development/production)

Local Setup

Create a .env file in the root directory:

# Server Configuration
PORT=3004

# Gemini API Configuration
GEMINI_API_KEY=your-api-key

Vercel Deployment

1. Go to your project settings in the Vercel dashboard
2. Navigate to the Environment Variables section
3. Add the required variables:
   • GEMINI_API_KEY
   • GEMINI_API_ENDPOINT
4. Deploy your project to apply the changes

Features

File Upload

The application supports PDF file upload through:

• Drag and drop interface
• Traditional file picker

When a file is selected:

1. The file name and size are displayed
2. Only PDF files are accepted
3. An "Analyze PDF" button appears

Pricing

• Base fee: $1.00 per document
• Per record: $0.10

Testing File Upload

1. Local Testing

   • Start the development server: npm run dev
   • Open http://localhost:3004 in your browser
   • Try uploading a PDF file by: a. Dragging and dropping a PDF onto the upload zone b. Clicking the upload zone and selecting a PDF
   • Verify that:
     • The file name and size are displayed
     • Non-PDF files are rejected
     • The "Analyze PDF" button appears after selection

2. Production Testing

   • Visit the deployed site
   • Perform the same upload tests as above
   • Verify the upload interface is responsive on mobile devices

API Endpoints

Health Check

• GET /api/health: Health check endpoint
  • Returns: { status: 'healthy', timestamp: '...' }

PDF Analysis

• POST /api/analyze: Upload and analyze a PDF file
  • Content-Type: multipart/form-data
  • Body:
    • pdf: PDF file (required)
  • Size Limit: 10MB
  • Returns:

    {
      "success": true,
      "message": "File successfully processed",
      "data": {
        "sessionId": "uuid-v4",
        "filename": "example.pdf",
        "size": 1234567,
        "mimeType": "application/pdf",
        "base64Preview": "...",
        "base64": "full-base64-string"
      }
    }

Testing the API

Using the Web Interface

1. Visit the landing page
2. Upload a PDF file using drag-and-drop or file picker
3. Click "Analyze PDF"
4. Check the response in the UI

Using Postman

1. Create a new POST request to /api/analyze
2. Set the request type to multipart/form-data
3. Add a field named pdf and select a PDF file
4. Send the request
5. Verify the JSON response includes:
   • Success status
   • Session ID
   • Summary of the PDF content
   • Structured data extracted from the PDF

Using cURL

curl -X POST \
  -F "pdf=@/path/to/your/file.pdf" \
  http://localhost:3004/api/analyze

Error Responses

• File too large (>10MB):

  {
    "success": false,
    "message": "File too large"
  }

• Invalid file type:

  {
    "success": false,
    "message": "Only PDF files are allowed"
  }