Verity - Legal Document Analyzer

A Next.js application that uses Google Cloud Document AI for OCR and Vertex AI's Gemini model to analyze legal documents and provide AI-powered Q&A functionality.

Features

• PDF Upload: Drag-and-drop PDF upload with file validation
• OCR Processing: Extract text from legal documents using Google Cloud Document AI
• AI Summarization: Generate key points and summaries using Gemini 1.5 Pro
• Interactive Q&A: Ask questions about the document with conversational AI
• Professional UI: Clean, responsive interface optimized for legal document analysis

Prerequisites

1. Google Cloud Project with the following APIs enabled:

   • Document AI API
   • Vertex AI API

2. Document AI Processor: Create a Document AI processor for OCR

   • Go to the Document AI Console
   • Create a new processor (type: "Document OCR")
   • Note the Processor ID

3. Authentication: Set up Google Cloud authentication

   • For local development: Install Google Cloud CLI and run gcloud auth application-default login
   • For production: Use service account keys or workload identity

Setup

1. Clone and install dependencies:

   npm install

2. Environment Configuration:

   cp .env.example .env.local

   Edit .env.local with your values:

   PROJECT_ID=your-google-cloud-project-id
   LOCATION=us-central1
   PROCESSOR_ID=your-document-ai-processor-id

3. Run the development server:

   npm run dev

4. Open the application: Navigate to http://localhost:3000

Usage

1. Upload Document: Drag and drop or click to upload a PDF legal document
2. Wait for Processing: The app will extract text using OCR and generate a summary
3. Review Summary: Read the AI-generated key points and analysis
4. Ask Questions: Use the chat interface to ask specific questions about the document

API Endpoints

• POST /api/extract-text - Extract text from PDF using Document AI
• POST /api/summarize - Generate document summary using Gemini
• POST /api/ask - Answer questions about the document using Gemini

Architecture

• Frontend: Next.js 15 with TypeScript and Tailwind CSS
• OCR: Google Cloud Document AI for PDF text extraction
• AI: Google Vertex AI (Gemini 1.5 Pro) for summarization and Q&A
• Styling: Tailwind CSS with responsive design

Security Notes

• File size limited to 10MB
• Only PDF files accepted
• All processing happens server-side
• No document content is stored permanently

Troubleshooting

Common Issues

1. "Cannot find module" errors: Ensure all dependencies are installed with npm install

2. Authentication errors:

   • Verify Google Cloud authentication is set up
   • Check that your project has the required APIs enabled
   • Ensure the processor ID is correct

3. OCR failures:

   • Verify the PDF contains readable text (not scanned images)
   • Check file size is under 10MB
   • Ensure the Document AI processor is properly configured

4. AI response errors:

   • Verify Vertex AI API is enabled in your project
   • Check that the location supports Gemini models
   • Ensure sufficient quotas for API usage

Development

To run in development mode with detailed error logging:

npm run dev

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

License

This project is licensed under the MIT License.