Doc Q&A

An AI-powered document analysis system that transforms your documents into an intelligent Q&A interface. Upload PDFs, contracts, papers, and more, then ask questions to get instant AI-powered answers. Built with Next.js 15, TypeScript, and Material UI, integrated with Voltage Park AI Factory.

Features

📄 Document Upload - Support for PDF, DOC, DOCX, and TXT files
🤖 AI-Powered Q&A - Ask questions and get intelligent answers from your documents
🎨 Modern UI - Sleek Material UI design with dark/light mode and green accent colors
📱 Fully Responsive - Optimized for all devices
⚡ Real-time Processing - Live document indexing and vector embedding
🔍 Semantic Search - Intelligent retrieval of relevant document chunks
🌐 Unified Architecture - Single Next.js app with API routes and frontend
📊 Multi-Document Collections - Organize documents into docsets for topic-specific Q&A

Quick Start

Prerequisites

Node.js 18+
npm or yarn
Voltage Park API credentials

Installation

# 1. Clone the repository
git clone <your-repo-url>
cd doc-qa

# 2. Install dependencies
npm install

# 3. Set up environment variables
cp .env.example .env.local
# Edit .env.local with your Voltage Park credentials

# 4. Run the development server
npm run dev

# 5. Open http://localhost:3000

Environment Variables

Create a .env.local file in the root directory:

DOCSETS_API_URL=https://060de239.voltagepark.studio
DOCSETS_BEARER_TOKEN=your-bearer-token

# Optional: Concurrency control (defaults shown)
MAX_CONCURRENT_INGESTIONS=3
MAX_CONCURRENT_GENERATIONS=5

Get your credentials from Voltage Park.

Concurrency Control

The application includes built-in concurrency limiting to prevent server overload:

MAX_CONCURRENT_INGESTIONS (default: 3) - Maximum number of simultaneous document uploads/processing
MAX_CONCURRENT_GENERATIONS (default: 5) - Maximum number of simultaneous answer generations

When limits are reached, requests are automatically queued and processed as capacity becomes available. This ensures fair processing without rejecting requests. Adjust these values based on your server capacity and Voltage Park API rate limits.

Usage

1. Create a Document Collection (Docset)

Give your collection a name and optional description:

"Research Papers"
"Legal Documents"
"User Manuals"

2. Upload Documents

Upload one or more documents (PDF, DOC, DOCX, TXT). The system will:

Extract text content
Chunk the document into semantic sections
Create vector embeddings for semantic search
Index for fast retrieval

3. Ask Questions

Ask natural language questions about your documents:

"What are the main findings?"
"Summarize the key points"
"What does section 3 say about...?"
"Explain the methodology used"

The AI will retrieve relevant context and generate comprehensive answers.

Technology Stack

Next.js 15 - React framework with App Router
React 19 - UI library
TypeScript - Type safety
Material UI v5 - Component library with custom green theme
Emotion - CSS-in-JS styling
Voltage Park AI Factory - Document processing and Q&A generation

Project Structure

doc-qa/
├── app/
│   ├── api/
│   │   ├── docsets/
│   │   │   ├── route.ts                    # POST - Create docset, GET - List docsets
│   │   │   └── [id]/
│   │   │       ├── route.ts                # GET - Get docset details
│   │   │       ├── ingest/route.ts         # POST - Upload document
│   │   │       └── generate/route.ts       # POST - Generate answer
│   │   └── health/route.ts                 # Health check
│   ├── components/
│   │   ├── AnswerCard.tsx                  # Answer display component
│   │   ├── DocumentUpload.tsx              # Document upload component
│   │   ├── Header.tsx                      # App header with branding
│   │   ├── Banner.tsx                      # Voltage Park banner
│   │   ├── Footer.tsx                      # App footer
│   │   ├── ClientLayout.tsx                # Layout wrapper
│   │   └── ThemeRegistry.tsx               # Theme provider
│   ├── lib/
│   │   ├── theme.ts                        # Material UI theme (green accents)
│   │   └── docsets-store.ts                # State management
│   ├── layout.tsx                          # Root layout
│   └── page.tsx                            # Home page with stepper interface
├── public/
│   └── favicon.svg
├── .env.example                            # Environment template
├── next.config.js                          # Next.js config
├── tsconfig.json                           # TypeScript config
└── package.json

API Endpoints

POST /api/docsets

Create a new document collection.

Request:

{
  "name": "Research Papers",
  "description": "Analysis of attention-is-all-you-need paper",
  "factory_id": "default",
  "user_id": "anonymous"
}

Response:

{
  "docset_id": "3da8233a-b11b-4c89-a000-95a97735a512",
  "name": "Research Papers",
  "status": "created"
}

GET /api/docsets

List all document collections.

Response:

{
  "docsets": [
    {
      "docset_id": "3da8233a-b11b-4c89-a000-95a97735a512",
      "name": "Research Papers",
      "description": "Analysis of attention-is-all-you-need paper",
      "status": "ready",
      "document_count": 1,
      "created_at": "2025-11-01T14:20:47.000848"
    }
  ],
  "count": 1
}

POST /api/docsets/:id/ingest

Upload and process a document.

Request: (multipart/form-data)

file: Document file (PDF, DOC, DOCX, TXT)
source_type: Document type (default: "document")
factory_id: Factory ID (default: "default")
doc_tags: Comma-separated tags (optional)

Response:

{
  "doc_id": "878f4019-9a1b-4c93-b1a0-4958212a8786",
  "status": "processed",
  "chunks": 35,
  "vectors": 35,
  "processing_time_ms": 48234
}

POST /api/docsets/:id/generate

Generate an answer to a question about the documents.

Request:

{
  "content_prompt": "What is this paper about?",
  "format_prompt": "Provide a detailed explanation with bullet points",
  "section_label": "Paper Summary",
  "top_k": 8
}

Response:

{
  "docset_id": "3da8233a-b11b-4c89-a000-95a97735a512",
  "generation_id": "1adbcfc0-e5d6-40c6-a11b-e674f183bad6",
  "section_label": "Paper Summary",
  "content": "## Summary\n\nThis paper introduces...",
  "word_count": 339,
  "status": "completed",
  "processing_time_ms": 20931,
  "created_at": "2025-11-01T14:20:47.000848"
}

GET /api/health

Health check endpoint.

Response:

{
  "status": "ok",
  "timestamp": "2025-11-01T...",
  "docsets": 3
}

GET /api/concurrency

Get current concurrency limiter statistics for document ingestion and answer generation.

Response:

{
  "timestamp": "2025-11-02T...",
  "ingestion": {
    "name": "Ingest",
    "maxConcurrent": 3,
    "activeCount": 1,
    "queuedCount": 0,
    "availableSlots": 2,
    "utilizationPercent": 33
  },
  "generation": {
    "name": "Generate",
    "maxConcurrent": 5,
    "activeCount": 2,
    "queuedCount": 1,
    "availableSlots": 3,
    "utilizationPercent": 40
  }
}

Development

# Start development server
npm run dev

# Build for production
npm run build

# Start production server
npm start

# Run linter
npm run lint

Deployment

Deploy to Vercel (recommended):

npm install -g vercel
vercel

Or deploy to:

Netlify
AWS Amplify
Google Cloud Run
Any Node.js hosting platform

Important: Set environment variables (DOCSETS_API_URL and DOCSETS_BEARER_TOKEN) in your hosting platform's dashboard.

Production Notes

The application is designed with a stateless architecture:

Server-Side (Stateless)

Concurrency limiting only - Server only maintains in-memory concurrency queues
Pure API proxy - All requests are forwarded to Voltage Park API
Horizontal scaling - Multiple server instances work independently
No data loss on restart - Client state persists across server restarts

Client-Side State Management

Docsets - Stored in browser memory during session
Generations - Q&A history maintained in React state
Persistence - Consider adding localStorage for session recovery

Additional Production Considerations

Client State Persistence - Add localStorage/IndexedDB for persistent client state
User Authentication - Add login/signup with backend user session management
Rate Limiting - Implement per-user or per-IP rate limits
Monitoring - Add logging and error tracking (e.g., Sentry)
CDN - Deploy static assets to CDN for better performance
Redis (Optional) - For distributed concurrency limiting across multiple servers

API Integration Example

Using the Voltage Park API directly (via curl):

# 1. Create a docset
curl -X POST "https://060de239.voltagepark.studio/docsets/" \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "factory_id": "default",
    "name": "Attention Paper Analysis",
    "metadata": {
      "user_id": "user123",
      "description": "Analysis of attention-is-all-you-need paper"
    }
  }'

# 2. Upload a document
curl -X POST "https://060de239.voltagepark.studio/docsets/DOCSET_ID/ingest" \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -F "file=@paper.pdf" \
  -F "source_type=contract" \
  -F "factory_id=default" \
  -F "doc_tags=paper,attention,nlp"

# 3. Ask a question
curl -X POST "https://060de239.voltagepark.studio/docsets/DOCSET_ID/generate?factory_id=default" \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "content_prompt": "What is this paper about?",
    "top_k": 8
  }'

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License - see LICENSE file for details

Acknowledgments

Powered by Voltage Park AI Factory
UI components from Material UI
Built with Next.js

Questions or issues? Open an issue on GitHub or contact the maintainers.

Navigation Menu

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Doc Q&A

Features

Quick Start

Prerequisites

Installation

Environment Variables

Concurrency Control

Usage

1. Create a Document Collection (Docset)

2. Upload Documents

3. Ask Questions

Technology Stack

Project Structure

API Endpoints

POST /api/docsets

GET /api/docsets

POST /api/docsets/:id/ingest

POST /api/docsets/:id/generate

GET /api/health

GET /api/concurrency

Development

Deployment

Production Notes

Server-Side (Stateless)

Client-Side State Management

Additional Production Considerations

API Integration Example

Contributing

License

Acknowledgments

About

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Contributors

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Name		Name	Last commit message	Last commit date
app		app
public		public
.env.example		.env.example
.eslintrc.json		.eslintrc.json
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
next.config.js		next.config.js
package-lock.json		package-lock.json
package.json		package.json
tsconfig.json		tsconfig.json

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Doc Q&A

Features

Quick Start

Prerequisites

Installation

Environment Variables

Concurrency Control

Usage

1. Create a Document Collection (Docset)

2. Upload Documents

3. Ask Questions

Technology Stack

Project Structure

API Endpoints

POST /api/docsets

GET /api/docsets

POST /api/docsets/:id/ingest

POST /api/docsets/:id/generate

GET /api/health

GET /api/concurrency

Development

Deployment

Production Notes

Server-Side (Stateless)

Client-Side State Management

Additional Production Considerations

API Integration Example

Contributing

License

Acknowledgments

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