My AI PDF Summarizer Web App

Minimal Next.js + Tailwind scaffold that extracts text from PDFs and uses an AI provider to produce a concise summary and key points.

Features

• Single PDF upload (drag-and-drop or file picker)
• Client-side validation (PDF only, < 10MB)
• Server-side PDF text extraction using pdf-parse
• Server-side AI call to OpenAI Chat Completions (configurable via env var)
• 30s timeout for AI requests
• Parses AI output into summary and keyPoints array
• Copy-to-clipboard and download .txt of results

Local setup

1. Install dependencies

npm install

2. Create .env.local from the example and set your API key

cp .env.local.example .env.local
# Edit .env.local and replace the placeholder with your real key

3. Run the dev server

npm run dev

Open http://localhost:3000

Notes

• The API route pages/api/summarize.js decodes the uploaded PDF (base64), extracts text with pdf-parse, builds a prompt, sends it to the configured AI provider, and parses the response. Update the provider integration there if you prefer Claude or another API.
• This scaffold does not persist uploaded PDFs or summaries.

Deployment

Push the repository to GitHub, connect the project to netlify, Vercel or any other web hosting service, and add GOOGLE_API_KEY, OPENAI_API_KEY your dashboard environment variables. It will run npm run build automatically.

TODOs / Next steps

• Improve AI response parsing and edge-case handling
• Add server-side rate limiting
• Add visual polish and accessibility improvements
• Add tests and CI

Security

• Keep API keys out of source control. Do not commit .env.local.

License

This scaffold is provided as-is for educational purposes.