I Revived My AI-Powered Google Form Generator Using GitHub Copilot
This is a submission for the GitHub Finish-Up-A-Thon Challenge
What I Built
I revived and completed my unfinished project: AI-Powered Google Form Generator — a full-stack web application that creates real Google Forms from natural language prompts using Google Gemini AI.
The original idea started as a small experiment:
“Can AI automatically generate a complete Google Form from a simple text description?”
Initially, the project only supported basic prompt-to-form generation. It worked as a proof of concept, but the user experience was incomplete, the backend structure was messy, and several important features were missing. Eventually, I stopped working on it.
For the GitHub Finish-Up-A-Thon Challenge, I decided to revisit the project and properly finish it by transforming it from a simple AI demo into a more complete workflow platform.
The application now supports:
- 🔐 Google OAuth authentication
- 🧠 AI-powered form generation using Google Gemini
- 📄 PDF and DOCX document-to-form generation
- 🖼️ Image-to-form generation
- ✏️ Editable generated questions
- 📊 Form analytics dashboard
- 📂 User form management dashboard
- 📝 Pre-built form templates
- 🛡️ Secure token handling and validation
- 🐳 Docker-based deployment support
Tech Stack
Frontend
- React 18
- Vite
- TailwindCSS
- Redux Toolkit
- Framer Motion
- Recharts + D3.js
Backend
- Node.js
- Express.js
- Google Gemini API
- Google Forms API
- Supabase PostgreSQL
- Zod validation
- JWT Authentication
GitHub Repository
https://github.com/dpkpaswan/AI-powered-Google-Form-Generator
Demo
🎥 Video Walkthrough
Application Workflow
- Sign in using Google OAuth
- Enter a natural language prompt
- AI generates structured form questions
- Edit or improve generated questions
- Publish directly to Google Forms
- Manage forms and view analytics
Example Prompt
“Create a college symposium registration form with participant details, department selection, workshop preferences, and feedback questions.”
Screenshots
Repository
https://github.com/dpkpaswan/AI-powered-Google-Form-Generator
The Comeback Story
When I first started this project, it was mainly a proof of concept focused on AI-generated forms.
The original version had multiple issues:
- Weak UI and UX
- No form management system
- No analytics support
- Limited backend structure
- Minimal validation
- No document parsing
- No templates
- No deployment setup
- Difficult-to-maintain codebase
Over time, I kept adding ideas without properly finishing the core workflow. The project slowly became harder to maintain and eventually got abandoned.
For this challenge, I focused less on adding random new features and more on improving usability, architecture, reliability, and overall product quality.
Major improvements I made during the revival process:
- Rebuilt the backend using controllers/services architecture
- Added secure Google OAuth integration
- Integrated Supabase for persistent storage
- Added PDF and DOCX parsing support
- Added image-based form generation
- Added editable forms workflow
- Built analytics dashboards using charts
- Improved validation and error handling
- Added reusable templates
- Added Docker deployment support
- Improved overall frontend design and responsiveness
One important lesson from this process was:
Finishing and polishing a project is much harder than starting one.
The biggest improvements were not flashy AI features — they were stability, usability, and better system structure.
My Experience with GitHub Copilot
GitHub Copilot helped me significantly during the rebuilding and cleanup process.
I mainly used Copilot for:
- Refactoring backend services
- Creating API boilerplate
- Improving Express routes and middleware
- Writing reusable utility functions
- Generating validation schemas
- Improving React component structure
- Debugging async logic
- Speeding up repetitive frontend tasks
- Improving documentation
One of the most useful parts was backend refactoring. The earlier version had tightly coupled logic, and Copilot helped accelerate the process of separating business logic into cleaner service layers.
I also used Copilot while improving UI components and simplifying repetitive coding tasks during frontend cleanup.
Instead of treating Copilot as a replacement for development, I used it as a productivity tool to speed up implementation and refactoring while still making the technical decisions manually.
Challenges Faced
Some of the biggest technical challenges were:
- Managing Google OAuth token handling securely
- Integrating the Google Forms API reliably
- Structuring AI-generated question formats consistently
- Parsing uploaded documents correctly
- Maintaining clean architecture while expanding features
- Handling async workflows between AI generation and Google APIs
I also realized that overengineering can easily destroy project momentum. At one point, I was adding too many ideas without stabilizing the core product experience.
This challenge helped me focus on actually finishing the application.
Final Thoughts
This challenge pushed me to revisit an abandoned project and finally complete it properly.
The biggest takeaway for me was:
A polished and usable product matters more than endlessly adding features.
There are still future improvements I want to make, but this challenge helped me transform an unfinished prototype into a much more stable and production-ready application.
Thanks for reading!
This is a submission for the GitHub Finish-Up-A-Thon Challenge