AppCraft
Automate.Optimize.Thrive
The problem AppCraft solves
Tech Stack Used:
Frontend:
React.js (UI)
CSS (Styling)
Backend:
FastAPI (API Development)
Python (AI Integration)
AI Model:
Google Gemini API (Generative AI for Code & Descriptions)
Database:
PostgreSQL
Persistent AI-Generated Code Storage
Without a database, every AI-generated app is lost when the page is refreshed.
Solution: The app now stores AI-generated apps in a database, allowing users to revisit their generated projects.
Accessibility to Previously Generated Apps
Users may want to review or reuse old app ideas.
Solution: The app provides a "Saved Apps" section, displaying past AI-generated apps.
Eliminating Repeated API Calls
Without a database, users need to regenerate apps every time they return to the website.
Solution: The app retrieves stored results instantly, reducing unnecessary API calls and improving efficiency.
Scalability for Future Enhancements
A temporary session-based approach doesn't work for multiple users.
Solution: With a PostgreSQL database, we can scale the app for multiple users, storing and managing their AI-generated apps separately.
Enhancing User Experience & Usability
Previously, the app only displayed responses but didn’t save them.
Solution: The user can now search, filter, and manage past AI-generated projects.
Challenges we ran into
AI Response Formatting – Extracting and structuring AI-generated descriptions and code properly.
Database Integration – Designing an efficient schema for storing prompts and responses while ensuring scalability.
Asynchronous Processing – Managing AI requests and database writes without slowing down the app.
CORS Issues – Resolving frontend-backend communication restrictions in FastAPI.
UI/UX Enhancements – Ensuring a responsive, visually appealing interface with proper positioning and styling.
Avoiding Redundant AI Calls – Implementing caching to prevent repeated processing of the same prompt.
Tracks Applied (1)