A lot of my friends build their own tools. They hit a problem and just make the thing they want. I wanted to build something for someone else this time, and the answer was sitting right next to me.
My father has wanted to modernize his physical home textile shop for a long time. He's tried a bunch of times, and it always ends the same way: he gives up. When I asked him why, it came down to two things. There are too many product configurations, sizes, and pricing tiers to memorize, and everything feels slow and awkward compared to what he's used to when trying to manually match patterns for customers.
So I built Harmony AI, a browser app that acts as an automated design concierge for our showroom.
The application captures user layout requirements dynamically and structures interior themes in real-time. A few things I designed around his actual store problems:
Only a few inputs at a time.
The lesson from clunky software was simplicity. The tool asks for basic text inputs—Budget, Item Type, and Visual Style—with a simplified visual flow always on screen.
Every selection matches our real catalog.
The interface maps choices directly to verified stock definitions: Bedcovers, Bedsheets, Blankets, Quilts, Carpets, Cushion covers, and Towels.
Elegant visual transparency.
The panels leverage a modern glassmorphism design (backdrop-blur-md, bg-white/70, border-white/30) so a high-quality, cozy bedroom background layers softly underneath, keeping the emphasis on interior aesthetic aesthetics.
Zero local processing stress.
Since running heavy localized installations would completely slow down a basic storefront laptop, the application offloads all complex machine learning tasks securely to the cloud.
Right now, the system handles dynamic, context-aware layout generation across our entire textile portfolio, starting with quick budget filtering and working up through detailed fabric pairings, layer styling, and color coordinate systems.
Then there's the AI part, which runs entirely serverless via API channels.
When I handed it over to him, he actually sat there and worked through it for a while, which felt like a pretty good sign considering every previous attempt at using inventory platforms had ended with him giving up.
He liked the instant styling responses and being able to see high-end design suggestions matching his actual showroom numbers. More importantly, he kept exploring without me having to convince him to.
You'll want a desktop or mobile browser with a steady internet connection to process the real-time cloud data pipelines.
The complete source architecture is fully public, tracking all component configurations and open framework parameters transparently.
The app itself is built using Vite, React, and Tailwind CSS to ensure immediate rendering, zero framework bulk, and fast layout transitions inspired by cinematic, immersive structures like the premium Resn agency style.
To ensure absolute safety for our developer accounts and zero risk of token revocation on public Git platforms, all authentication metrics are handled using a localized environment variable pipeline (.env.local) linked securely via Vite's import.meta.env utilities. This ensures the private access keys stay local to the production engine.
It also caught some fun integration bugs. During early testing, rapid user double-clicking would send overlapping fetch calls, causing the UI text boxes to stutter.
By binding the React states (is) directly to the form actions, the submit engine now cleanly disables itself and displays an animated "Weaving your layout..." sequence until data resolves.
The automated design engine utilizes the open-weight Mistral-7B-Instruct-v0.3 model [Hugging Face].
The frontend builds an asynchronous pipeline communicating directly with the serverless Hugging Face Inference API endpoint [Hugging Face]. Your parameters pass safely to the cloud infrastructure and return clean layout styling profiles instantly.
return_full_text: false and tracking max_new_tokens: 200 to prevent truncation errors while completely filtering prompt repetition out of the final display box.
[SYSTEM CONTEXT]
You are acting as the premium automated interior layout coordinator for "Harmony Home Textiles" based in China Town shopping Complex, Sundhara, Kathmandu, Nepal. Our active showroom specializes in premium Bedcovers, Bedsheets, Blankets, Quilts, Carpets, Cushion covers, and Towels.
[USER PREFERENCES]
- Desired Interior Item: ${productType}
- Target Budget Threshold: ${budget}
- Visual Design Aesthetic & Room Color Notes: ${designStyle}
For this project, it's pretty concrete.
An open-weight model is the reason a customized tool like this can be built for a family business at all.
With a closed, restrictive API, every single layout consultation or product pairing attempt would turn into a paid request, adding server upkeep bills and complex business keys to manage. For a gift meant to help a small storefront digitize permanently, that's a bad fit.
Running open-weight models over public infrastructure nodes means it costs nothing per use, requires no consumer account configurations, and lets a small business leverage enterprise-grade capabilities for free.