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Agri Guard is a full-stack web application that helps farmers identify plant diseases instantly using AI. Users can upload a photo of an affected plant or describe symptoms in text, and the app returns a diagnosis along with a verified treatment plan.
What I built:
A clean, dark-themed landing page with a hero section, trust badges, feature highlights and clear call-to-action buttons (Get Started, Login to Dashboard)
A Node.js and TypeScript backend with REST API routes, utility modules and environment-based configuration
AI integration for image analysis and text-based diagnosis through the OpenRouter API
A disease database with treatment recommendations, plus scripts to extend it with new diseases
Login and dashboard flow for returning users
My focus: a clear, conversion-friendly landing page, readable typography, consistent spacing and a responsive layout that works on both desktop and mobile.
How do you connect the model's diagnosis to the treatment database? Does it have to match a known disease entry before showing a treatment, or can the model generate recommendations outside that list?
Great question, Andrei! It's database-first by design. The model only identifies the disease and returns a confidence score. That label is matched against a curated knowledge base of verified entries (Punjab agriculture institutes, FAO), and the treatment comes from that entry...
Thanks for explaining—that clears it up. Keeping treatment tied to a reviewed database entry makes sense. Appreciate you being clear about what’s already working and what you’re still building. Good luck with the final-year project!
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