AI powered website (AI Nutritionist)

I have mapped out an end-to-end system that detects and segments more than eighty common food classes with YOLOv8-seg and returns calorie estimates in under a second. The architecture is already sketched: a Django REST API backed by SQLite3, a responsive HTML / CSS / JavaScript front end, and automated deployment to Render through CI/CD.

Where I now need support is turning this blueprint into a polished, user-facing product. Users must be able to:

• upload a meal photo and receive an on-screen breakdown of detected items, servings, macros and total calories
• open a nutrition panel for any item to drill into vitamins, allergens and other details
• save each analysis so their meal history accumulates automatically, ready for basic charts and summaries
• schedule a consultation slot and request an AI-assisted personalised meal plan generated from their history

A straightforward email-and-password flow will gate all of this. The computer-vision core is trained and validated; your focus will be clean API endpoints, state management on the front end, and wiring the consultation / meal-plan logic.

Acceptance criteria
1. Endpoints accept JPEG/PNG ≤8 MB, return JSON with classes, masks, weight estimates and calories in ≤1 s on Render’s standard instances.
2. Front-end renders masks as overlays, displays nutrition facts and writes meal logs without page reloads.
3. Meal history, consultation bookings and generated plans persist in SQLite3 and are exposed through paginated REST routes.
4. CI/CD pipeline deploys a tagged commit to Render and passes automated tests for inference speed (<1 s), data integrity and authentication.

Tech stack is fixed to Django 4, YOLOv8, SQLite3, Tailwind (optional), vanilla JS and GitHub Actions, but I’m open to lightweight suggestions that keep deployment simple on Render. Deliver workable, documented code and a short video demo, and we’re done.