AI meal recognition

AI Meal Recognition

A review-first approach to capturing nutrition data using large language models as a proposing layer for local deterministic validation.

What this feature does

Proposes food names and weight estimates from photos or text descriptions.
Matches AI suggestions against the app's local database of foods.
Calculates nutrition totals locally using matched product data.
Provides a manual review interface to edit or reject every entry.

What it does NOT do

It does not provide medical-grade nutrition analysis.
It does not automatically 'know' the caloric density of a specific restaurant dish.
It does not silently save data without your explicit review and confirmation.

The Architecture: Local-First & BYOK

Train Libre uses a "Bring Your Own Key" (BYOK) model. You choose a provider and model; the app handles the orchestration. Your data stays local, and the AI is only called when you trigger a capture.

Recognition is treated as a noisy proposal. Once the AI returns food names and grams, the app runs a deterministic validation pass. It attempts to repair common errors and flags low-confidence matches before you see the result.

Scientific & Technical Limitations

Research into computer-vision-based nutrition estimation highlights several fundamental hurdles that make 100% accuracy impossible for consumer apps:

The Volume Problem: A 2D photo lacks depth information. Studies show that without a reference object or multiple angles, volume error rates typically range from 10% to 30%.

Hidden Ingredients: AI cannot 'see' the oils, butter, or sugar used in preparation. A grilled breast and a sautéed one may look identical but differ significantly in caloric density.

Mixed Dishes: Ingredients in dishes like stir-fries or burritos are often occluded. If the rice is under the curry, the AI will likely underestimate the portion.

Practical Guidance

Treat AI capture as a friction-reduction tool, not a ground truth. Always use the review screen to adjust gram estimates and ensure the matched foods align with what you actually ate.