Domain-Specific Food Recommendation Intelligence

Engineering MoodBite.Ai

MoodBite is an explainable, constraint-aware culinary recommendation engine designed to regulate psychological states through dietary intervention. Unlike generic LLM wrappers, MoodBite runs a deterministic 12-layer pipeline that combines an Emotional Vector Machine (EVM), clause-level negation parsing, hard constraint safety, and multi-factor ranking—100% locally with zero paid API dependencies.

01 • Not A Chatbot

Intent-Gated Boundaries

MoodBite refuses to hallucinate arbitrary food for off-topic inquiries or gibberish. Every input passes strict intent gates.

02 • Zero Violations

Strict Hard Constraints

Vegetarian, vegan, and allergy filters are strictly deterministic filters, never soft score increments. Forbidden foods are pruned immediately.

03 • Local & Private

<3ms Local Computation

Zero third-party telemetry, zero external token costs, and 100% offline functionality powered by local client & edge execution.

Wellness & System Scope

MoodBite analyzes linguistic markers to suggest comfort and nourishment. It is an ambient wellness recommendation system, not a clinical psychiatric or medical diagnosis tool.

12-Layer System Architecture

LAYER 01P0 Guardrail

Input & Intent Gate

Validates queries before emotion analysis. Categorizes into MOOD, FOOD_REQUEST, GREETING, OFF_TOPIC, or UNKNOWN so random text never triggers hallucinated meals.

LAYER 02NLP Semantics

Clause & Negation Engine

Splits multi-clause sentences at punctuation and contrastive markers ('but', 'however'). Resolves negation scopes ('not sad', 'no longer stressed') accurately.

LAYER 03EVM Vector

Canonical Emotion Ontology

Maps linguistic signals into an 11-class canonical ontology (joy, sadness, anger, fear, stress, calm, excitement, boredom, loneliness, neutral, unknown).

LAYER 04Evidence-Based

Calibrated Confidence

Derives confidence from expert agreement, signal separation, and clause intensity. Low-confidence inputs safely trigger an AMBIGUOUS clarification state.

LAYER 05P0 Safety

Hard Constraint Extraction

Extracts dietary rules (vegetarian, vegan, non-veg, Jain), availability channels (home, market, restaurant, delivery), and spice preferences from query and profile.

LAYER 06Domain Model

Rich Culinary Knowledge

Curated dataset of 25+ rich food profiles featuring mood affinities, nutritional balance, spice profiles, prep times, and availability tags.

LAYER 07Zero Violations

Deterministic Hard Filtering

Strictly eliminates any candidate violating dietary restrictions or availability channels. Vegetarian never receives meat. Hard rules always win.

LAYER 08Deterministic

Multi-Factor Scoring & Ranking

Scores remaining candidates across emotion affinity (0.35), comfort fit (0.20), energy/digestion (0.15), variety bonus (0.10), and user feedback boost (0.10).

LAYER 09Top Choices

Hero & Curated Alternatives

Selects the highest-ranking candidate as Hero recommendation and preserves distinct alternative candidates spanning different preparation avenues.

LAYER 10Transparent

Explainable Chef's Logic

Generates clear, transparent rationales breaking down why the meal was chosen, its physiological intervention, and the emotional vector physics.

LAYER 11Mobile PWA

Adaptive Glassmorphism UI

Renders real-time dynamic ambient lighting reflecting the detected mood, multi-axis vector radar chart, hero cards, and one-click quick starters.

LAYER 12Local-First

Privacy-First Personalization

100% local-first data storage. Taste feedback, mood trajectories, and dietary settings remain in your browser with full anonymous guest mode support.

Evaluation Benchmarks

VERIFIED OFFLINE

Every subsystem change is benchmarked against real linguistic and constraint test suites without using external cloud services.

100.0%
Intent Gate Accuracy
14/14 test cases verified
100.0%
Emotion Classification
12/12 canonical classes
100.0%
Negation Handling
7/7 contrastive & double negations
100.0%
Hard Constraint Safety
0 violations across all diets
< 3 ms
Average Inference Latency
Pure local CPU execution
33 / 33
Automated Unit Tests
Passing in Node.js test runner

Verified Production Test Cases

DETERMINISTIC BEHAVIOR
User QueryMoodIntervention StrategyFood RecommendationExplainability & Gate
"My exam is tomorrow and I haven't studied anything."StressCalming Warmth & FocusMasala Chai / Moong Dal KhichdiContextual academic anxiety detected without direct keywords. Calming warmth lowers cortisol.
"I am not sad at all, actually had a wonderful day!"JoyCelebration & RewardVegetable BiryaniNegation engine resolved 'not sad' and prioritized positive clause 'wonderful day'.
"I'm feeling down and need comfort, but I am strictly vegan."SadnessGrounding ComfortDal Tadka with Steamed RiceHard constraint enforced: dairy/ghee excluded. Warm, protein-rich lentils provide serotonin support.
"I am furious about my flight delay!"AngerSensory ReleaseSpicy Chaat / Pav BhajiHigh-arousal frustration balanced with endorphin-releasing capsicum and bold spices.
"What is Python?"NeutralIntent GuardrailClarification GuideOff-topic gate triggered. Explains culinary scope without hallucinating meals.
"Hey"NeutralGreeting WelcomeInteractive PromptsRecognized conversational greeting. Welcomes user and offers instant starter prompts.
"cxkvkxv"UnknownDisambiguationI Didn't Quite Catch ThatLow lexical entropy detected. Prompts user for clarification without guessing.

Mobile App & Offline PWA

MoodBite.Ai is fully progressive-web-app (PWA) compliant. You can install it on iOS, Android, macOS, and Windows for an app-like experience with instant launch speeds and offline caching.

Cross-Platform PWA v4.0

Install MoodBite.Ai on Your Device

Enjoy instant launch speeds, offline capability, zero battery drain, and full-screen access directly from your phone, tablet, or laptop desktop.

<3ms Engine Offline Ready Local & Private
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