MVP Specification: Mood Recipes for Perimenopause & Menopause (Open-Source AI)Project Overview
This project aims to develop an AI-powered web and mobile app MVP that provides mood-based recipe suggestions for women experiencing perimenopause and menopause. The platform will use open-source AI to generate personalized recipes, provide nutrition advice, and create smart grocery lists based on user-selected moods or symptoms.
The focus is on cost-effective, scalable open-source AI solutions while maintaining high-quality user experience and AI-driven personalization.
1. Core Features & Open-Source AI IntegrationsA. AI Mood-Based Recipe Suggestions
📌 Functionality:
- Users select a mood or symptom (e.g., hot flashes, fatigue, mood swings, anxiety).
- AI provides science-backed recipe recommendations to support hormonal balance.
- Recipes are personalized based on dietary preferences (e.g., vegan, gluten-free).
🛠 Open-Source AI Solution:
- TensorFlow Recommendation System for personalized recipe suggestions.
- Haystack NLP for processing user inputs and generating recommendations.
B. AI Chatbot for Nutrition & Symptom Advice
📌 Functionality:
- Users ask nutrition-related questions and receive evidence-based answers.
- AI suggests ingredients, lifestyle changes, and symptom-specific foods.
- Provides scientific references on nutrition for menopause.
🛠 Open-Source AI Solution:
- Rasa (Open-Source AI Chatbot) for conversational AI.
- BioBERT (Pre-trained Medical NLP Model) for symptom-based responses.
C. Smart Grocery List Generator
📌 Functionality:
- Auto-generates a shopping list from selected recipes.
- Allows users to modify ingredients and quantities.
- Option to integrate affiliate grocery APIs for online shopping.
🛠 Open-Source AI Solution:
- OpenAI Whisper + Tesseract OCR for voice or text-based grocery list creation.
- AutoML Tables (Open-Source Version) for grocery list optimization.
D. User Profiles & AI-Powered Personalization
📌 Functionality:
- Users create profiles to track moods, symptoms, and preferences.
- AI adapts recommendations based on historical selections.
- Users can save favorite recipes and track symptom improvement.
🛠 Open-Source AI Solution:
- FastAPI with PostgreSQL for user data storage.
- Hugging Face Transformers for personalized recommendation learning.
2. Monetization Strategy
💰 Revenue Streams:✅ Affiliate Revenue – Earn commissions from grocery API integrations.✅ Subscription Model – Premium users get custom meal plans & expert insights.✅ Sponsored Content & Brand Partnerships – Featuring menopause-friendly products.
3. Technology Stack (Recommended)
🖥️ Frontend (Web & Mobile App): Vue.js / React (Web) + React Native (iOS & Android).⚙️ Backend: FastAPI (Python) or Node.js (Express).📊 Database: PostgreSQL / Firestore.🧠 AI Integration:
- Rasa (Chatbot).
- TensorFlow Recommender (Recipe Suggestions).
- Hugging Face NLP Models (Personalization & Responses).
4. Development Phases & TimelinePhase 1: Core MVP Development
✅ Web-based AI recipe generator (Mood-based suggestions).✅ AI chatbot for nutrition advice (basic responses).✅ Manual grocery list feature (No API integration yet).
Phase 2: Mobile App & AI Enhancements
🔹 Native iOS & Android App.🔹 AI-powered grocery list with real-time API integration.🔹 Advanced AI personalization for improved recommendations.
5. Scope of Work & Developer Requirements
Proposals should include:✅ Development timeline & milestones.✅ Tech stack & approach.✅ Budget estimate & payment structure.✅ Portfolio & experience with open-source AI applications.