A Hugging Face Space for personalized weekly diet and exercise planning, integrating modern medical science and Ayurveda for holistic wellness.

Visit Project on Hugging Face

• Personalized Weekly Plans: Custom diet and exercise routines based on your health metrics, goals, and preferences.
• Dynamic Adjustments: Plans adapt to your selected month and local cuisine.
• Dietary Preferences & Allergies: Vegetarian, Vegan, Keto, Halal, and custom allergy support.
• Wearable Integration: Track steps, heart rate, and calorie burn.
• Progress Monitoring: Daily calorie intake vs. burn and weight tracking.
• Food Delivery Integration: Meal suggestions and delivery options from platforms like Uber Eats and DoorDash.
• Ayurvedic Insights: (Planned) Dosha assessment, seasonal herbs, and modern validation.

Main Interface

Plan Example

Food Delivery Integration

Future Implementation

• Frontend: Streamlit
• AI Model: Langchain-Groq (Llama 3)
• Backend: Python
• Integration: dotenv for environment variables, torch for ML support

1. Clone the repository: git clone https://github.com/Abs6187/AI_Health_v2.git cd AI_Health_v2

text 2. Install dependencies: pip install -r requirements.txt

text 3. Set up environment variables:
Create a .env file with your API keys as needed. 4. Run the app: streamlit run app.py

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• Aditi Soni
• Bhumika Patel
• Aditi Lakhera
• Anushri Tiwari

• GitHub Repository
• Presentation
• HackSRIT Hackathon

• Enhanced Ayurvedic insights and dosha recommendations
• Seasonal herbs and spices (Ayurveda)
• Modern medical validation for traditional advice
• Combined holistic wellness tracking