MyFitnessBuddy – AI Fitness Coach
MyFitnessBuddy acts as a 24/7 personal trainer and nutritionist. Unlike static fitness apps, it uses RAG to pull from a vast database of nutritional science and exercise physiology, tailoring every response to the user's specific biometric data, goals, and limitations.
Technology Stack
System Architecture
Vector Database
Azure CosmosDB with vector search capabilities.
LLM Orchestration
Azure Prompt Flow managing OpenAI GPT-4 calls.
Frontend
React Native mobile app (or React web app).
The Challenges
Preventing hallucinations in health and fitness advice.
Handling complex, multi-turn conversations about diet adjustments.
Ensuring low latency in generating comprehensive weekly plans.
The Solutions
Implemented strict RAG boundaries, forcing the LLM to ground its answers exclusively in the retrieved scientific literature context.
Used a specialized conversational memory buffer that summarizes past dietary restrictions.
Pre-computed embeddings for common workout routines to speed up the retrieval process.
Key Results & Metrics
RAG-powered personalization
Azure AI integration
Context-aware health recommendations