Personal Fitness Assistant
Developed a Personal Fitness Assistant web app that delivers AI-powered fitness and nutrition guidance tailored to each user. Built using Streamlit, the app collects personal data (like age, weight, activity level, and fitness goals), then connects to Langflow-based AI workflows to generate personalized plans and advice. It integrates Astra DB to store user notes as vector embeddings, enabling semantic search through Retrieval-Augmented Generation (RAG). When users ask fitness-related questions, the system retrieves relevant notes and enriches the AI’s response for more contextual, personalized guidance. The “Ask AI” Langflow workflow uses a multi-LLM setup with an agent architecture. A dedicated LLM first analyzes the query to determine if it requires calculation. If so, it routes the query to an agent equipped with a calculator tool; otherwise, it passes it to a general-purpose LLM for advice. This conditional logic ensures accurate and relevant outputs, demonstrating how AI
About Me
I'm actively honing my skills in generative AI, machine learning, and data analysis as an aspiring data scientist. I'm an expert at turning complicated datasets into useful insights, and I have a strong background in Python. To assist clients in making data-driven decisions, I provide freelancing services in predictive analytics, specialized machine learning solutions, and data visualization. I can address real-world issues and have a significant effect across industries because of my expanding understanding of natural language processing and AI applications.
$ 10 USD/hr
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