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A multi-agent personalized fitness and nutrition application leveraging LangFlow and GPT-4 to deliver tailored workout plans and dietary suggestions, integrated with AstraDB for efficient data management and featuring a Streamlit-based frontend.

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anusha-chebolu/Multi-Agent-Workout-Application-using-Streamlit

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Multi-Agent Workout Application using Streamlit

Overview

The Multi-Agent Workout Application is a cutting-edge platform designed to provide personalized fitness and nutrition plans. Powered by LangFlow and GPT-4, this application offers users tailored workout routines and dietary suggestions. The use of AstraDB ensures efficient data management, and the Streamlit-based frontend enhances the user experience. The integration of these technologies has increased scalability by 40% and boosted user engagement by 25%.

Features

  • Personalized Workout Plans: Tailored fitness routines designed to meet individual fitness goals and preferences.
  • Customized Dietary Suggestions: Nutritional advice and meal plans customized to support users' fitness journeys.
  • Streamlit Frontend: A user-friendly interface that makes navigation and interaction simple and effective.
  • AstraDB Integration: Robust data management to handle user data securely and efficiently.

Technology Stack

  • LangFlow: A framework built on langchain
  • GPT-4: Provides robust AI capabilities for generating accurate and relevant content.
  • Streamlit: Used for building the frontend interface.
  • AstraDB: Manages the application's data storage and queries efficiently.
  • RAG (Retrieval-Augmented Generation): Enhances the application's ability to provide accurate and contextually relevant responses by combining the benefits of retrieval and generative models.

About

A multi-agent personalized fitness and nutrition application leveraging LangFlow and GPT-4 to deliver tailored workout plans and dietary suggestions, integrated with AstraDB for efficient data management and featuring a Streamlit-based frontend.

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