Part 3/6:
After filling in the initial profile, users can enter additional notes which the LLM will consider in future responses. The most compelling feature is the AI query interface, which allows users to ask personalized questions regarding their fitness routines. The LLM uses retrieval-augmented generation to pull relevant data from user notes to create contextually aware and specific workout recommendations.
Technical Implementation Steps
As the article progresses, it describes how to structure the code:
- Setting up the Environment:
Begin by initializing the necessary libraries and packages such as Streamlit and LangFlow.
Users are guided to set up their local environment to run the application.
- Building the AI Workflow with LangFlow: