Creating a React Wrapper for an LLM Project

One of my recent projects involved building a frontend for a local large language model (LLM) to complement a suite of Analytic tools. This project was my first major undertaking since completing server side and getting through the basics of AI integration. The tools present a clean react based interface with dynamic page generation for hundreds of analytic methodologies.

Each Structured Analytic Technique or SAT is a React component that can be rendered dynamically based on user input. The challenge was to create a wrapper that could handle the state management and API calls without becoming overly complex. I wanted to keep it simple, so I used React’s built-in hooks for state and effects. In a nutshell, I took in a user input, fed it into a strucutred system prompt, then parsed the results back to the user.

While I can't get into too much detail on how I trained the model, I can say that it was an awesome project that T's up a lot of future work. The LLM can now handle complex queries and provide insights based on the structured data it receives. The next step is to integrate this with a more robust backend that can handle larger datasets and more complex queries.