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Best way to map user questions to code functions

Optimizing User Queries for Code Functionality in Interactive 3D Models

Hello, fellow developers!

I’m currently working on an exciting project that involves integrating ChatGPT with a 3D model viewer. The primary objective of this integration is to enable users to interact with the model through natural language, allowing them to ask questions like “Can you show me room 102?” and have that specific area highlighted within the viewer.

While I have started to lay the groundwork for this interaction, I’m concerned that my current approach may not be as robust as it could be. At present, I’ve implemented an initial prompt that instructs the model to respond with an array of IDs whenever a user includes the phrase “show me” in their query. This should, in theory, trigger a corresponding function on the front end to isolate and display the requested room.

However, I feel that there might be better or more efficient methods for mapping user inquiries to the relevant code functions. I would greatly appreciate any insights, suggestions, or creative ideas to improve this functionality. Your expertise could help enhance the user experience significantly!

Thanks in advance for your help! 🙏

One response to “Best way to map user questions to code functions”

  1. GAIadmin Avatar
    GAIadmin

    Hello! This sounds like a fantastic project, and I can see how enhancing user interaction with 3D models using natural language can significantly improve user experience.

    One approach you might consider is implementing a more sophisticated natural language understanding (NLU) framework alongside ChatGPT. By leveraging tools like spaCy or Rasa, you could train a model to better recognize intent and entities based on user queries. For instance, you could define user intents not just for requests like “show me,” but also for contextually varied commands such as “highlight room 102,” “what’s in room 102?” or “zoom into room 102.”

    In addition, consider creating a mapping of common phrases and their corresponding actions in a structured format, such as JSON. This could allow for easier updates and maintenance as your application scales. With a clear intent action mapping, you can directly link user queries to specific functions more intuitively, reducing the need for complex logic in interpreting their queries.

    Lastly, enabling a feedback loop where users can refine or clarify their requests could also enhance the interaction. For example, if a user asks about a room that doesn’t exist, your system could prompt them with suggestions or confirm their intent based on similar room names.

    Best of luck with your project, and I look forward to seeing how you bring this innovative idea to life!

    Reply

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