Feature/NutritionSuggestions_GPTCall

[Karmalized]

Feature Implementation: This should help you understand the feature implementation of the GPT section of CalorieMinder:

GPT function calling is a feature that allows chatbots to interact with other systems by calling external APIs. This enables the GPT models to access real-time information or data not included in their training set. Function calling requires the model to output a JSON object containing arguments to call functions. The API must be called twice: once to get the JSON object from the model, and once to send the response to the function call back to the model.

A helpful article: https://semaphoreci.com/blog/function-calling

In essence, construct the bot to call upon functions noted in the sections of Nutrition Suggestions and outsource information from the web in order to broaden and improve the Users ability to make mindful dietary considerations based on the initial prompt or user desire.

Some Objectives:

• Make calls to relevant functions that will provide relevant information that the user seeks based on the initial prompting or request directed toward the AI (Chatbot).
• Provide a coherent, understandable response with relevant data collected from functions called on by the chatbot and possible data outsourced by the AI in order to aid the User on their Nutrition Intake, providing possible suggestions and recommendations based on the response provided by the user on a multitude of nutrition-focused topics and questions.

[BRYC33]

Got a solid framework for calling, prompting, and returning the Chatbot. Only thing needed is an OpenAI API key.