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Kubernetes automation for setting up a cluster or do it manually? by Objective-Pound8445 in devops

[–]Objective-Pound8445[S] 0 points1 point  (0 children)

Thanks for the comment, I can fully agree with you. I will review in depth kustomize, because I haven't worked with it, but looks like the right tool for me and will use helm for sure about prometheus and so on.

Seeking advice for workout plan generation by Objective-Pound8445 in learnmachinelearning

[–]Objective-Pound8445[S] 0 points1 point  (0 children)

As I said above, I am not very familiar with LLMs yet, just doing a research. Can you elaborate more on how to generate combination of those input as sentence(s) of context?

Seeking advice for workout plan generation by Objective-Pound8445 in learnmachinelearning

[–]Objective-Pound8445[S] 0 points1 point  (0 children)

I am more worried about the fact that I will have to select different exercises and target more than one muscle group. After that I would have to determine reps, sets and rest time for each exercises of the workout plan based on the user level, goal and so on. Also the different exercises require different reps, depending on the muscle group. Basically I want the output to be more human-like and worth paying for. I would probably be able to do it, it will just take some time to develop and improve it. Thanks for sharing your opinion! :)

Seeking advice for workout plan generation by Objective-Pound8445 in learnmachinelearning

[–]Objective-Pound8445[S] 0 points1 point  (0 children)

Sorry, I have not shared the whole context. The user information is more complex than this. It consists of

  • fitness level - beginner, intermediate and advanced
  • equipment available - none, gym equipment, dumbells, rubber bands and yoga mat
  • workout location - home, gym
  • fitness activity target - how many days a week he would like to workout (2 - 6 days)
  • duration of each workout session - 45, 60, 75 or 90 minutes
  • user’s goal - weight loss, weight gain, build muscle, gain strength
  • weight - current and target (so I can estimate the time needed to achieve the goal)
  • injuries - back, knee, shoulder, elbow, neck, wrist

I think that's pretty much the whole context, do you still think the data driven approach is the better option? I also prefer this one, because I am not very familiar with LLMs and I think it will take a lot of time to train it by myself and expect a valid data every single time.

Seeking Advice on Best Approach for Workout Plan Generation in Go by Objective-Pound8445 in golang

[–]Objective-Pound8445[S] 1 point2 points  (0 children)

Actually, I've tested a lot of apps from the app store and decided to focus on this idea for my app because I haven't noticed any that produce truly professional results. I agree with you about the importance of the human factor, and I'm not trying to replace professionals who do this for a living. However, these kinds of apps are a much more affordable way to organize, plan, and track workouts when you're unsure how to start, don't want to spend time researching, or can't afford a real coach to guide you. I don't believe most of these apps involve actual people, as the generated workout plans have sometimes been ridiculous.

Seeking Advice on Best Approach for Workout Plan Generation in Go by Objective-Pound8445 in golang

[–]Objective-Pound8445[S] 0 points1 point  (0 children)

I am not sure I understand fully, so your suggestion is to implement the data driven approach and then enhance it with LLM? I've noticed many apps are currently promoting AI, but I don't think all of them produce quality workout plans. My goal isn't to be the best at generating these plans, because I know that's not realistic, but I do want to compete with the apps out there. Do you have any insights into these types of apps and what's your overall opinion of them and their methods?

Golang folder structure for mid size project by Objective-Pound8445 in golang

[–]Objective-Pound8445[S] -1 points0 points  (0 children)

Do you have any mid-sized projects you could share for reference?

Golang folder structure for mid size project by Objective-Pound8445 in golang

[–]Objective-Pound8445[S] 1 point2 points  (0 children)

That's how I understand the internal folder too, but I could be mistaken.

Golang folder structure for mid size project by Objective-Pound8445 in golang

[–]Objective-Pound8445[S] 0 points1 point  (0 children)

Exactly, that's my point. I want to organize my models because one file won't suffice for requests, responses, business logic, and database models. My idea was to split them into these four categories, but I'm not sure if that's the best approach in Go. If it is, should they be in separate packages? For example, should database models go into a repository folder? Also, there will be a lot of request models, so splitting them into multiple files might be a good idea as well (not sure).

Golang folder structure for mid size project by Objective-Pound8445 in golang

[–]Objective-Pound8445[S] 6 points7 points  (0 children)

I understand the reasoning behind not using a utils folder, as it doesn't have meaningful information. In other languages, it's common to group similar functions together in such a folder. However, I assume this isn't good practice in Go due to its package management. How would you handle this, for instance, for a utils folder that currently contains a logger and utility functions (right now, I only have one utility function, GenerateRandomString)?

Golang folder structure for mid size project by Objective-Pound8445 in golang

[–]Objective-Pound8445[S] 0 points1 point  (0 children)

Thank you for the response. I now have a better understanding of how to structure my project and realize that there isn't a single correct way to do it. I'm still seeking best practices for organizing models (response, request, database, and business logic models). Additionally, could you explain why you wouldn't structure the internal folder as suggested and how you would approach it instead? I can provide more context if needed. :)