Enhance GPT4All with Model Configuration Import/Export and Recall

[Harvester62]

Proposal: Enhance GPT4All with Model Configuration Import/Export and Recall

Hey everyone,

I have an idea that could significantly improve our experience with GPT4All, and I'd love to get your feedback. Currently, I'm running GPT4All on both my personal notebook and my business account at work. However, I've noticed a major inconvenience: there's no easy way to transfer an LLM model's configuration between accounts on the same machine.

This means that whenever we customize our models and later remove them, all the associated settings are lost. This is especially frustrating for models that are manually downloaded and installed, as finding the correct System and Prompt Template can be quite challenging and often requires extensive searching.

To solve this, I propose developing a feature within GPT4All that allows us to save an LLM model's configuration for future use or to import it into another user account on the same machine. This would eliminate the need to manually record settings and streamline our workflow.

Specifically, I'd like the ability to import, export, and recall the following configuration data:

• System Prompt
• Prompt Template
• Context Length

The rationale behind this is that finding the correct syntax for System Prompts can be time-consuming, and context length often depends on local system resources, such as available memory or GPU capabilities.

Implementing a built-in feature for importing, exporting, and recalling model configurations would greatly enhance our experience with GPT4All and simplify the management of multiple models across different user accounts.

What do you think? Would this enhancement be beneficial for the community? I’d love to hear your thoughts, suggestions, and feedback!

Looking forward to your responses!

[onestardao]

Really thoughtful proposal — and yes, totally feel the pain around config loss across user accounts.

I’ve also had to repeatedly reconstruct system prompts and context settings across machines, and it always feels like solving the same puzzle twice. Being able to save/export that configuration would absolutely reduce friction and help avoid silent regressions.

Especially agree on your point about context length — when GPU resources vary, it’s one of the first dials we tweak, and remembering what worked last time shouldn’t rely on memory alone.

Hope this idea gains traction — happy to see others thinking about the ergonomics of LLM workflows at this level!