Comment by sebastiennight
Comment by sebastiennight 2 days ago
To clarify, you seem to be asking about end-users storing their (eg. ChatGPT) prompts, not software devs managing the prompts they use in the API?
These are two very different questions.
Comment by sebastiennight 2 days ago
To clarify, you seem to be asking about end-users storing their (eg. ChatGPT) prompts, not software devs managing the prompts they use in the API?
These are two very different questions.
To keep my prompts organized as an end-user, I use an open-source desktop frontend called AnythingLLM [0]. I have a different workspace per use case, and I fork existing threads to continue from prevous prompts.
To keep prompts organized as a software startup is a completely different use-case, as we need: - a way to dynamically fill the prompts (we use Mustache) - a way to store the prompts that enable versioning (so they are on git like the rest of our code) - a way to allow non-technical users (eg. Product team) to revise a prompt, so they are stored as JSON objects.
So our prompts are basically an object that encapsulates the OpenAI-style parameters, plus additional in-house parameters such as fallback model, risk profile, etc.
Both actually, as I think there is a lot of overlap between the use cases. Someone mentioned to me that they recently "graduated" from using the Mac ChatGPT app to something more robust, for example, due to how many prompts they were managing and the systems they were submitting them to. I would also be interested in your perspective why these are vastly different (user prompts vs system prompts), as I might be missing context.