Very cool! But for hard enough problems, prompt engineering is kind of like hyperparameter tuning. It's only a final (and relatively minor) step after building up an effective architecture and getting its modules to work together. DSP provides a high-level abstraction for building these architectures—with LMs and search. And it gets the modules working together on your behalf (e.g., it annotates few-shot demonstratio…
Prompt Engine – Microsoft's prompt engineering library
91–94 of 94 posts
Re: Prompt Engine – Microsoft's prompt engineering library
#92Earlier quoted context omitted.
For the financial applications at finclout I would prefer engineer. Yet for the stable diffusion tasks, I'd prefer designer.
Is your website https://finclout.io/ ? Some very odd behaviour in the animations on the page when you load it (Chrome 109.0.5414.119 on Mac) that you might want to have someone look at.
Re: Prompt Engine – Microsoft's prompt engineering library
#93Very cool! But for hard enough problems, prompt engineering is kind of like hyperparameter tuning. It's only a final (and relatively minor) step after building up an effective architecture and getting its modules to work together. DSP provides a high-level abstraction for building these architectures—with LMs and search. And it gets the modules working together on your behalf (e.g., it annotates few-shot demonstratio…
Re: Prompt Engine – Microsoft's prompt engineering library
#94Interesting. It's almost the exact same structure (although better organized) that I have built in my "AI Programmer" project (also in Node). Which by the way I hope to have a new release within a week or so. I am not mentioning the domain name again until I have the new release because it much, much better than the version I have up now. The core idea is that you need a certain structure in order to deal with the li…
>so you will need to truncate the beginning of the conversation at some point I wrote a little python script to keep track of a running conversation when I started playing with openai's completions API. I keep track of how many tokens the prompt is taking up, and when it gets too close to some configurable threshold, I then have a different prompt to tell the AI to summarize the conversation and any previous summary,…
If you don't mind sharing the code I'd be super interested to see how it works