Show HN: Automatic prompt optimizer for LLMs(promptperfect.jina.ai) |
Show HN: Automatic prompt optimizer for LLMs(promptperfect.jina.ai) |
I want you to become my prompt master creator, by helping me to create the best possible prompt.
In order to do this we will follow the following process:
- First, you ask me what the prompt is about. I will answer you, and we will go through the next step.
- Based on the answer I gave you, you will generate the following:
- An improved prompt, concise.
- Relevant questions you might have to improve the quality of the prompt.
- We will go through this process repeatedly, with me providing additional information to you, and you updating the prompt to improve it, until I say we are done.So it will give you suggestions that sound plausibility like how we tend to think an AI might work, but there's no reason to expect it to be correct.
For example, latest try had this initial prompt:
> How can I create collisions in Bevy and Rust?
After 4-5 messages back and forth, I ended up with:
> What is the most efficient method to implement 2D collision detection for a large number of constant-radius circles randomly distributed in Bevy and Rust without using third-party tools, focusing on detection only, without any unique properties or attributes affecting the detection process?
Which is much more explicit and targeted to what I initially wanted to do, but didn't write. It ended up helping me implement a Quadtree solution which I don't have any experience with before, but overall it went smoothly.
After failing to improve performance manually, I eventually asked 4 to improve my prompt after explaining the problem and it basically added "Don't assume the existence of any examples".
This makes perfect sense in hindsight, but I had been approaching things from the other direction - directing it to only consider explicit examples in the report, and for some reason that didn't work.
that's because from the point of view of gpt, gpt is always providing is most accurate anwer already, and the only improvement you'd get is in context clarity as defined by gpt understanding of language, which is not bad by itself, but it's not as effective as having gpt fight itself.
Then when you want to use that prompt, you'll open yet another session. Sorry if that was unclear.
> By providing any User Contribution on the Platform, you grant us and our affiliates a perpetual, worldwide, royalty free, fully paid up, license to use, reproduce, modify, create derivative works, perform, display, distribute and process any such User Contributions in order to maintain, improve, enhance, or secure the Platform and any Services provided via the Platform.
Prompts are not code, fine. But are you saying that you'll potentially make use of prompts provided by users?
ChatGPT, where were the causes for WWII?
For each cause
specify the people involved
for each person
print out a brief biographyThe reality of modern business and purpose is morphing into a caricature of itself.
I'm sure there's an LLM somewhere, but is it as simple as a (very specific, elaborate) prompt for each service run through GPT4, or something more specific... like breaking it up with actual code and running the reconstructed bits through a finetuned LLM?
just so you know the automated translations of your website are completely AWFUL
maybe use GPT or deepl to translate it?
Since you claim in that copy to be able to optimize a prompt for a better output it felt like an odd dissonance to read that copy and have that reaction since your product claims to do the opposite. Hope this helps!
$$$
This is extremely similar to the PayPal logo/favicon and could be problematic for your branding (I'm the second user who got confused just in this thread), or could even cause you legal issues.
I suppose you could try asking for shorter examples to provide for a few-shot prompt, could work well in some cases
What I'm trying to say is that that's exactly what it's optimized for. They're predicting what sounds plausible based on all the pre-gpt writing about AI.
But GPT was revolutionary! A lot of the pre-gpt blogspam and reddit comments and fiction and so on was wrong about how AI works in exactly the way you've been socialized to find plausible.
In general plausibility is the wrong metric to evaluate GPT on, and it's wronger than it seems like it should be.
Edit: And in contrast a human trying to write good prompts will have data about how GPT works that they've personally observed, and they'll weigh that data much higher than say Star Trek.
gpt can be layered and made into an agent etc. To do the AB testing or to make prompts longer by adding more end cases as time goes by. But the effects of one single word change are far too complex for gpt base output to understand anything about.