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Ask HN: What have you built with LLMs?

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221–230 of 349 posts

Re: Ask HN: What have you built with LLMs?

#221

I just built a tool that uses Whisper.cpp compiled to WASM in conjunction with SQLite WASM for a fully client-side book writing tool. Basically, I want to write a book without having to type out the whole thing. I got the dictation idea from an episode of Columbo. It is very much a work in progress and a proof of concept for another writing tool I want to make. https://orderly.cmgriffing.com/ https://github.com/cmgri…

This is awesome! What is the performance like? particularly around WASM compiled Whisper.

Re: Ask HN: What have you built with LLMs?

#222
I'm building a platform where product managers and engineers can build interaction automation with users using small model. The goal is to help people to build LLM for them without deep expertise in DS/ML, train and host the model in their infrastructure, where no data require to be submitted.

Still on progress at https://www.chathip.com/

Re: Ask HN: What have you built with LLMs?

#223
post #66

I am currently building an automatic book generator of Rust source code, in which the LLM will write the description of the code of a whole Rust project. It will be a bot, which will connect to the website, generate descriptions, download them, and create the book. It is very early in the project, 3 days in, but it's going well. https://github.com/pramatias/documentdf

Nice idea, but README is required. Also it can be generated by GPT :)

Re: Ask HN: What have you built with LLMs?

#224
post #106

Wrote an application to find myself a flat in Berlin, scans some rental websites every minute, uses Google Maps API to calculate the distance to my office, and summarizes the rental description with the GPT-4 API, sends it to me via Telegram. I have no time to read all that generic "vibrant neighborhood" stuff :D

Do you mind sharing a github link if it is public.

it isnt.

Re: Ask HN: What have you built with LLMs?

#225
I built a summarizer for drilling reports. Anytime you drill boreholes, whether it's on a drilling platform in the ocean or the middle of the desert or wherever, there's a geologist watching what comes out and writing notes about it. They likely do this multiple times both in the field and a laboratory setting. These notes are paired with logging software which also asks the geologist more quantitative questions sometimes (e.g., on a scale 1 to 5 how many fractures are there). Typically these are written for at least every meter of extracted core/rock/etc. typically you are drilling hundreds or thousands of meters, or more. So you end up with a highly unstructured data set that occasionally someone glances through to find tidbits. Using chatgpt we converted this data into keywords that could then be used to look at depth dependencies of various geological or petrological features of the region.

Re: Ask HN: What have you built with LLMs?

#227

Earlier quoted context omitted.

The costs have dropped significantly months after I created the cost image. Now I use GPT-4 Turbo. This GPT-4 model understand how text adventures work and there is no need to give him known commands. Of course you try even more sophisticated techniques than mine. I tried the ReAct pattern and virtual discussions. So far, he always stumbles at the same place in a critical understanding of the text. And I tried exactl…

You mean at the very end of the game? The game seems like it's only designed to trick you into that very ending :) Are you hoping it will figure out the game based on the context clues? I'm not sure I can find them myself... A long time ago I did some exercises in "classical planning algorithms", which all feel very like the early part of this game. I.e., how do you get ready to leave if you have to shower, and can't…

Yes, that is the first "bad" ending. After that follow just the one relevant context clue and look under the bed. That might be already enough.

I chose this game, because the game just helps you, at the every step, what you have to do next. Not much to try out. Just the narrative changes. One time, you have to go to work and one time you have to flee.

Other text adventures are even more problematic. I saw GPT-4 trying for dozens of steps in the "The Hitchhiker's Guide to the Galaxy" adventure just to turn on the lights. And this just the first command you have to get right in the game.

Re: Ask HN: What have you built with LLMs?

#228
post #66

I am currently building an automatic book generator of Rust source code, in which the LLM will write the description of the code of a whole Rust project. It will be a bot, which will connect to the website, generate descriptions, download them, and create the book. It is very early in the project, 3 days in, but it's going well. https://github.com/pramatias/documentdf

Nice idea, but README is required. Also it can be generated by GPT :)

It is generated in it's entirety by GPT. Well 98% is more like it. By the time it's ready, it will have a README. I will announce it on Reddit /r/rust if you are interested.

Something i want to test, is how much documentation is needed, for the machine to infer the rest of it. Something like, one sentence of human documentation + code, how much can LLM infer and describe the code as accurately as possible. Does it need two sentences? 3? We'll see.

Re: Ask HN: What have you built with LLMs?

#229

We're building a GPT for managing your finances. https://candle.fi/gpt Our backend stack: - AWS - SST - TypeScript Our clients: - Next (web) - Vanilla React Native (mobile) OpenAI's App Store announcement is what got us interested in building w/ LLMs.

Why not show names and faces of the founders? Explain the backstory. Using your service requires users put absolutely enormous trust in you. But there is currently nothing on the site to engender that trust. I would work on that as a priority.

Re: Ask HN: What have you built with LLMs?

#230
post #53
post #42

Earlier quoted context omitted.

So the AI tries to sell to you, or you try to sell to the AI? This sounds very intriguing but I can tell by your README that you're an engineer and not a sales guy - there are no distinct value propositions. But it sounds damn creative as a project.

The AI answers the call and acts as a potential customer. They take on personas to simulate behaviors like difficult or reluctant customers. You then do your pitch, handle objections, etc. At the end you get a transcript that's 'graded' to show you where you could improve your sales approach. And you're right, I'm not a sales guy. This project is for people like me who want a risk-free place to learn the basics of sa…

This, for some reason, reminds me of Nathan Fielder rehearsal skits.
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