Live data from Hacker News

Ask HN: What have you built with LLMs?

news.ycombinator.com

21–30 of 349 posts

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

#21
An automatic video editor.

It should be cheap enough to deploy that it can be applied to relatively low-value content like video meeting recordings, so it can’t spend a lot of expensive GPU time analyzing video frames.

It also needs to be easily customizable for various content verticals and visual styling like branding and graphics overlays.

And everything is meant to be open sourced, so that’s fun!

I wrote about it on my employer’s blog here:

https://www.daily.co/blog/automatic-short-form-video-highlig...

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

#22
I use sponsor block and it's really good, I like that it's community-driven but sometimes it's not available for videos so your solution sounds great.

I consult to a law firm as their founder-in-residence. For fun, I trained Llama 2 on all the non-client data of the firm so that people could ask it questions like "Who are the lawyers in Montreal who litigate American securities laws, what are their email addresses and what time is it where they are?" It's a njs app running on linode.

It's extremely simple, but people seem to find it useful.

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

#23
I've made a couple games, though I am still having a hard time finding the soul of the game in the LLM and haven't released them; there's a historical roleplay game (that I plan to release soon), a storytelling game (the player tells stories to the LLM), a wander-a-world-aimlessly-and-chat game, and I never get further than 50% through the way of murder mystery games, though murder mysteries seem like an excellent structure.

I've built some abstract content development tools, generally focused on building larger content somewhat top-down (defining vibes, then details).

I'm working on a general project helper using the GPT-Vision, voice, and regular GPT. You setup the camera above your workspace, work on paper, and chat with the LLM while you do it. I think there's a lot of potential, but the voice stuff is quite hard to deal with... there's just a ton of stuff happening in parallel, and I find it very hard to code something reliable.

The stack I use is all in the browser, generally Next.js, Preact Signals, and my own code to call into GPT, Whisper, etc. I like having everything available for inspection, and I generally keep all the working bits visible somewhere. (This can be overwhelming when other people see it.)

But I haven't gotten over the deployment hump... the cost and complexity is a challenge. I've used Openrouter.ai recently in a project, and I think if I leaned on that more completely I'd find the release process easier.

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

#24
I don't like selling. I wanted a way to practice cold calling in a realistic way. I set up a phone number you can call and talk to an AI that simulates sales calls.

I ended up using it for more general purpose things because being able to have a hands-free phone call with an AI turned out to be pretty useful.

It's offline now, but here's the code with all the stack and deployment info: https://github.com/kevingduck/ChatGPT-phone/

Edit: forgot to mention this was all running off a $35 raspberry pi.

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

#25
We've made a lot of data tooling things based on LLMs, and are in the process of rebranding and launching our main product.

1. sketch (in notebook, ai for pandas) https://github.com/approximatelabs/sketch

2. datadm (open source, "chat with data", with support for the open source LLMs (https://github.com/approximatelabs/datadm)

3. Our main product: julyp. https://julyp.com/ (currently under very active rebrand and cleanup) -- but a "chat with data" style app, with a lot of specialized features. I'm also streaming me using it (and sometimes building it) every weekday on twitch to solve misc data problems (https://www.twitch.tv/bluecoconut)

For your next question, about the stack and deploy: We're using all sorts of different stacks and tooling. We made our own tooling at one point (https://github.com/approximatelabs/lambdaprompt/), but have more recently switched to just using the raw requests ourselves and writing out the logic ourselves in the product. For our main product, the code just lives in our next app, and deploys on vercel.

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

#26

I am building textool [1] an app that lets you create endpoints using GPT4. The idea is to make it so you can create "actions" for GPT4 assistants easily. - Nextjs - Deno Deploy for hosting the apis - Supabase - postgres / auth - Shadcn I want to use the t3 app stack [2] for v2. It's really MVP, but I want to see if anyone is interested at all before I work on v2: creating gpts that come with databases! [1] https://t…

IMO the Grimoire GPT's success is proof that there is a market for something like this.

Thanks for saying this! Really appreciate it :)

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

#28
An AI agent to answer questions about any github/gitlab repository. www.useadrenaline.com

It does the work of understanding questions in the context of a repo, code snippet, or any programming question in general, and pulls in extra context from the internet with self thought + web searches.

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

#29
I wrote gait, an LLM-powered CLI that sits on top of git and translates natural language commands into git commands. It's open-source: https://github.com/jordanful/gait

I also wrote PromptPrompt, which is a free and extremely light-weight prompt management system that hosts + serves prompts on CDNs for rapid retrieval (plus version history): https://promptprompt.io

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

#30
A “YouTube video subtitles generator” script for Estonian content.

Powered by whisper-timestamped [1] using a model trained by the local tech university TTÜ [2]

And it just… works! (with some tweaks and corrections)

[1] https://github.com/linto-ai/whisper-timestamped

[2] https://huggingface.co/TalTechNLP/whisper-large-et

Post reply on HN