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Ask HN: What have you built with LLMs?

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

#171

Post by pseudosavant »

joetann wrote: post #165

I’ve always found podcast discovery to be lacking, so I’m building the ultimate solution to that. We’re processing the top podcasts in many genres every day (currently thousands of daily episodes) and running them through our pipeline. From this we’ve made a semantic search engine, for example: https://www.podengine.ai/podcasts/search?search_term=Should+... We’re soon going to improve and summarise the responses from…

I really like the idea of using embeddings in this way. I'm sure scaling out to get "most" of the podcasts is no joke. But some bigger podcasts like Smartless didn't seem to be in your database.

Have you considered using embeddings to show similar podcasts?

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

#172

Post by DrNosferatu »

duckkg5 wrote: post #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/C…

Now do it for dating practice - great for nerds ;)

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

#173

Post by pseudosavant »

joshelgar wrote: post #121

1. An infinite crafting game: https://foodformer.com 2. An embeddings-based job search engine: https://searchflora.com 3. I used LLMs to caption a training set of 1 million Minecraft skins, then finetuned Stable Diffusion to generate minecraft skins from a prompt: https://multi.skin

I love the skin generator

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

#174

Post by gremlinsinc »

adrianmonk wrote: post #136
callmeed wrote: post #110

I'm building a weight-loss app that leverages LLM to do 2 things: 1. Analyze calories/macronutrients from a text description or photo 2. Provide onboarding/feedback/conversations like you'd get from a nutritionist https://www.fatgpt.ai/ My stack is Ruby on Rails, PostgreSQL, OpenAI APIs. I chose Rails because I'm very fast in it, but I've found the combination of Rails+Sidekiq+ActionCable is really nice for building…

fatGPT... the LLM that helps you be more model, less large.

our large language model is large so you don't have to be.

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

#175

Post by spywaregorilla »

duckkg5 wrote: post #53
dsco wrote: 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…

do you have any reason to believe the phone calls are realistic?

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

#177

Post by dvcrn »

Lots of small stuff like bots and scripts to automatically rename files that I use locally every single day

Then things like:

“Fix My Japanese” - uses LLM to correct Japanese grammar (built with Elixir LiveView): https://fixmyjapanese.com

It has different “Senseis” that are effectively different LLMs, each with slightly different style. One is Claude, one is ChatGPT.

Or a slack bot that summarizes long threads:

https://github.com/dvcrn/slack-thread-summarizer

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

#178

Post by instagary »

reality_swim wrote: post #166
instagary wrote: post #161

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.

link seems broken to me.

We've been deploying changes all day so could related, thanks for the report. Should work now.

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

#179

Post by fekunde »

smeej wrote: post #160
personjerry wrote: post #142

I built https://eternalsouls.ai/ for a client recently. You just export and upload a WhatsApp conversation and it will learn the personality AND voice of your conversation partner. You can send/receive text or voice messages; It was pretty damn spooky to actually have a voice conversation back and forth with an AI standing in for my "friend"

I've seen this episode of Black Mirror.

Yeah, the pricing tiers make it all the more morbid and disconcerting. Scary future for sure.

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

#180

Post by takinola »

As I was building LLM projects, I found I was re-implementing a new vector database for each one. So I built RagTag (https://ragtag.weaveapi.com), a vectordb/RAG as a service to make the process faster. This provides a CRUD interface to push and retrieve documents, which are automatically chunked and converted to embeddings.

AgentX (https://theagentx.com), an LLM chat support app is one of the projects I built on this framework. It is a self-updating customer support agent that is trained on your support docs. Not only does this answer your customer questions, it provides summaries of the queries so you get a sense of where your product and/or documentation is deficient.

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