Ooooh, not something i have built, I do want to but suspect someone else has done it better than i could.
A tool to RAG a github repo, so i can ask questions of how a certain library or tool works? Even better if it pulls in issues
Ask HN: What have you built with LLMs?
41–50 of 349 posts
Re: Ask HN: What have you built with LLMs?
#42I 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…
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.
Re: Ask HN: What have you built with LLMs?
#43"Widjosumarajzer" = video summarizer
It's just a hodgepodge of prototype scripts, but one that I actually used on a few occasions already. Most of the work is manual, but does seem easily run as "fire and forget" with maybe some ways to correct afterwards.
First, I'm using the pyannote for speech recognition: it converts audio to text, while being able to discern speakers: SPEAKER_01, _02, etc. The diarization provides nice timestamps, with resolution down to parts of words, which I later use in the minimal UI to quickly skip around, when a text is selected.
Next, I'm running a LLM prompt to identify speakers; so if SPEAKER_02 said to SPEAKER_05 "Hey Greg", it will identify SPEAKER_05 = Greg. I think it was my first time using the mistral 7b and I went "wow" out loud, once it got correct.
After that, I fill in the holes manually in speaker names and move on to grouping a bunch of text - in order to summarize. That doesn't seem interesting at a glance, but removing the filler words, which there are a ton of in any presentation or meeting, is a huge help. I do it chunk by chunk. I'm leaning here for the best LLM available and often pick the dolphin finetune of mixtral.
Last, I summarize those summarizations and slap that on the front of the google doc.
I also insert some relevant screenshots in between chunks (might go with some ffmpeg automatic scene change detection in the future).
aaand that's it. A doc, that is searchable easily. So, previously I had a bunch of 30 min. to 90 min. meeting recordings and any attempt at searching required a linear scan of files. Now, with a lot of additional prompt messaging I was able to:
- create meeting notes, with especially worthwile "what did I promise to send later" points
- this is huge: TALK with the transcript. I paste the whole transcript into the mistral 7b with 32k context and simply ask questions and follow-ups. No more watching or skimming an hour long video, just ask the transcript, if there was another round of lay-offs or if parking spaces rules changed.
- draw a mermaid sequence diagram, of a request flowing across services. It wasn't perfect, but it got me super excited about future possibilities to create or update service documentation based on ad-hoc meetings.
I guess everybody is actually trying to build the same, seems like a no-brainer based on current tool's capabilities.
Re: Ask HN: What have you built with LLMs?
#44I made some LLM-powered text-adventure games: https://cosmictrip.space/gameannouncement And I'm working on a webapp that is a kanban board where LLM and human collaborate to build features in code. I just got a cool thing working there: like everyone, having LLM generate new code is easy but modifying code is hard. So my attempt at working on modifying code with LLM is starting with HTML and having GPT-4 write beautf…
I didn't make text-adventures with LLMs. I try to solve them [0].
So, far, none of the 7 tested models were able to win even one of the easiest text adventures. I tried many prompting techniques. But only GPT-4 was able to play through the first half of the game.
Re: Ask HN: What have you built with LLMs?
#45An Extensible Conversational UI for Interactive Components[1][2], current use case is a Personal Productivity Assistant for structured data.
The stack is simple, preact in the fronted with a custom framework on top and bun on the backend calling OpenAI, I may port it to rust in the future.
I plan to try local LLMs when I have some free time.
For now each users runs the application locally with their own keys[3].
[1] https://www.youtube.com/watch?v=nS1wsif3y94
[2] https://www.youtube.com/watch?v=f-txlMDLfng
[3] Alpha software, check the readme: https://gloodata.com/download/
Re: Ask HN: What have you built with LLMs?
#46I created a Chrome extension which shows cryptocurrency prices & insights when you hover cash tags on Twitter. I'm a product manager with solid CS understanding, but haven't had the time to learn React or glue frontend stuff together - so about 80% of the code is generated by GPT4. I've mainly architected the code and deployed on Vercel. I feel like AI + Vercel has given me that final push to actually deploy products instead of just building stuff and leave it lying around.
Re: Ask HN: What have you built with LLMs?
#47I've built several things! These include bots for code generation that you can tag onto issues, q&a on text etc. The thing I'm working on now is AI mock interviewing. It's basically scratching my own itch, since I hate leetcode prep, and have found I can learn better through interaction. To paste a blurb from an earlier comment of mine: I'm building https://comp.lol . It's AI powered mock coding interviews, FAANG sty…
Very cool, I signed up. I agree that practicing a coding interview is better under pressure. It's a much difference skill to solve a coding problem both under time pressure and pressure to speak your thoughts to entertain the interviewer. Only practice can help improve that skill.
Re: Ask HN: What have you built with LLMs?
#48Ooooh, not something i have built, I do want to but suspect someone else has done it better than i could. A tool to RAG a github repo, so i can ask questions of how a certain library or tool works? Even better if it pulls in issues
This is very easy to do and a great idea!
Langchain and Llama Index both have classes to read a directory, if you git clone, and perform a RAG.
If you want it to scrape a github URL, there is a module for that too!
This starter tutorial will do RAG on a directory of files: https://docs.llamaindex.ai/en/latest/getting_started/starter...
Re: Ask HN: What have you built with LLMs?
#49I am working on building out a better voice interface for LLMs.
It is still a work in progress (early beta), but you can check it out at https://www.bonamiko.com
Currently I have mainly been using it as a tandem conversation partner for a language I'm learning, but it can be used for many more things. As it is right now, you can use it to bounce ideas of, practice interviews, and help answer quick general questions. You just need to tell it what you want.
The stack is a Next.js application hosted on Vercel using Supabase for the backend. (There is also some plumbing in AWS for email and DNS.) It is automatically deployed via GitHub actions.
Re: Ask HN: What have you built with LLMs?
#50Also a Chrome extension [0]! The concept is to use the browser's context menu to run commands on the LLM, so it stays out of your way most of the time but feels like a somewhat native experience. The stack is: 1. TypeScript/Node/tRPC/Postgres/Redis/OpenAI on the backend 2. SolidJS/Crxjs/tRPC on the front end 3. Astro for the docs/marketing site And deployment is currently through render.com for the databases and serv…
Open source alternative that does the same but in vanilla JS and completely in user's control https://github.com/SMUsamaShah/LookupChatGPT