#arkaine

Back when I was working on coppermind at the heyday of GPT3.5’s initial world shattering release, I had… difficulty finding good ways to deal with parsing the stochastic LLM outputs.

I got better at this when I started work on arkaine, eventually developing a pretty useful and reliable parsing pattern.

With an idea that would be best served as a golang app requiring interacting with LLMs I decided to do a quick port of the parser to an idiomatic golang module.

So if you need AI parsing for your golang project, check out go-arkaine-parser.

#arkaine #golang #AI

Did some work on eli5equation, cleaning up and fully deploying prior one day project. We’ll see if people find it useful. I find it super useful when tackling new AI papers.

I also gave it a bit of a glowup too. And yeah, still powered by arkaine.

#arkaine #AI #math

I have been busy due to a flood of inspiration to work on projects. Pleasant, but also exhausting.

The only updates to arkaine has been to fix an issue with default arguments in the ParallelList flow tool. The reason for the freeze in development is an accidental startup.

How does one go “oops, I made a startup?” Basically, I decided to quickly develop a series of simple apps that utilized arkaine and would demonstrate its usage. Then combine them into a large post walking through the examples.

The very first one you saw a prototype for in an earlier post wherein I made a interview practice question generator. This was a simple script, but the results struck me as promising. Why not build a nice site around it so that other people can use it? And so started hiredcoach

I really liked what I started to see, and realized that this could actually be useful to people if offered as a service. So that’s what I’m aiming to do - try and build out a startup from it as quickly as possible. I’m at ~12 days of development effort. I had hoped to get it out in 2 weeks - 3 or 4 still seems a possibility.

I’ll post here when I launch and my initial thoughts. I temper my anxiety of startup launching with thoughts that the worst case is a nice line item in my resume upon failure.

#hiredcoach #startup #AI #arkaine

One of the great parts of building out tools like arkaine is that it allows me to sit down and just build for a bit to test the framework. After some quick experimentation I have a great agent that:

1. Takes in a resume and a job description

2. Considers additional topics to research to build out a knowledge base of what certain acroynms, skills, and technologies mean, and what are industry standards and expectations are

3. Searches the web for those topics with arkaine’s research agents, building a knowledge base of relevant information

4. Builds a list of questions that an interview should ask and…

5. Converts the questions to natural sounding language and uses TTS to create a virtual interviewer. (This part is… it works. But sometimes it’s too heavy on the pausing and filler words)

So far it’s working surprisingly well for a simple prototype script. I’ll probably expand on it quite a bit, especially since I haven’t utilized speech-to-text to allow the user to answer (and an agent to judge their response) yet.

Here are some examples (the TTS is handled by OpenAI’s gpt-4o-mini-tts):

#AI #arkaine

Version 0.0.21 of arkaine is out, including the finalized format for the text to speech tooling, equivalent speech to text tooling (though, admittingly, I currently lack a locally hosted option for this), and the think tool I mentioned earlier.

There’s still a lot of features that I want to add, and some I’m in the middle of; adding a chat interface to Spellbook and expanding the number of possible chat interfaces would be fun, and I already started the process a month ago. Similarly I half a ~60% completed OCR implementation and a redefining of how researchers utilize resources (necessary for handling non website object search, like your own books/documents)… but right now I’m thinking of taking a moment to just building with what I have and creating something useful for people as is.

#AI #arkaine

I simply love when simple ideas get tested and proven to be quite effective. It’s a clear sign of slowly feeling out how to best understand the system at hand. Such a delight popped up when I saw that Anthropic had revealed that simply adding a no-op tool with a “thought” argument called “think”, allowing the agent to just output its thought in the chain of Action -> Result generation, improved performance on complicated tasks.

…of course, I also have already implemented it in arkaine; I’ll give it a more thorough testing with some more complicated agents later.

#AI #arkaine

Inspired by OpenAI’s newest text to speech models, I decided to finally take a crack at text to speech on arkaine. To that end, I published 0.0.20 of arkaine with a beta build of text to speech tools, support OpenAI, Google, and Kokoro for local execution. Check them out in the toolbox!

#arkaine #AI

My framework arkaine, which I quickly presented a bit ago, finally has some nice documentation for it. I had v0 do an initial pass on it, which I rather liked. After two quick rounds of prompting on their free tier I downloaded the project and tried my hand at expanding it from there. It’s my first tailwind/next.js project, but it was surprisingly easy. Granted it’s a simple page relative to a typical SPA or backend service, but hey, I’ll take the wins where I can get them.

Check out the documentation, especially the toolbox, and see if you can get inspired to build anything cool with arkaine.

#arkaine #AI

I’ve been working on arkaine’s OCr service all weekend, and need a break. I’ve been toying with the idea of an equation explainer that copies the style I present complicated math in my paper club presentations. I’ve decided to step away from arkaine and try using it a bit in a prototype. Hence: eli5-equations.

Want to get a walk through of a complicated equation? Pass it in with some context and see if your evening is a bit enlightened. I’ll do a further write up on this later probably.

#arkaine #AI #math

Today I attended a mini-hackathon via SDx. I attended to solo work on some arkaine agents and to be present as a mentor/advisory role for other attendees. It was a short 6 hour affair, mainly focused on playing with the new OpenAI o3-mini. It also helps to be inspired by seeing other people creatively applying AI to a quick weekend project.

I ended up building a great prototype of a research agent - the original goal of arkaine for myself. It needs some work - I definitely ran into rate limiting issues and need to get the agent to better understand report generation at the end. Expect this to get added in to arkaine soon. Pushing myself to finish the project in the time allotted was also a great exercise in rapid prototyping. As for the other projects - there were quite a few that wowed me. I’m certainly looking forward to the next time I can dive in and code surrounded by other makers.

#arkaine #AI #SDx