Vercel has a library called ai, that is useful for building language model chat applications. I used it to help build Write Partner The library has two main components:
A backend API that is called by a frontend app that streams language model responses A hook (in React) that provides access to the chat, its messages and an API to fetch completions When designing Write Partner, I started the chat session with the following messagesI started playing the NYTimes word game “Connections” recently, by the recommendation of a few friends. It has the type of freshness that Wordle lost for me a long time ago. After playing Connections for a few days, I wondered if an OpenAI language model could solve the game (the objective is to group the 16 words into 4 categories of 4 words). I tried with gpt-4-32k and gpt-4-1106-preview, tweaking prompts for a few hours and wasn’t able to make much progress.Goku has a concept called a simlayer. A simlayer allows you to press any single key on the keyboard, then any second key while holding the first and trigger an arbitrary action as a result. I’m going to write a karabiner.edn config that opens Firefox when you press .+f.
{:simlayers {:launch-mode {:key :period}}, :templates {:open-app "open -a \"%s\""}, :main [{:des "launch mode", :rules [:launch-mode [:f [:open-app "Firefox"]]]}]} ❯ goku Done! To start, we define a simlayer for the period key.Karabiner is a keyboard customizer for macOS. I’ve used it for a while to map my caps lock key to cmd + ctrl + option + shift. This key combination is sometimes called a hyper key. With this keyboard override, I use other programs like Hammerspoon and Alfred to do things like toggle apps and open links. Karabiner provides an out-of-the-box, predefined rule to perform this complex modification. I’ve used this approach for a while but recently learned about Goku which adds a lot of additional functionality to Karabiner using Clojure’s extensible data notation (edn) to declaratively configure Karabiner.I’ve starting playing around with Fireworks.ai to run inference using open source language models with an API. Fireworks’ product is the best I’ve come across for this use case. While Fireworks has their own client, I wanted to try and use the OpenAI Python SDK compatibility approach, since I have a lot of code that uses the OpenAI SDK. It looks like Fireworks’ documented approach no longer works since OpenAI published version 1.At the beginning of 2023, I set some goals for myself. Here are those goals and how the year turned out.
Learn a new word each week (50%) Clear and effective communication is important to me. My thought process was that I could improve as a communicator if I further developed my vocabulary. I also find it particularly satisfying to conjure the perfect word to describe a situation, experience, etc. Each Monday, I would find a new word and record it, it’s part of speech and definition in Obsidian.In a previous note, I discussed running coroutines in a non-blocking manner using gather. This approach works well when you have a known number of coroutines that you want to run in a non-blocking manner. However, if you have tens, hundreds, or more tasks, especially when network calls are involved, it can be important to limit concurrency. We can use a semaphore to limit the number of coroutines that are running at once by blocking until other coroutines have finished executing.Python coroutines allow for asynchronous programming in a language that earlier in its history, has only supported synchronous execution. I’ve previously compared taking a synchronous approach in Python to a parallel approach in Go using channels. If you’re familiar with async/await in JavaScript, Python’s syntax will look familiar. Python’s event loop allows coroutines to yield control back to the loop, awaiting their turn to resume execution, which can lead to more efficient use of resources.Render is a platform as a service company that makes it easy to quickly deploy small apps. They have an easy-to-use free tier and I wanted run a Python app with dependencies managed by Poetry. Things had been going pretty well until I unexpectedly got the following error after a deploy
Fatal Python error: init_fs_encoding: failed to get the Python codec of the filesystem encoding Python runtime state: core initialized ModuleNotFoundError: No module named 'encodings' You don’t have to search for too long to find out this isn’t good.In Javascript, using async/await is a cleaner approach compared to use of callbacks. Occasionally, you run into useful but older modules that you’d like to use in the more modern way.
Take fluent-ffmpeg, a 10 year old package that uses callbacks to handle various events like start, progress, end and error.
Using callbacks, we have code that looks like this:
const ffmpeg = require('fluent-ffmpeg'); function convertVideo(inputPath, outputPath, callback) { ffmpeg(inputPath) .