OpenAI just reduced their prices, starting September 1 2022 on midnight UTC. For the DaVinci model, the price is cut by around two thirds.
| Model | Before | On Sept 1 |
|---|---|---|
| Davinci | $0.06 / 1k tokens | $0.02 / 1k tokens |
| Curie | $0.006 / 1k tokens | $0.002 / 1k tokens |
| Babbage | $0.0012 / 1k tokens | $0.0005 / 1k tokens |
| Ada | $0.0008 / 1k tokens | $0.0004 / 1k tokens |
| Davinci Embeddings | $0.6 / 1k tokens | $0.2 / 1k tokens |
| Curie Embeddings | $0.06 / 1k tokens | $0.02 / 1k tokens |
| Babbage Embeddings | $0.012 / 1k tokens | $0.005 / 1k tokens |
| Ada Embeddings | $0.008 / 1k tokens | $0.004 / 1k tokens |
I am using Sidekiq for background processing for my website Every Podcast. One of the background jobs is loading new episodes from known feeds. Because this relies on external resources, many things that are out of my control can go wrong. To isolate the individual fetch and potential errors, I automatically create a job for every single podcast update. This obviously leads to a lot of jobs. Sidekiq comes with a UI that allows me to monitor the job queue, find dead jobs and see the throughput.
Beautiful visualizations and projects by Aaron Koblin. Through this I discovered the flight patterns, generated with the processing framework which is now on my list to try out. I meant to post this some time ago and recently found it in my “drafts” folder.
While working on my current project, everypodcast, I needed to implement an RSS feed parser, mostly for iTunes RSS feeds. Initially I went with the builtin RSS package from the standard library. When reading a lot of large XML feeds, I noticed that parsing those feeds takes anywhere from 0.5 to over 30 seconds. At the same time the process was using a 100% CPU.
After some searching I found Feedjira. With this, it now takes on average 0.5 seconds and at most 1.5 seconds to parse even the longest feeds. Furthermore it has dedicated support for different types of RSS feeds, I highly recommend it.
I wanted to test some part of my application that performs HTTP requests against a different website. Now, for testing, I didn’t want to perform actual outside HTTP calls because they tend to become flaky if the internnet becomes unstable or when the remote resource is not available. Another reason, why I didn’t want to use the rails server and their static files, is that I didn’t want to serve those files in production. So I decided to write my own static file server.