Simon Willison’s Weblog

Paying people to work on open source is good actually. In which Jacob expands his widely quoted (including here) pithy toot about how quick people are to pick holes in paid open source contributor situations into a satisfyingly comprehensive rant. This is absolutely worth your time—there’s so much I could quote from here, but I’m going to go with this:

“Many, many more people should be getting paid to write free software, but for that to happen we’re going to have to be okay accepting impure or imperfect mechanisms.”

# 1:42 am / jacob-kaplan-moss, open-source

wddbfs – Mount a sqlite database as a filesystem. Ingenious hack from Adam Obeng. Install this Python tool and run it against a SQLite database:

wddbfs --anonymous --db-path path/to/content.db

Then tell the macOS Finder to connect to Go -> Connect to Server -> http://127.0.0.1:8080/ (connect as guest) - connecting via WebDAV.

/Volumes/127.0.0.1/content.db will now be a folder full of CSV, TSV, JSON and JSONL files - one of each format for every table.

This means you can open data from SQLite directly in any application that supports that format, and you can even run CLI commands such as grep, ripgrep or jq directly against the data!

Adam used WebDAV because "Despite how clunky it is, this seems to be the best way to implement a filesystem given that getting FUSE support is not straightforward". What a neat trick.

# 3:31 am / cli, python, sqlite, webdav, jq

Representation Engineering: Mistral-7B on Acid (via) Theia Vogel provides a delightfully clear explanation (and worked examples) of control vectors—a relatively recent technique for influencing the behaviour of an LLM by applying vectors to the hidden states that are evaluated during model inference.

These vectors are surprisingly easy to both create and apply. Build a small set of contrasting prompt pairs—“Act extremely happy” v.s. “Act extremely sad” for example (with a tiny bit of additional boilerplate), then run a bunch of those prompts and collect the hidden layer states. Then use “single-component PCA” on those states to get a control vector representing the difference.

The examples Theia provides, using control vectors to make Mistral 7B more or less honest, trippy, lazy, creative and more, are very convincing.

# 3:49 am / ai, generative-ai, llms, mistral

Datasette 1.0a10. The only changes in this alpha release concern the way Datasette handles database transactions. The database.execute_write_fn() internal method used to leave functions to implement transactions on their own—it now defaults to wrapping them in a transaction unless they opt out with the new transaction=False parameter.

In implementing this I found several places inside Datasette—in particular parts of the JSON write API—which had not been handling transactions correctly. Those are all now fixed.

# 5:10 am / projects, sqlite, transactions, datasette

datasette-studio. I've been thinking for a while that it might be interesting to have a version of Datasette that comes bundled with a set of useful plugins, aimed at expanding Datasette's default functionality to cover things like importing data and editing schemas.

This morning I built the very first experimental preview of what that could look like. Install it using pipx:

pipx install datasette-studio

I recommend pipx because it will ensure datasette-studio gets its own isolated environment, independent of any other Datasette installations you might have.

Now running datasette-studio instead of datasette will get you the version with the bundled plugins.

The implementation of this is fun - it's a single pyproject.toml file defining the dependencies and setting up the datasette-studio CLI hook, which is enough to provide the full set of functionality.

Is this a good idea? I don't know yet, but it's certainly an interesting initial experiment.

# 8:38 pm / cli, plugins, projects, pypi, python, datasette

ActivityPub Server in a Single PHP File (via) Terence Eden: “Any computer program can be designed to run from a single file if you architect it wrong enough!”

I love this as a clear, easy-to-follow example of the core implementation details of the ActivityPub protocol—and a reminder that often a single PHP file is all you need.

# 12:20 am / php, mastodon, activitypub, terence-eden

aiolimiter. I found myself wanting an asyncio rate limiter for Python today—so I could send POSTs to an API endpoint no more than once every 10 seconds. This library worked out really well—it has a very neat design and lets you set up rate limits for things like “no more than 50 items every 10 seconds”, implemented using the leaky bucket algorithm.

# 1:15 am / async, python, rate-limiting

htmz (via) Astonishingly clever browser platform hack by Lean Rada.

Add this to a page:

<iframe hidden name=htmz onload="setTimeout(() => document.querySelector( this.contentWindow.location.hash || null)?.replaceWith( ...this.contentDocument.body.childNodes ))"></iframe>

Then elsewhere add a link like this:

<a href="/flower.html#my-element" target=htmz>Flower</a>

Clicking that link will fetch content from /flower.html and replace the element with ID of my-element with that content.

# 1:21 am / html, iframes, javascript

Let’s build the GPT Tokenizer. When Andrej Karpathy left OpenAI last week a lot of people expressed hope that he would be increasing his output of educational YouTube videos.

Here’s an in-depth 2 hour dive into how tokenizers work and how to build one from scratch, published this morning.

The section towards the end, “revisiting and explaining the quirks of LLM tokenization”, helps explain a number of different LLM weaknesses—inability to reverse strings, confusion over arithmetic and even a note on why YAML can work better than JSON when providing data to LLMs (the same data can be represented in less tokens).

# 6:02 pm / ai, andrej-karpathy, generative-ai, llms, tokenization

Gemma: Introducing new state-of-the-art open models. Google get in on the openly licensed LLM game: Gemma comes in two sizes, 2B and 7B, trained on 2 trillion and 6 trillion tokens respectively. The terms of use “permit responsible commercial usage”. In the benchmarks it appears to compare favorably to Mistral and Llama 2.

Something that caught my eye in the terms: “Google may update Gemma from time to time, and you must make reasonable efforts to use the latest version of Gemma.”

One of the biggest benefits of running your own model is that it can protect you from model updates that break your carefully tested prompts, so I’m not thrilled by that particular clause.

UPDATE: It turns out that clause isn’t uncommon—the phrase “You shall undertake reasonable efforts to use the latest version of the Model” is present in both the Stable Diffusion and BigScience Open RAIL-M licenses.

# 4:22 pm / google, ai, generative-ai, local-llms, llms, gemma

JavaScript Bloat in 2024 (via) Depressing review of the state of page bloat in 2024 by Nikita Prokopov. Some of these are pretty shocking: 12MB for a Booking.com search, 9MB for a Google search, 20MB for Gmail(!), 31MB for LinkedIn. No wonder the modern web can feel sludgy even on my M2 MacBook Pro.

# 11:31 pm / web-performance

Okay, Color Spaces (via) Fantastic interactive explanation of how color spaces work by Eric Portis.

# 11:38 pm / colour, explorables

PGlite (via) PostgreSQL compiled for WebAssembly and turned into a very neat JavaScript library. Previous attempts at running PostgreSQL in WASM have worked by bundling a full Linux virtual machine - PGlite just bundles a compiled PostgreSQL itself, which brings the size down to an impressive 3.7MB gzipped.

I built this interactive demo of PGlite using Observable Framework, source code here.

# 3:56 pm / postgresql, observable, webassembly, observable-framework

Bloom Filters, explained by Sam Rose. Beautifully designed explanation of bloom filters, complete with interactive demos that illustrate exactly how they work.

# 3:59 pm / bloom-filters, explorables, sam-rose

Does Offering ChatGPT a Tip Cause it to Generate Better Text? An Analysis (via) Max Woolf:“I have a strong hunch that tipping does in fact work to improve the output quality of LLMs and its conformance to constraints, but it’s very hard to prove objectively. [...] Let’s do a more statistical, data-driven approach to finally resolve the debate.”

# 5:42 pm / ai, max-woolf, generative-ai, chatgpt, llms

How to make self-hosted maps that work everywhere and cost next to nothing. Chris Amico provides a detailed roundup of the state of web mapping in 2024. It’s never been easier to entirely host your own mapping infrastructure, thanks to OpenStreetMap, Overture, MBTiles, PMTiles, Maplibre and a whole ecosystem of other fine open source projects.

I like Protomaps creator Brandon Liu’s description of this: “post-scarcity web mapping”.

# 4:19 am / gis, maps, chris-amico, overture