Wednesday, 26th March 2025
We estimate the supply-side value of widely-used OSS is $4.15 billion, but that the demand-side value is much larger at $8.8 trillion. We find that firms would need to spend 3.5 times more on software than they currently do if OSS did not exist.
— Manuel Hoffmann, Frank Nagle, Yanuo Zhou, The Value of Open Source Software, Harvard Business School
I've added a new content type to my blog: notes. These join my existing types: entries, bookmarks and quotations.
A note is a little bit like a bookmark without a link. They're for short form writing - thoughts or images that don't warrant a full entry with a title. The kind of things I used to post to Twitter, but that don't feel right to cross-post to multiple social networks (Mastodon and Bluesky, for example.)
I was partly inspired by Molly White's short thoughts, notes, links, and musings.
I've been thinking about this for a while, but the amount of work involved in modifying all of the parts of my site that handle the three different content types was daunting. Then this evening I tried running my blog's source code (using files-to-prompt and LLM) through the new Gemini 2.5 Pro:
files-to-prompt . -e py -c | \
llm -m gemini-2.5-pro-exp-03-25 -s \
'I want to add a new type of content called a Note,
similar to quotation and bookmark and entry but it
only has a markdown text body. Output all of the
code I need to add for that feature and tell me
which files to add the code to.'Gemini gave me a detailed 13 step plan covering all of the tedious changes I'd been avoiding having to figure out!
The code is in this PR, which touched 18 different files. The whole project took around 45 minutes start to finish.
(I used Claude to brainstorm names for the feature - I had it come up with possible nouns and then "rank those by least pretentious to most pretentious", and "notes" came out on top.)
This is now far too long for a note and should really be upgraded to an entry, but I need to post a first note to make sure everything is working as it should.
MCP 🤝 OpenAI Agents SDK
You can now connect your Model Context Protocol servers to Agents: openai.github.io/openai-agents-python/mcp/
We’re also working on MCP support for the OpenAI API and ChatGPT desktop app—we’ll share some more news in the coming months.
Function calling with Gemma (via) Google's Gemma 3 model (the 27B variant is particularly capable, I've been trying it out via Ollama) supports function calling exclusively through prompt engineering. The official documentation describes two recommended prompts - both of them suggest that the tool definitions are passed in as JSON schema, but the way the model should request tool executions differs.
The first prompt uses Python-style function calling syntax:
You have access to functions. If you decide to invoke any of the function(s), you MUST put it in the format of [func_name1(params_name1=params_value1, params_name2=params_value2...), func_name2(params)]
You SHOULD NOT include any other text in the response if you call a function
(Always love seeing CAPITALS for emphasis in prompts, makes me wonder if they proved to themselves that capitalization makes a difference in this case.)
The second variant uses JSON instead:
You have access to functions. If you decide to invoke any of the function(s), you MUST put it in the format of {"name": function name, "parameters": dictionary of argument name and its value}
You SHOULD NOT include any other text in the response if you call a function
This is a neat illustration of the fact that all of these fancy tool using LLMs are still using effectively the same pattern as was described in the ReAct paper back in November 2022. Here's my implementation of that pattern from March 2023.