5 posts tagged “textual”
2025
mistralai/mistral-vibe. Here's the Apache 2.0 licensed source code for Mistral's new "Vibe" CLI coding agent, released today alongside Devstral 2.
It's a neat implementation of the now standard terminal coding agent pattern, built in Python on top of Pydantic and Rich/Textual (here are the dependencies.) Gemini CLI is TypeScript, Claude Code is closed source (TypeScript, now on top of Bun), OpenAI's Codex CLI is Rust. OpenHands is the other major Python coding agent I know of, but I'm likely missing some others. (UPDATE: Kimi CLI is another open source Apache 2 Python one.)
The Vibe source code is pleasant to read and the crucial prompts are neatly extracted out into Markdown files. Some key places to look:
- core/prompts/cli.md is the main system prompt ("You are operating as and within Mistral Vibe, a CLI coding-agent built by Mistral AI...")
- core/prompts/compact.md is the prompt used to generate compacted summaries of conversations ("Create a comprehensive summary of our entire conversation that will serve as complete context for continuing this work...")
- Each of the core tools has its own prompt file:
The Python implementations of those tools can be found here.
I tried it out and had it build me a Space Invaders game using three.js with the following prompt:
make me a space invaders game as HTML with three.js loaded from a CDN
Here's the source code and the live game (hosted in my new space-invaders-by-llms repo). It did OK.
Textual v4.0.0: The Streaming Release. Will McGugan may no longer be running a commercial company around Textual, but that hasn't stopped his progress on the open source project.
He recently released v4 of his Python framework for building TUI command-line apps, and the signature feature is streaming Markdown support - super relevant in our current age of LLMs, most of which default to outputting a stream of Markdown via their APIs.
I took an example from one of his tests, spliced in my async LLM Python library and got some help from o3 to turn it into a streaming script for talking to models, which can be run like this:
uv run http://tools.simonwillison.net/python/streaming_textual_markdown.py \
'Markdown headers and tables comparing pelicans and wolves' \
-m gpt-4.1-mini
2024
Anatomy of a Textual User Interface. Will McGugan used Textual and my LLM Python library to build a delightful TUI for talking to a simulation of Mother, the AI from the Aliens movies:
The entire implementation is just 77 lines of code. It includes PEP 723 inline dependency information:
# /// script # requires-python = ">=3.12" # dependencies = [ # "llm", # "textual", # ] # ///
Which means you can run it in a dedicated environment with the correct dependencies installed using uv run like this:
wget 'https://gist.githubusercontent.com/willmcgugan/648a537c9d47dafa59cb8ece281d8c2c/raw/7aa575c389b31eb041ae7a909f2349a96ffe2a48/mother.py'
export OPENAI_API_KEY='sk-...'
uv run mother.pyI found the send_prompt() method particularly interesting. Textual uses asyncio for its event loop, but LLM currently only supports synchronous execution and can block for several seconds while retrieving a prompt.
Will used the Textual @work(thread=True) decorator, documented here, to run that operation in a thread:
@work(thread=True) def send_prompt(self, prompt: str, response: Response) -> None: response_content = "" llm_response = self.model.prompt(prompt, system=SYSTEM) for chunk in llm_response: response_content += chunk self.call_from_thread(response.update, response_content)
Looping through the response like that and calling self.call_from_thread(response.update, response_content) with an accumulated string is all it takes to implement streaming responses in the Textual UI, and that Response object sublasses textual.widgets.Markdown so any Markdown is rendered using Rich.
2023
textual-paint (via) Isaiah Odhner built a full working clone of MS Paint that runs entirely in the terminal, using Textual and Python. It’s worth trying this out to get a feel for quite how much you can get done with a CLI app these days—“pipx install textual-paint” worked for me.
textual-mandelbrot (via) I love this: run “pipx install textual-mandelbrot” and then “mandelexp” to get an interactive Mandelbrot fractal exploration interface right there in your terminal, built on top of Textual. The code for this is only 250 lines of Python and delightfully easy to follow.