We're working on that! Many sandboxes exist, including our own, Greywall. It integrates with our proxy, Greyproxy, which handles TLS interception and reconstructing LLM conversations, plus features like credential swapping. We currently have a PR for middlewares we can test; things like intent classification to catch conversation derails, PII redaction, etc.
It's open source, check out greywall.io // github.com/greyhavenhq/greyproxy // github.com/greyhavenhq/greywall
This is why kernel-level sandboxing matters. I use a sandbox name greywall that enforce filesystem/network isolation at the syscall level (Landlock + Seccomp + eBPF on linux, sandbox-exec on mac).
I do disagree about unix system were designed for this kind of stuff. Unix was not designed for an agent to act like you and take decision for you...
Author here. I didn't set out to build this. Started with Cubbi as a opinionated Docker-based wrapper for CLI agents, but the network restrictions and not having my own tooling kept fighting. Then found Fence which was already doing the hard kernel work really well. What pushed me to go further was network control: tools that ignore HTTP_PROXY env vars bypass proxy-based filtering entirely. The transparent TUN approach captures everything regardless (but not yet on macos).
The dashboard is just the start. The real goal is full conversation observability including tool calls, a semantic firewall that understands what the agent is actually trying to do rather than just which domain it's hitting, and credential replacement on the fly before anything leaves the machine. The hard part is that sitting as a transparent proxy makes this significantly more complex, and I don't want to touch any agent internals or require integrating a third party SDK.
Happy to answer questions and curious how others are thinking about the visibility vs isolation tradeoff.
I wrote a podcast generator based on AI related papers that ingest the podcast dialogues, voices, tag, assemble audio et publish RSS automatically. I was inspired by the PDF ingestion of OpenAI and the quality of the TTS.
SEEKING WORK | France (UTC-1) | Remote | Full stack developer
My name is Mathieu Virbel, and I am a consultant on system and software architecture with over 12 years of experience as a consultant and 20 years into programming. I have a passion for creating innovative and user-friendly applications. I specialize in using the open-source Kivy framework to develop desktop and mobile applications, but I am also skilled in other technologies and frameworks.
I worked on a variety of subjects, from Interactives and mobile application for Museum and Public Institutions, Embedded system in security company, telecommunication, and Startups environments from scratch. Recently playing with Python, Golang, VueJS 3/Typescript, InfluxDB, Docker Swarm, as well as writing specifications and reviewing code of others contractors.
SEEKING WORK | France (UTC-1) | Remote | Full stack developer
My name is Mathieu Virbel, and I am a consultant on system and software architecture with over 12 years of experience as a freelance and 20 years in the field. I have a passion for creating innovative and user-friendly applications. I specialize in using the open-source Kivy framework to develop desktop and mobile applications, but I am also skilled in other technologies and frameworks.
I worked on a variety of subjects, from Interactives and mobile application for Museum and Public Institutions, Embedded system in security company, telecommunication, and Startups environments from scratch. Recently playing with Python, Golang, VueJS 3/Typescript, InfluxDB, Docker Swarm, as well as writing specifications and reviewing code of others contractors.
My name is Mathieu Virbel, and I am a consultant on system and software architecture with over 12 years of experience as a freelance and 20 years in the field. I have a passion for creating innovative and user-friendly applications. I specialize in using the open-source Kivy framework to develop desktop and mobile applications, but I am also skilled in other technologies and frameworks.
I worked on a variety of subjects, from Interactives and mobile application for Museum and Public Institutions, Embedded system in security company, telecommunication, and Startups environments from scratch. Recently playing with Python, Golang, VueJS 3/Typescript, InfluxDB, Docker Swarm, as well as writing specifications and reviewing code of others contractors.
Shameless plug here. I'm working for https://cozyair.fr - keeping a good indoor air quality is good for both the user but also the the building.
CO2 is not the only factor you should look at, PM are also dangerous when you cook, or when there is outside pollution. NO2/O3 is an outdoor air pollution that we watch. Because the only way to get out the CO2 is ventilation / open your windows for a few minutes. But it can bring another kind of pollution depending your area.
Just an addition, there is many others alternatives, but it may be hard for others to be able to compile the Python extensions you want (or impossible). That's what we wanted to do here: ability to pick the extension needed, provide a "recipe" that contain specialized tricks or patches to extension for running in Android, etc.
A minimal hello world with Python 3 required 7MB. But it's not optimized.
Unlike pyinstaller, we don't scan import to try reducing the distribution on the phone. Instead we have a blacklist.txt which you can put file pattern to exclude during packaging.
I remember for one app in Python 2 to reduce the size around the 5MB.
We won't be able to reduce much more, as Python interpreter is embedded. We also don't want to adopt an approach like Qt where Qt binaries can be shared for all Qt-application, which break the all-in-one APK, open some potential issues, and add more work to manage dependencies.
Please note that Python for Android project is not meant to be used with Kivy only anymore.
It's a project that allow you to compile Python and dependencies, and package it along your own application. You could for example compile Numpy, ZMQ, sqlalchemy, zeroconf, etc...
We have a mechanism called bootstrap that allow you to select your primary technology that you're going to use for your application, such as "sdl2" (required for kivy), "webview" (it just start a webpage that connect to your phone port 5000, so you can start an embed webserver such as Flask to serve your app), "service_only" (if you don't need any kind of UI). New bootstrap can be written to support another type of apps.
Also, you could embed your whole UI in pure java if you wanted too, as the directory libs (to include .jar) or src (to include .java) are compiled. So you can imagine having your app in Java, but still call Python for something else if you really wanted too.
One of the idea behind CDN for javascript/css is to leverage caching by reusing the same resources across websites.
But then optimization tools said we should bundle everything into one javascript, which delay the loading time, but defeat the initial purpose.
I wonder if the caching could be more intelligent, by recognizing libraires bundled into the "big" javascript that website delivers, and parse only the new content.
Not at all. For example, if you already know the HSK1, feel free to start directly on the World 2. Each world = one HSK for now, and you can learn up to HSK 5 with the current application (HSK 6 on the way).
In case you stop in the middle of HSK 1, going through the stage should be very easy. I still think you should give it a try, as even if you know the word, you'll also make sentence and learn to talk (or listen if you don't like to talk). Review are only for words right now, and if you know them, they won't bother you a lot ^^
I liked! Already done the first 3, the music didn't bothered me neither the voice (i'm not a native english at all.). As for the concept explain, it's true that some equation are a little bit out of reach for someone that has less mathematical background. But i understand the concept so far, which are well explained.
I'm not sure i would be able to just write (or decide) the equation for the neural network. On what criteria can you decide this will work better or not? What are your key to make a decision?
Documentation. A subject that is as important as the code, maybe more. We are internally always debating what does an user should known by default, and how. Both matters and depends of the target (noob, average, expert) or which approach first (kv based or python based). I personally don't know how to write a good documentation, except if it's just API documentation. But in that case, API is just not sufficient, as concept need to be explain as well. We have actually one big big big contributor named ZenCode who work behind the scene on the documentation, and constantly fixing our mistake / wording.
I ear you loud and clear, wish to have a better programming guide / module documentation as well.
About ListView... Let's say it's one of the Kivy widget that doesn't fit to the Kivy logic at all. Historically, i started a POC about it, then a contributor take it and worked a lot to have something that works for any sort of situations. And he tend up to something that cover lot of cases, but still bugs, and not easy to get it. Not to mention issue with performance.
That's why i rebooted the ListView from scratch, and named it RecycleView (like RecycledView from android): https://github.com/kivy-garden/garden.recycleview
The visual design was taken from Meego / Android in the old days. We might be able to refresh the theme one day, if we have somebody that can contribute to it (i mean a real designer, not a coder). I rarely use the default theme, always extend a widget to put the designer visuals i got on customers projects.
It's open source, check out greywall.io // github.com/greyhavenhq/greyproxy // github.com/greyhavenhq/greywall