Hey everyone, Great news for anyone setting up a new instance or onboarding friends and clients to Agent Zero. We have officially launched our one-line install scripts! You no longer need to manually clone the repo. Just paste the command for your OS into your terminal: - Mac/Linux: curl -fsSL https://bash.agent-zero.ai | bash - Windows: irm https://ps.agent-zero.ai | iex - Docker: docker run -p 80:80 agent0ai/agent-zero Why is this important right now? We are currently polishing the Plugin System and the Community Plugin Marketplace. Very soon, you will be able to extend Agent Zero's capabilities by installing community-made plugins directly from the UI with a single click. Let us know how the new install scripts work for you!

I just wanted to share how I set up VNC for Agent Zero in case anyone wants to try it. This is intended for personal use only — if you plan to expose it publicly, I strongly recommend using an SSH tunnel and enabling TLS. For personal/local use it should be fine as-is. Don't forget to configure port mapping in Docker when starting your container!

I saw someone else on hear had mentioned the need for a stop button. I wasn't sure at first if that was truly necessary as I have only been serious about using Agent Zero for the past 2 weeks now. Well, it seems they were indeed correct. Today I found the need for one in the middle of my workflow. I had been doing some market research and with my agent going at it for about 30 minutes solid, I managed to fill the context. The memory compaction kicked in and started doing its job. I have seen this before, so I thought, No big deal - research was about complete and it was running tokens on the final response. Then, something went wrong and the memory compaction failed. It hung at that step forever. I nudged it to continue giving the final response. It seems that with the context being full it did not have reference of what was already given as output - so it proceeded to do the research as per original instructions again! It just kept going! I paused it, I sent a stop message, the agent acknowledged but continued its tasks any way. I gave it further instructions to abort - again it acknowledged that "the user wants me to stop" but it still kept going. It just kept burning up tokens. No way did I want it to run through the whole 30 minute research routine again! The only solution I had was to stop the docker container. This behavior is just unacceptable. If I were using online models and required to pay API fees I could be throwing money away had I left the agent unattended. That's time and money wasted. Thankfully, I have the hardware to run everything locally, so in this case it was just my time and the hassle to get it to stop. Can someone perhaps bring this up in today's call? I'm unsure if I will be able to make it. Thanks. Would be nice to see this implemented in a way that stops/aborts all running tasks.

I was wondering why cant I stop the agent when he does something wrong and not really following mij instructions it keeps in a loop that it wants to do it even when I try to stop it. Is there a way to talk to the agent even if its doing a task to steer it in the right direction.