This is our first major release after the UI redesign of the version 1 line, and it's really three things shipping together. 1. A0 Launcher (our new product) A desktop app for Windows, macOS and Linux. It manages your local and remote Agent Zero instances from one place, and, for anyone just starting, it onboards new users with an installer that sets up the container runtime automatically. You don't need to understand Docker to get running. Visit https://www.agent-zero.ai and look right above the install scripts. There is a download link for your platform and a link to a Launcher first run guide. - Mac Intel - https://github.com/agent0ai/a0-launcher/releases/download/v0.9/a0-launcher-0.9-macos-x64.dmg - Linux x86 - https://github.com/agent0ai/a0-launcher/releases/download/v0.9/a0-launcher-0.9-linux- - Windows x86 - https://github.com/agent0ai/a0-launcher/releases/download/v0.9/a0-launcher-0.9-windows-x64.exe ARM64 - Mac Apple Silicon - https://github.com/agent0ai/a0-launcher/releases/download/v0.9/a0-launcher-0.9-macos-arm64.dmg - Linux ARM64 - https://github.com/agent0ai/a0-launcher/releases/download/v0.9/a0-launcher-0.9-linux-arm64.AppImage - Windows ARM64](https://github.com/agent0ai/a0-launcher/releases/download/v0.9/a0-launcher-0.9-windows-arm64.exe) | 2. Agent Zero Core v2.0 The engine itself: native Responses API transport (with chat-completions fallback), inspectable parallel tool calls, project-scoped MCP configuration with search and scanning, a Skills Scanner for checking packages before import, and a refreshed WebUI across welcome, composer, settings, mobile and the shared canvas. Full changelog at https://github.com/agent0ai/agent-zero/releases

So I have a interesting setup. i big Unraid Server with a very small 5GB Nvidia Quadro P2200. My Ollama VM is 100GB RAM and has the Nvidia Quadro P2200 passed through to yet. I then have a Agent-Zero Docker container latest as of yesterday. The Models are Chat = qwen2.5:3b Utility = qwen2.5:1.5b When as it to create an create an ebook I get the following error. ValueError: Tool request must have a tool_name (type string) field Traceback (most recent call last): Traceback (most recent call last): File "/a0/helpers/extension.py", line 176, in _run_async data["result"] = await data["result"] ^^^^^^^^^^^^^^^^^^^^ File "/a0/agent.py", line 572, in handle_exception raise exception # exception handling is done by extensions ^^^^^^^^^^^^^^^ File "/a0/agent.py", line 485, in monologue tools_result = await self.process_tools(agent_response) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/a0/helpers/extension.py", line 183, in _run_async result = _process_result(data) ^^^^^^^^^^^^^^^^^^^^^ File "/a0/helpers/extension.py", line 143, in _process_result raise exc File "/a0/helpers/extension.py", line 176, in _run_async data["result"] = await data["result"] ^^^^^^^^^^^^^^^^^^^^ File "/a0/agent.py", line 854, in process_tools await self.validate_tool_request(tool_request) File "/a0/helpers/extension.py", line 183, in _run_async result = _process_result(data) ^^^^^^^^^^^^^^^^^^^^^ File "/a0/helpers/extension.py", line 143, in _process_result raise exc File "/a0/helpers/extension.py", line 176, in _run_async data["result"] = await data["result"] ^^^^^^^^^^^^^^^^^^^^ File "/a0/agent.py", line 956, in validate_tool_request raise ValueError("Tool request must have a tool_name (type string) field")

Hello Everyone, I have been trying to get Agent-Zero up and running on my configuration at home, but I am running into what I think is a timing issue with the LLMS. I am trying to get Agent-Zero working with LLMSTER (The headless version of LLM Studio). Here is my setup that I have tried but it can never respond just gives me an error. I will put a picture of the error here. Setup (Running everything on a UnRaid ProServer 7.2.4 (With 256GB RAM, 8GB Nvidia card , with Nvidia Plugin): Virtual Machine - LLMSTER Server - 200GB RAM - Virtual card - 1 TB Hard Drive - Ubuntu 24.04.4 Server - What I have tried as the Chat and Utility models - Qwen3.5 122B A10B [Q4_K_M] (75.12 GB) - mistral-small-24b-instruct-2501 - Gemma-4-31B-it - Gemma-4-26B-A4B-it - I have also tried context 32768 to 16384 (For each one and matching Agent-Zero settings) Docker Container Agent-Zero I have made sure that Agent-Zero can talk to the LLMSTER VM. Any ideas or recommendations on which models to use? I wish I had a big NVIDIA card but I only have this server. with lots of ram. lol Thanks in advance