This is a really cool project and I've enjoyed exploring it. I've worked on a couple of things within this repo. My preference was to use local LLMs as opposed to LLM API keys, as I'm working on developing local LLM usage to address the enterprise concerns of data privacy. Hive supports the usage of Ollama for local model inference, which I felt was a good starting point. During development, I found the Hive docs to be primarily focused on using Claude Code and OpenAI LLM inference, and development on Linux OS. I absolutely use Linux frequently, and also understand that there are many devs using Windows as well. Issue: Hive docs needed some fleshing out to produce clear guides, walkthroughs, and examples using the above framework. How to fix: I proposed a fully fleshed out guide using Ollama models, and CLI, along with a breakdown for both Linux and Windows users. Though, WSL works, again, I wanted to appeal to less technical users that may have an interest in Hive, and suggested a less technical approach for simple PowerShell or Linux CLI instructions. Why does it matter?: There are several reasons this is important, but primarily it has to do with creating a platform that not only highly technical people can use, but also beginner or intermediate users as well. This not only broadens the audience, but also demonstrates professionalism.

I've really enjoyed using the Hive framework to build some local LLM inference projects (currently using Hive for a short term/long term memory agentic system to address context window limitations, attention deficit, and drift in long conversations.