Alternatives
Products that do what Tlume – a CLI tool that converts Tart VM images for Lume does
Shoutout to our amazing contributor @iaktech for building tlume - a CLI tool that converts Tart VM images into the format expected by Lume! tlume will: - Locate your Tart VM in ~/.tart/vms/ - Create a Lume VM in ~/.lume/ - Copy all VM files with optimized buffering - Convert the Tart config to Lume format - Preserve all your VM hardware settings, network config, and display settings This new bridge interface will greatly simplify adoption for those with existing Tart images and help commoditize Apple Virtualization.framework solutions across the ecosystem! Lume repo:…
- 1LO
We just open-sourced Lume - a tool we built after hitting walls with existing virtualization options on Apple Silicon. No GUI, no complex stacks - just a single binary that lets you spin up macOS or Linux VMs via CLI or API. Why we built Lume: - Run native macOS VMs in 1 command, using Apple Virtualization.Framework: `lume run macos-sequoia-vanilla:latest` - Prebuilt images on https://ghcr.io/trycua (macOS, Ubuntu on ARM) - API server to manage VMs programmatically `POST /lume/vms` - A python SDK on github.com/trycua/pylume Run prebuilt macOS images in just…
2025 · github.com
- 2L0
Hey HN, Lume is an open-source CLI for running macOS and Linux VMs on Apple Silicon. Since launch (https://news.ycombinator.com/item?id=42908061), we've been using it to run AI agents in isolated macOS environments. We needed VMs that could set themselves up, so we built that. Here's what's new in 0.2: *Unattended Setup* – Go from IPSW to a fully configured VM without touching the keyboard. We built a VNC + OCR system that clicks through macOS Setup Assistant automatically. No more manual setup before pushing to a registry: lume create my-vm --os macos --ipsw latest…
Jan 2026 · cua.ai
- 3YA
Built this for my LLM workflows - needed searchable, persistent memory that wouldn't blow up storage costs. I also wanted to use it locally for my research. It's a content-addressed storage system with block-level deduplication (saves 30-40% on typical codebases). I have integrated the CLI tool into most of my workflows in Zed, Claude Code, and Cursor, and I provide the prompt I'm currently using in the repo. The project is in C++ and the build system is rough around the edges but is tested on macOS and Ubuntu 24.04.
2025 · github.com
- 4VC
I've long wanted to harness QEMU/KVM for my desktop virtual machines, but I'm befuddled by virt-manager's lack of support for working NVIDIA 3D acceleration, dogmatic embrace of ugly XML, and the puzzling UI decision of having to click what seems like 15 buttons to attach an ISO to a VM image. When I further learned that NVIDIA's broken 3D acceleration is the fault of libvirt as opposed to QEMU's virtio driver, I had an idea... Behold, vm-curator! A fast and friendly VM management TUI written in Rust. You can create, configure, organize, and manage VMs directly with QEMU. No libvert. No…
Jan 2026 · github.com
- 5LA
G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…
2023 · github.com
- 6LT
Current AI-assisted CLI tools are often part of larger systems and work better on Linux. I built llm-term to address these. It's a Rust-based tool that compiles into a single binary file. You only need to download the binary, add it to your PATH, and configure your OpenAI key to get started. While llm-term offers an option for gpt-4o, it works great with gpt-4o-mini. So it's not costly. I appreciate any feedback or suggestions.
2024 · github.com
- 7KD
I've built this to make it easy to host your own infra for lightweight VMs at large scale. Intended for exec of AI-generated code, for CICD runners, or for off-chain AI DApps. Mainly to avoid Docker-in-Docker dangers and mess. Super easy to use with CLI / Python SDK, friendly to AI engs who usually don't like to mess with VM orchestration and networking too much. Defense-in-depth philosophy. Would love to get feedback (and contributors: clear & exciting roadmap!), thx
Oct 2025 · github.com
- 8LL
What it is A single 45 MB Windows .exe that embeds llama.cpp and a minimal Tk UI. Copy it (plus any .gguf model) to a flash drive, double-click on any Windows PC, and you’re chatting with an LLM—no admin rights, Cloud, or network. Why I built it Existing “local LLM” GUIs assume you can pip install, pass long CLI flags, or download GBs of extras. I wanted something my less-technical colleagues could run during a client visit by literally plugging in a USB drive. How it works PyInstaller one-file build → bundles Python runtime, llama_cpp_python, and the UI into a single PE. On first launch, it…
2025 · github.com
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- 10TC
Hi HN, I built a CLI for uploading documents and querying them with an LLM agent that uses search tools rather than stuffing everything into the context window. I recorded a demo using the CrossFit 2025 rulebook that shows how this approach compares to traditional RAG and direct context injection[1]. The core insight is that LLMs running in loops with tool access are unreasonably effective at this kind of knowledge retrieval task[2]. Instead of hoping the right chunks make it into your context, the agent can iteratively search, refine queries, and reason about what it finds. The CLI handles…
2025 · github.com
- 11PR
If you just want to use it, try here - https://pdf2md.trieve.ai . I think the LLM's are astoundingly good at converting complex powerpoint style infographics. I wouldn't normally think folks on HN would find this interesting as the general concept has been posted about already in the past few months. We were heavily inspired by Zerox[1]. However, the stack we went with was fun and over-engineered which is more likely to create interesting discussion. We use all the same tools at Trieve (our main product), but wanted to see if they would be a good fit for something that needed to…
2024 · github.com
- 12RW
Hi HN, I'm Holger, a developer who worked in the lighting industry. I built this to scratch my own itch and put it on crates.io and PyPI where nothing like it existed. The old file formats (EULUMDAT from 1990, IES from 1991) still work fine for basic photometry. But the industry is moving toward spectral data – full wavelength distributions instead of just lumen values. The new standards (TM-33, ATLA-S001) are barely supported by existing tools. So this handles both: legacy formats for compatibility, spectral data for anyone who wants to work with the new standards. Stack: Rust core, then…
Dec 2025 · eulumdat.icu
- 13
- 14NT
With the latest launch from Google I've added support for Gemma 3 270M, the speed for local LLM to TTS token time is incredible! This is an heavy obvious work in progress - any contributions or tips would be welcome. The idea is to have a fast moving edge model playground, and maybe have some utility (like the e reader) on the side.
2025 · github.com
- 15IB
I had 14,000 photos sitting on a drive and wanted an excuse to play with local vision models and Elixir/Phoenix. I originally tried to get LLaVA to tell me if a photo was 'good' or matched my style, but quickly learned that LLMs have terrible taste. I ended up demoting the LLM to just extract metadata, and built a custom CLIP/Ridge Regression pipeline to actually learn my preferences based on how I rate things. The stack is Phoenix/Oban on the orchestrator side, and Python/FastAPI/Instructor for the AI workers. Happy to answer any questions about the architecture,…
Apr 2026 · qwelian.com
- 16
I made this after seeing someone posit the idea online yesterday over lunch then spent some time refining it. So far it's pretty impressive IMO! Right now I am running Qwen3-30B-A3B on my 24gb unified memory m4 MacBook Pro at 50 tok/sec and this should definitely not be working for such a large model on my middling hardware. Things are detailed in the README to get up and running and DESIGN.md has details on all the choices and such made along the way.
23d ago · github.com
- 17KP
I thought it'd be interesting to use Linux PSI (Pressure Stall Information) for an LLM runtime to trim the KV cache. This is mainly useful imo for edge devices like the Jetson Orin super nano kit which have unified memory. I haven't benched much, but plan to do so more over time and see if I can make a real use of it as I run local LLMs. Let me know if it makes sense :P (I of course vibed this idea)
Jun 2026 · github.com
- 18IB
Built a simple web app that tells you which open-source LLMs will work on your hardware. It auto-detects your specs, shows compatible models from Hugging Face, gives realistic performance estimates (tokens/sec), and recommends quantization settings. You can also manually input specs to see "what if I upgraded my RAM?" Made this after wasting time downloading giant models only to find they crawled on my hardware. Hope it saves you some frustration!
2025 · caniusellm.com
- 19NT
I built a CLI tool that turns codebases and PRs into diagrams so you can quickly understand how things fit together. Originally made it because I couldn't follow my own AI-generated repos. Just shipped a big update: - Switched from D2 to Mermaid for rendering - Tree-sitter AST parsing + agentic flow instead of raw LLM calls. ~50x faster. - Works on any GitHub repo or PR, not just local - Dropped the web frontend, it's just a CLI now - Published as a pip package Still a ton to improve and I'm building fast. Feedback, issues, PRs all welcome.
Feb 2026 · github.com
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- 22IB
Apr 2026 · github.com
- 23HA
Demo starts at 50m into the video. This was a bit terrifying to record because 2am the previous night everything was totally broken after a major refactor (so that we could add external LLM support as well as local GPUs). But pressure can be a useful force :-D We start with a stack deployed on my laptop without a GPU, pointing to together.ai so we can run open source LLMs easily without having to have access to a GPU. We show simple inference through the ChatGPT-like web interface (with users, sessions etc) and then simple drag'n'drop RAG. Then we show some helix apps defined as yaml: Marvin…
2024 · youtube.com
- 24RA
Hello there! The idea behind this CLI tool is to use it for short-term reminders, e.g. to remind you (via OS-specific notifications) to do something in 2 hours or in 10 minutes. The app is supposed to be cross-platform compatible. Still, I have limited access to platforms, so it was tested only on MacOS, Ubuntu (via VirtualBox), Fedora (via VirtualBox) and Windows 10 Home. I'd appreciate any feedback on how it works on these and other OS-es. Also, I have never tested it outside my time zone (GMT+2), so it would be nice to hear from folks from other parts of the world. Any feedback, comments,…
2023 · github.com
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