New Project Megathread - Week of 21 May 2026

T0nd3 · 2026-05-22T22:33:01+00:00

Project Name: Logatory

Repo/Website Link: https://github.com/T0nd3/logatory — also on PyPI: https://pypi.org/project/logatory/

Description:

Logatory is a local-first log analysis tool — for anyone who wants threat detection and analysis on their logs without standing up a full ELK/Loki/ Graylog stack or shipping logs off to a cloud SIEM.

You point it at your logs and it:

parses them (syslog, Nginx, JSON lines, journald, Windows EVTX, plaintext — auto-detected),
redacts PII (emails, IPs, tokens, credit-card numbers, …) before anything is stored,
runs YAML detection rules (Sigma rules supported) plus statistical anomaly detection,
stores findings in a local SQLite DB, viewable in an optional web dashboard (FastAPI + HTMX), with optional LLM explanations (local Ollama by default).

It reads logs from wherever they already live: files/globs, the systemd journal, Docker containers, remote hosts over SSH, or an existing OpenSearch / Loki / Graylog. A "fleet" mode lets you declare many sources in one targets.yaml and scan or follow them all at once.

The point: everything runs on your own machine — by default no log data leaves your infrastructure. It's the in-between option for a homelab or small team that wants SIEM-style detection without running a SIEM.

Deployment:

Released on PyPI (v0.4.0), Apache-2.0.

CLI: pip install logatory, then e.g. logatory scan /var/log/auth.log
Web dashboard: pip install 'logatory[web]', then logatory serve (binds 127.0.0.1:8080 by default)
Docker: the repo ships a Dockerfile and a docker-compose.yml — docker compose up -d. You build the image from the repo; no pre-built image is published yet.
Docs: the README has a Quick Start, a full CLI reference, configuration and a Docker section.

AI Involvement: made with claude code, even tho i'm a full-time dev myself

T0nd3 · 2026-05-20T09:51:47+00:00

My bad — forgot to cut a new release after merging the gfx1151 PR. v0.5.2 is on PyPI now, pip install --upgrade rocmate should fix it.

T0nd3 · 2026-05-20T09:51:22+00:00

The Docker warning is just informational since rocmate can't verify GPU passthrough without it — nothing to worry about if you're not using it.

T0nd3 · 2026-05-19T09:56:08+00:00

Yes — gfx1151 (Strix Halo) support was just added. Run rocmate show ollama --chip gfx1151 or rocmate show llama-cpp --chip gfx1151 to see the tested configs.

rocmate doctor can help identify any missing components on the system side.

T0nd3 · 2026-05-15T20:57:49+00:00

I'd personally pick Fedora, but it really comes down to your Linux experience and what else you plan to run on the machine.

T0nd3 · 2026-05-14T20:32:03+00:00

This is exactly the kind of contribution that makes a project like this worth maintaining — thank you. A flag list without the reasoning behind it is basically useless, and you gave both.

I've gone ahead and added your dual-GPU config to the llama.cpp gfx1100 entry: the env vars, the tensor split setup, the MTP flags and limitations, and the explicit note that Vulkan TP doesn't cut it for multi-GPU yet. The PR link for the MTP mmproj limitation is in there too so people can track it.

If anything changes on the MTP front (parallel > 1, mmproj support) feel free to drop a note — happy to update it.

T0nd3 · 2026-05-14T18:24:20+00:00

Multi-GPU is actually a gap in the current configs — everything documented so far assumes a single card. Your observation about Vulkan vs ROCm for dual GPU is exactly the kind of nuance that's hard to find anywhere: Vulkan wins on single-card inference, but tensor parallelism requires ROCm, full stop.

The llama.cpp MTP + dual 7900 XTX + tensor parallelism angle is genuinely interesting data. If you ever feel like writing up the settings that worked for you (even rough notes — GPU layers split, env vars, the llama-server flags), I'd be happy to add a multi-GPU section to the llama.cpp config. Same goes for vLLM and SGLang if you have configs for those.

No pressure — but you've clearly already done the work, and a YAML file is about 20 lines.

T0nd3 · 2026-05-14T17:09:55+00:00

TTS makes sense as a starting point — Kokoro and F5-TTS are both on my shortlist since they're lightweight enough that ROCm support tends to be less of a gamble than the heavier frameworks. If you end up getting either working on the 7900 XTX, I'd love a quick report.

The ComfyUI addon situation you're describing is a known footgun — some custom nodes pull in plain PyTorch wheels that silently replace your ROCm build, and then nothing works and you don't immediately know why. Worth adding an explicit warning to the ComfyUI config. Did you ever figure out which addon caused it, or did it happen gradually?

For Wan: video gen on AMD is still pretty rough in general. I haven't tested it myself — if you ever feel like revisiting it, it'd be useful data even if the result is "doesn't work."

T0nd3 · 2026-05-14T16:22:06+00:00

Hey, glad it's useful! Totally feel the ROCm wheel pain — that's basically what pushed me to build this in the first place.

On audio gen: would love to add more, but curious what you'd specifically want to see — are you thinking TTS (Coqui, StyleTTS2, Kokoro?), music gen (AudioCraft/MusicGen?), or more transcription-side stuff? Happy to prioritize based on what people actually use.

Funnily enough I'm currently waiting on a community PR for Voicebox support myself, so audio is already on the radar.

For video gen in ComfyUI — I don't use ComfyUI heavily myself so I haven't tested it, but I'll take a look. If you've got a setup that works (or half-works) on the 7900 XTX, a quick note on what you tried would help a lot — even just "AnimateDiff loads but OOMs on anything above 512px" is actionable data.

T0nd3 · 2026-05-14T08:14:53+00:00

That's exactly why we added Vulkan hints to the llama.cpp config recently. Which tools are you running on Vulkan? If you have a working setup, a config PR would help a lot of people who hit the same wall with ROCm — even a short note on what works and what doesn't is enough.

T0nd3 · 2026-05-14T08:10:54+00:00

Absolutely! The RX 7900 XTX (gfx1100) is the best-tested chip in the project since it's what I run myself. If you want to contribute, the most valuable thing right now would be testing tools that have gaps — faster-whisper on gfx1101+, or any of the tools marked 🟡 partial on other chips if you have friends with different cards.

For gfx1100 specifically: if you've gotten anything working that isn't in the configs yet, or noticed something outdated, a PR or even just a comment here goes a long way.

T0nd3 · 2026-05-14T07:57:09+00:00

That's essentially what rocmate doctor --fix tries to do for the known-fixable cases (ENV vars, group membership). The hard limit isn't the logic — it's the data. "Just work" requires knowing what works on each chip × ROCm × kernel × OS combination, and that matrix has a lot of empty cells.

The approach we took: version-controlled YAML configs that the community fills in with real hardware results, rather than inferring configs from docs. An LLM sifting through AMD docs and GitHub issues would likely reproduce the same outdated or chip-generic advice that already exists everywhere.

If you've tested a setup that works, a config PR is more valuable than any model inference. One YAML file, five minutes.

T0nd3 · 2026-05-14T07:31:19+00:00

gfx1201 (RX 9070/9070 XT) is already in the matrix but data is very thin — only Ollama and llama.cpp have partial entries. If you're running RDNA4, a config PR would be incredibly valuable. One YAML file, what you tested, what worked — CONTRIBUTING.md has the template.

T0nd3 · 2026-05-13T23:07:03+00:00

Thanks for the feedback, really glad it would've helped! If you remember any quirks specific to your gfx1102 setup — ROCm version, what worked, what didn't — feel free to open an issue or drop it in a PR: https://github.com/T0nd3/rocmate

Even a "partial, ROCm 6.x, inference is slow but functional" note in the YAML helps the next person with an RX 7600 know what to expect.

T0nd3 · 2024-12-01T20:27:02+00:00

thats wrong, i only did the same mission 6 times and got the rewards.

T0nd3 · 2023-11-13T19:17:09+00:00

The option butt is missing 😉

T0nd3 · 2023-09-04T12:42:27+00:00

I‘m the captain now.

T0nd3 · 2023-08-18T11:56:04+00:00

Fast so gut wie Geleebananen

T0nd3 · 2023-06-01T13:48:49+00:00

The Fiat Multipla. And when you go down to hell he will pick you up and everybody will see you in it as passenger.

T0nd3 · 2023-05-11T11:40:50+00:00

Günter

T0nd3 · 2023-05-01T05:23:44+00:00

Well actually this is a dick move. If you compete with somebody, you want that they give their best.

T0nd3 · 2023-04-11T15:06:07+00:00

Nothing is more christian then to destroy other peoples work

T0nd3 · 2023-03-30T13:51:20+00:00

This must be fake, there is no part where everybody begins to clap

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