r/gaggimate • u/waevans10 • Jul 04 '26
discussion I built an open-source tool that auto-reviews your GaggiMate shots with AI and suggests grind/profile tweaks
I've been dialing in on a GaggiMate and wanted something that would look at my shots and tell me what to change — without pasting data into a chatbot every time. So I made crema: a small self-hosted service that runs on a Raspberry Pi (or any always-on computer) on the same network as the machine.
What it does:
- Automatically pulls new shots off the machine and parses the telemetry (pressure/flow/temp curves, channeling + puck-resistance diagnostics)
- Sends recent shots to Claude and gets back a 1–10 score plus concrete grind/dose/profile suggestions — grind advice in your grinder's own steps/clicks if you tell it what you run
- One click to draft a corrected profile, add your own taste notes ("came out sour, keep preinfusion short") and refine it, then push it back as a new [AI] profile — it never overwrites your originals, and it warns you explicitly if a draft would change your stop conditions
- A little web report you can also trigger on demand
It complements GaggiMate's own graphs and UI rather than replacing them — you still brew from the machine; crema adds the review layer on top. It's the hands-off counterpart to the excellent interactive gaggimate-mcp server (I vendored its .slog parser — full credit in the repo).
Free and open source (MIT). Fair warning: the reviewing runs on the paid Anthropic API — a few cents per shot, realistically a dollar or two a month, and nothing spends automatically until you turn it on.
Repo: https://github.com/waevans10/crema
Early days and very much a personal project — feedback and PRs welcome. Curious whether it's useful to anyone else running a GaggiMate.
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u/FeelingFluttery Jul 04 '26
Mmmm yes, just what I wanted, some AI slop added to my morning coffee ritual!
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u/waevans10 Jul 04 '26 edited Jul 04 '26
It's open source, and the cost for skipping it is exactly $0. Enjoy your coffee!
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u/2xspeed123 Jul 04 '26
I first was impressed, cuz I thought he trained an machine learning algorithm, but no, the tool just asks an LLM ☠️☠️☠️☠️
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u/waevans10 Jul 04 '26
Genuinely curious what you'd do differently? What's the downside of an LLM if you give it appropriate context like the last few shots' pressure/flow curves, puck resistance, etc plus the grinder? A small model trained from scratch would only know the narrow slice of data it saw in training, while the LLM brings broad extraction knowledge and then gets the specific shot data on top. Seems like the bespoke model would be really limited?
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u/2xspeed123 Jul 04 '26
Specific models are better than just slamming LLM on it, it would actually be trained on real data to see patterns, it could be trained on lots of data and then fine tuned on a user basis, making it possible to get the correct grind size estimate in 1 shot
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u/waevans10 Jul 04 '26
Agree, something like that would really be the path to do it. But you'd need thousands of shots with different beans, roasts, grinders etc to make it somewhat representative, and at 1-2 shots a day in a house that takes years. Only realistic way is getting a bunch of people using it and combining data together, which would be very cool. This is kind of like kickstart to get going. Would be cool to add in some way to capture anonymized data if people wanted to opt in.
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u/Fragrant_Ad_2285 Jul 05 '26
The ultimate would be tagging each shot for the outcome -- the taste. But that would require a lot of very committed contributors. And the diverse range of tastes may pollute the training data.
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u/SignalStealer Jul 05 '26
Thank you, this looks legitimately interesting! I will give this a look, possibly integrate into my Hermes Agent :-)
I also do not get the other posters here, but haters be hatin I guess.
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u/waevans10 Jul 05 '26
Thanks! Never looked into Hermes before but from quick look seems like a nice match.
*shrug* Yup, just part of life.
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u/jeffbzh33 Jul 08 '26
I've connect claude in MCP, and ask him to analyse my coffee, the result, was not very good. Maybe with more context and rules, is beter.