It depends on vendor really - I have Lenovo T480 and I replaced keyboard earlier this year (there are various options like w/ or w/o backlit + layout (I'm Czech), I have 2 batteries - one for "normal" use and extended one (in size and capacity) for traveling, changing multiple SSDs and RAM is possible (not soldered)... it's not framework, but easily fixable and Linux friendly HW.
T480 is indeed superb (except for being on the heavy side). I accidentally hurled my phone into the screen (both were on the bed and I shook the sheets trying to find the beeping phone). The replacement screen was like $75 and a 5 minute job. On MacBooks that’s typically closer to $600.
I’ll probably replace it eventually with a t14 which is pretty light these days.
the T series thinkpads tend to have a high repairability rating (9/10 on ifixit ) and easy affordable access to parts, it's the X series that's a PITA imo
Is there any generally agreed upon and reliable source for replacement batteries? Given the fire risk, I'm much less willing to take the risk of substandard aftermarket parts when it comes to batteries.
Lenovo stopped selling the batteries for the T480, so the only sources are various 3rd party manufacturers I've never heard of.
++on older Lenovo. Something that Framework might have after many years is a viable secondary and third party market for repair components. Lenovo has also done a great job with keeping their detailed service manuals online and available.
This is so true! But the adventure doesn't end there. I have 2 billing accounts from the past when I was building projects on AppEngine. Annual exercise to keep them alive (even if no action is needed in the end) is of similar complexity. Why do I need these accounts? Because I want to use Google services for which I don't pay.
"In the good old days, it was a good practice to run a new protocol proposal through some standards bodies like W3C or OASIS, which was mostly a useful exercise. Is the world somewhere else already, or would it be a waste of time?"
Rear is a really interesting project with admirable goals. I believe this is just the beginning, but you have already done a great job!
I have been working on my note-taking application (https://github.com/dvorka/mindforger) for some time and wanted to go in the same direction. However, I gave up (for now). I used ggerganov/llama.cpp to host LLM models locally on a CPU-only machine with 32GB RAM, and used them for both RAG and note-taking use cases (like https://www.mindforger.com/index-200.html#llm). However, it did not work well for me - the performance was poor (high hardware utilization, long response times, failures, and crashes) and the actual responses were rarely useful (off-topic and impractical responses, hallucinations). I tried llama-2 7B with 4b quantization and a couple of similar models. Although I'm not happy about it, I switched to an online commercial LLM because it performs really well in terms of response quality, speed, and affordability. I frequently use the integrated LLM in my note-taking app as it can be used for many things.
Anyway, Reor "only" uses the locally hosted LLM in the generation phase of the RAG, which is a nicely constraint use case. I believe that a really lightweight LLM - I'm thinking about a tiny base model fine-tuned for summarization - could be the way to go (fast, non-hallucinating). I'm really curious to know if you have any suggestions or if you will have any in the future!
As for the vector DB, considering the resource-related problems I mentioned earlier, I was thinking about something similar to facebookresearch/faiss, which, unlike LanceDB, is not a fully-fledged vector DB. Have you made any experiments with similarity search projects or vector DBs? I would be interested in the trade-offs similar to small/large/hosted LLMs.
Overall, I think that both RAG with my personal notes as a corpus and a locally hosted generic purpose LLM for the use cases I mentioned above can take personal note-taking apps to a new level. This is the way! ;)
