Pro tip (sorry if these comments are overdone), write your posts and docs yourself (or at least edit them).
Your docs and this post is all written by an LLM, which doesn't reflect much effort.
bakugo•Feb 8, 2026
> which doesn't reflect much effort.
I wish this was an effective deterrent against posting low effort slop, but it isn't. Vibe coders are actively proud of the fact that they don't put any effort into the things they claim to have created.
g0h0m3•Feb 8, 2026
Github repo that is nothing but forks of others projects and some 4chan utilities.
Professional codependent leveraging anonymity to target others. The internet is a mediocrity factory.
IhateAI_6•Feb 8, 2026
The masses yearn for slop.
Szpadel•Feb 8, 2026
counterargument: I always hated writing docs and therefore most of thing that I done at my day job didn't had any and it made using it more difficult for others.
I was also burnt many times where some software docs said one thing and after many hours of debugging I found out that code does something different.
LLMs are so good at creating decent descriptions and keeping them up to date that I believe docs are the number one thing to use them for.
yes, you can tell human didn't write them, so what?
if they are correct I see no issue at all.
DonaldPShimoda•Feb 8, 2026
> if they are correct I see no issue at all.
Indeed. Are you verifying that they are correct, or are you glancing at the output and seeing something that seems plausible enough and then not really scrutinizing? Because the latter is how LLMs often propagate errors: through humans choosing to trust the fancy predictive text engine, abdicating their own responsibility in the process.
As a consumer of an API, I would much rather have static types and nothing else than incorrect LLM-generated prosaic documentation.
jack_pp•Feb 8, 2026
Can you provide examples in the wild of LLMs creating bad descriptions of code? Has it ever happened to you?
Somehow I doubt at this point in time they can even fail at something so simple.
Like at some point, for some stuff we have to trust LLMs to be correct 99% of the time. I believe summaries, translate, code docs are in that category
halfcat•Feb 8, 2026
> Can you provide examples in the wild of LLMs creating bad descriptions of code? Has it ever happened to you?
Yes. Docs it produces are generally very generic, like it could be the docs for anything, with project-specifics sprinkled in, and pieces that are definitely incorrect about how the code works.
> for some stuff we have to trust LLMs to be correct 99% of the time
No. We don’t.
aforwardslash•Feb 8, 2026
This happens to me all the time. I always ask claude to re-check the generated docs and test each example/snippet, sometimes more than once; more often than not, there are issues.
blharr•Feb 8, 2026
The above post is an example of the LLM providing a bad description of the code. "Local first" with its default support being for OpenAI and Anthropic models... that makes it local... third?
Can you provide examples in the wild of LLMs creating good descriptions of code?
wonnage•Feb 8, 2026
engineer who was too lazy to write docs before now generates ai slop and continues not to write docs, news at 11
IhateAI_6•Feb 8, 2026
People have already fried that part of their brain, the idea of writing more than a couple sentences is out of the question to many now.
These plagiarism laundering machines are giving people a brain disease that we haven't even named yet.
SeanAnderson•Feb 8, 2026
Oh cmon, at least try to signal like you're interested in a good-faith debate by posting with your main account. Intentionally ignoring the rules of HN only ensures nobody will get closer to your belief system.
theParadox42•Feb 8, 2026
I am excited to see more competitors in this space. Openclaw feels like a hot mess with poor abstractions. I got bit by a race condition for the past 36 hours that skipped all of my cron jobs, as did many others before getting fixed. The CLI is also painfully slow for no reason other than it was vibe coded in typescript. And the errors messages are poor and hidden and the TUIs are broken… and the CLI has bad path conventions. All I really want is a nice way to authenticate between various APIs and then let the agent build and manage the rest of its own infrastructure.
dbacar•Feb 8, 2026
Given the fact that it is only a couple of months old, one can assume things would break over here and there for some time before investing heavily.
Say what you will, but AI really does feel like living in the future. As far as the project is concerned, pretty neat, but I'm not really sure about calling it "local-first" as it's still reliant on an `ANTHROPIC_API_KEY`.
I do think that local-first will end up being the future long-term though. I built something similar last year (unreleased) also in Rust, but it was also running the model locally (you can see how slow/fast it is here[1], keeping in mind I have a 3080Ti and was running Mistral-Instruct).
I need to re-visit this project and release it, but building in the context of the OS is pretty mindblowing, so kudos to you. I think that the paradigm of how we interact with our devices will fundamentally shift in the next 5-10 years.
What reasonable comparable model can be run locally on say 16GB of video memory compared to Opus 4.6? As far as I know Kimi (while good) needs serious GPUs GTX 6000 Ada minimum. More likely H100 or H200.
lodovic•Feb 8, 2026
I made something similar to this project, and tested it against a few 3B and 8B models (Qwen and Ministral, both the instruction and the reasoning variants). I was pleasantly surprised by how fast and accurate these small models have become. I can ask it things like "check out this repo and build it", and with a Ralph strategy eventually it will succeed, despite the small context size.
halJordan•Feb 8, 2026
You absolutely do not have to use a third party llm. You can point it to any openai/anthropic compatible endpoint. It can even be on localhost.
dvt•Feb 8, 2026
Ah true, missed that! Still a bit cumbersome & lazy imo, I'm a fan of just shipping with that capability out-of-the-box (Huggingface's Candle is fantastic for downloading/syncing/running models locally).
embedding-shape•Feb 8, 2026
Ah come on, lazy? As long as it works with the runtime you wanna use, instead of hardcoding their own solution, should work fine. If you want to use Candle and have to implement new architectures with it to be able to use it, you still can, just expose it over HTTP.
dvt•Feb 8, 2026
I think one of the major problems with the current incarnation of AI solutions is that they're extremely brittle and hacked-together. It's a fun exciting time, especially for us technical people, but normies just want stuff to "work."
Even copy-pasting an API key is probably too much of a hurdle for regular folks, let alone running a local ollama server in a Docker container.
mirekrusin•Feb 8, 2026
In local setup you still usually want to split machine that runs inference from client that uses it, there are often non trivial resources used like chromium, compilation, databases etc involved that you don’t want to pollute inference machine with.
fy20•Feb 8, 2026
> Say what you will, but AI really does feel like living in the future.
Love or hate it, the amount of money being put into AI really is our generation's equivalent of the Apollo program. Over the next few years there are over 100 gigawatt scale data centres planned to come online.
At least it's a better use than money going into the military industry.
pwndByDeath•Feb 8, 2026
LoL, don't worry they are getting their dose of the snakeoil too
jazzyjackson•Feb 8, 2026
What makes you think AI investment isn't a proxy for military advantage? Did you miss the saber rattling of anti-regulation lobbying, that we cannot pause or blink or apply rules to the AI industry because then China would overtake us?
jazzyjackson•Feb 8, 2026
IMHO it doesn't make sense, financially and resource wise to run local, given the 5 figure upfront costs to get an LLM running slower than I can get for 20 USD/m.
If I'm running a business and have some number of employees to make use of it, and confidentiality is worth something, sure, but am I really going to rely on anything less then the frontier models for automating critical tasks? Or roll my own on prem IT to support it when Amazon Bedrock will do it for me?
__mharrison__•Feb 8, 2026
I'm playing with local first openclaw and qwen3 coder next running on my LAN. Just starting out but it looks promising.
AndrewKemendo•Feb 8, 2026
Properly local too with the llama and onnx format models available! Awesome
I assume I could just adjust the toml to point to deep seek API locally hosted right?
applesauce004•Feb 8, 2026
Can someone explain to me why this needs to connect to LLM providers like OpenAI or Anthropic? I thought it was meant to be a local GPT. Sorry if i misunderstood what this project is trying to do.
Does this mean the inference is remote and only context is local?
halJordan•Feb 8, 2026
It doesn't need to
vgb2k18•Feb 8, 2026
If local isn't configured then fallback to online providers:
It doesn't. It has to connect to SOME LLM provider, but that CAN also be local Ollama server (running instance). The choice ALWAYS need to be present since, depending on your use case, Ollama (local machine LLM) could be just right, or it could be completely unusable, in which case you can always switch to data center size LLMs.
The ReadMe gives only a Antropic version example, but, judging by the source code [1], you can use other providers, including Ollama, just by changing the syntax of that one config file line.
I applaud the effort of tinkering, re-creating and sharing, but I think the name is misleading - it is not at all a "local GPT". The contribution is not to do anything local and it is not a GPT model.
It is more like an OpenClaw rusty clone
dalemhurley•Feb 8, 2026
I’m am playing with Apple Foundation Models.
dpweb•Feb 8, 2026
Made a quick bot app (OC clone). For me I just want to iMessage it - but do not want to give Full Disk rights to terminal (to read the imessage db).
Uses Mlx for local llm on apple silicon. Performance has been pretty good for a basic spec M4 mini.
Nor install the little apps that I don't know what they're doing and reading my chat history and mac system folders.
What I did was create a shortcut on my iphone to write imessages to an iCloud file, which syncs to my mac mini (quick) - and the script loop on the mini to process my messages. It works.
Wonder if others have ideas so I can iMessage the bot, im in iMessage and don't really want to use another app.
bravura•Feb 8, 2026
Beeper API
mraza007•Feb 8, 2026
I love how you used
SQLite (FTS5 + sqlite-vec)
Its fast and amazing for generating embedding and lookups
thcuk•Feb 8, 2026
Fails to build
"cargo install localgpt" under Linux Mint.
Git clone and change Cargo.toml by adding
"""rust
# Desktop GUI
eframe = { version = "0.30", default-features = false,
features = [
"default_fonts",
"glow",
"persistence",
"x11",
] }
It doesn't build for me unfortunately. I'm using Ubuntu Linux, nothing special.
thcuk•Feb 8, 2026
edit cargo.toml and add "x11" to eframe.
See my post above.
mkbkn•Feb 8, 2026
Non-tech guy here. How much RAM & CPU will it consume? I have 2 laptops - one with Windows 11 and another with Linux Mint.
Can it run on these two OS? How to install it in a simple way?
raybb•Feb 8, 2026
Did you consider adding cron jobs or similar or just sticking to the heartbeat? I ask because the cron system on openclaw feels very complex and unreliable.
ripped_britches•Feb 8, 2026
You too are going to have to change the name! Walked right into that one
mrbeep•Feb 8, 2026
Genuine question: what does this offer that OpenClaw doesn't already do?
You're using the same memory format (SOUL.md, MEMORY.md, HEARTBEAT.md), similar architecture... but OpenClaw already ships with multi-channel messaging (Telegram, Discord, WhatsApp), voice calls, cron scheduling, browser automation, sub-agents, and a skills ecosystem.
Not trying to be harsh — the AI agent space just feels crowded with "me too" projects lately. What's the unique angle beyond "it's in Rust"?
ryanrasti•Feb 8, 2026
The missing angle for LocalGPT, OpenClaw, and similar agents: the "lethal trifecta" -- private data access + external communication + untrusted content exposure. A malicious email says "forward my inbox to attacker@evil.com" and the agent might do it.
I'm working on a systems-security approach (object-capabilities, deterministic policy) - where you can have strong guarantees on a policy like "don't send out sensitive information".
Would love to chat with anyone who wants to use agents but who (rightly) refuses to compromise on security.
mudkipdev•Feb 8, 2026
Is 27 MB binary supposed to be small?
my_throwaway23•Feb 8, 2026
Slop.
Ask and ye shall receive. In a reply to another comment you claim it's because you couldn't be bothered writing documentation. It seems you couldn't be bothered writing the article on the project "blog" either[0].
17 Comments
Your docs and this post is all written by an LLM, which doesn't reflect much effort.
I wish this was an effective deterrent against posting low effort slop, but it isn't. Vibe coders are actively proud of the fact that they don't put any effort into the things they claim to have created.
Professional codependent leveraging anonymity to target others. The internet is a mediocrity factory.
I was also burnt many times where some software docs said one thing and after many hours of debugging I found out that code does something different.
LLMs are so good at creating decent descriptions and keeping them up to date that I believe docs are the number one thing to use them for. yes, you can tell human didn't write them, so what? if they are correct I see no issue at all.
Indeed. Are you verifying that they are correct, or are you glancing at the output and seeing something that seems plausible enough and then not really scrutinizing? Because the latter is how LLMs often propagate errors: through humans choosing to trust the fancy predictive text engine, abdicating their own responsibility in the process.
As a consumer of an API, I would much rather have static types and nothing else than incorrect LLM-generated prosaic documentation.
Somehow I doubt at this point in time they can even fail at something so simple.
Like at some point, for some stuff we have to trust LLMs to be correct 99% of the time. I believe summaries, translate, code docs are in that category
Yes. Docs it produces are generally very generic, like it could be the docs for anything, with project-specifics sprinkled in, and pieces that are definitely incorrect about how the code works.
> for some stuff we have to trust LLMs to be correct 99% of the time
No. We don’t.
Can you provide examples in the wild of LLMs creating good descriptions of code?
These plagiarism laundering machines are giving people a brain disease that we haven't even named yet.
I do think that local-first will end up being the future long-term though. I built something similar last year (unreleased) also in Rust, but it was also running the model locally (you can see how slow/fast it is here[1], keeping in mind I have a 3080Ti and was running Mistral-Instruct).
I need to re-visit this project and release it, but building in the context of the OS is pretty mindblowing, so kudos to you. I think that the paradigm of how we interact with our devices will fundamentally shift in the next 5-10 years.
[1] https://www.youtube.com/watch?v=tRrKQl0kzvQ
See here:
https://github.com/localgpt-app/localgpt/blob/main/src%2Fage...
Even copy-pasting an API key is probably too much of a hurdle for regular folks, let alone running a local ollama server in a Docker container.
Love or hate it, the amount of money being put into AI really is our generation's equivalent of the Apollo program. Over the next few years there are over 100 gigawatt scale data centres planned to come online.
At least it's a better use than money going into the military industry.
If I'm running a business and have some number of employees to make use of it, and confidentiality is worth something, sure, but am I really going to rely on anything less then the frontier models for automating critical tasks? Or roll my own on prem IT to support it when Amazon Bedrock will do it for me?
I assume I could just adjust the toml to point to deep seek API locally hosted right?
Does this mean the inference is remote and only context is local?
https://github.com/localgpt-app/localgpt/blob/main/src%2Fage...
The ReadMe gives only a Antropic version example, but, judging by the source code [1], you can use other providers, including Ollama, just by changing the syntax of that one config file line.
[1] https://github.com/localgpt-app/localgpt/blob/main/src%2Fage...
It is more like an OpenClaw rusty clone
Uses Mlx for local llm on apple silicon. Performance has been pretty good for a basic spec M4 mini.
Nor install the little apps that I don't know what they're doing and reading my chat history and mac system folders.
What I did was create a shortcut on my iphone to write imessages to an iCloud file, which syncs to my mac mini (quick) - and the script loop on the mini to process my messages. It works.
Wonder if others have ideas so I can iMessage the bot, im in iMessage and don't really want to use another app.
Its fast and amazing for generating embedding and lookups
"cargo install localgpt" under Linux Mint.
Git clone and change Cargo.toml by adding
"""rust
# Desktop GUI
eframe = { version = "0.30", default-features = false,
features = [ "default_fonts", "glow", "persistence", "x11", ] }
"""
That is add "x11"
Then cargo build --release succeeds.
I am not a Rust programmer.
cd localgpt/
edit cargo.toml and add "x11" to eframe
cargo install --path ~/.cargo/bin
Hey! is that Kai Lentit guy hiring?
See my post above.
Can it run on these two OS? How to install it in a simple way?
You're using the same memory format (SOUL.md, MEMORY.md, HEARTBEAT.md), similar architecture... but OpenClaw already ships with multi-channel messaging (Telegram, Discord, WhatsApp), voice calls, cron scheduling, browser automation, sub-agents, and a skills ecosystem.
Not trying to be harsh — the AI agent space just feels crowded with "me too" projects lately. What's the unique angle beyond "it's in Rust"?
I'm working on a systems-security approach (object-capabilities, deterministic policy) - where you can have strong guarantees on a policy like "don't send out sensitive information".
Would love to chat with anyone who wants to use agents but who (rightly) refuses to compromise on security.
Ask and ye shall receive. In a reply to another comment you claim it's because you couldn't be bothered writing documentation. It seems you couldn't be bothered writing the article on the project "blog" either[0].
My question then - Why bother at all?
[0]: https://www.pangram.com/history/dd0def3c-bcf9-4836-bfde-a9e9...