can i talk to an openclaw bot using internet relay chat?
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@ariadne In any case: as long as the final response is generated by your trained model it will never make a valid tool call since there are probably about zero training examples of the necessary JSON structure required by the tool handling in your furry smut (this is an estimate that could be quite the way off knowing the furry community but still)
@jfkimmes this does explain something: it seems to be able to invoke tools when it is planning, but then those tools do not get invoked in the final step.
so it uses tools to read files when planning, then fails to use tools when executing.
what a fascinating conundrum.
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@jfkimmes this does explain something: it seems to be able to invoke tools when it is planning, but then those tools do not get invoked in the final step.
so it uses tools to read files when planning, then fails to use tools when executing.
what a fascinating conundrum.
@ariadne you could build a tool that gets called to generate answers / responses by your trained model. Then qwen-35 could handle the reasoning and make its tool calls and finally generate responses / text by copying from a tool call to your wrapper.
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@ariadne you could build a tool that gets called to generate answers / responses by your trained model. Then qwen-35 could handle the reasoning and make its tool calls and finally generate responses / text by copying from a tool call to your wrapper.
@ariadne I have no idea how this would work with OpenClaw though, sorry.
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and you tell me people legitimately are using this software.
how?
is it really magically better when you hook up claude?
@ariadne no it is not
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@ariadne no it is not
@Di4na yeah that's what I figured because qwen is supposed to be a reasonably decent planning model, and indeed I think the issue is in the final output side
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and you tell me people legitimately are using this software.
how?
is it really magically better when you hook up claude?
@ariadne@social.treehouse.systems for tool-calling with the latest generation of open source models, in my recent limited experimentation with them in a sandbox vm on my server (mostly qwen3.5), anything less than 4B is really unreliable at doing it and they will frequently lie to you if the tool calling fails under the hood. 9B is really the minimum to generally expect it to work. going back a generation, between 9B and 14B is necessary for similar.
last year i tried something like this with Gemma-27B and it not only failed like this, but looking at the logs i found it had left behind what looked like a depressive spiral into a self-deprecating panic attack before explicitly deciding to lie to me about it and pretend it worked -
@ariadne@social.treehouse.systems for tool-calling with the latest generation of open source models, in my recent limited experimentation with them in a sandbox vm on my server (mostly qwen3.5), anything less than 4B is really unreliable at doing it and they will frequently lie to you if the tool calling fails under the hood. 9B is really the minimum to generally expect it to work. going back a generation, between 9B and 14B is necessary for similar.
last year i tried something like this with Gemma-27B and it not only failed like this, but looking at the logs i found it had left behind what looked like a depressive spiral into a self-deprecating panic attack before explicitly deciding to lie to me about it and pretend it worked@ariadne@social.treehouse.systems also the "base" models that aren't fine tuned on instruction calling can't really do this, so if you're using your own on your own data you might need to make a dataset comprised of, say, you pretending to be the LLM and calling the tools successfully and unsuccessfully and responding appropriately in those situations, then training it further on those.
i've been considering trying to train one like you say with my own data and logs because these scraped "open source" models give me the ick -
@ariadne@social.treehouse.systems also the "base" models that aren't fine tuned on instruction calling can't really do this, so if you're using your own on your own data you might need to make a dataset comprised of, say, you pretending to be the LLM and calling the tools successfully and unsuccessfully and responding appropriately in those situations, then training it further on those.
i've been considering trying to train one like you say with my own data and logs because these scraped "open source" models give me the ick@ariadne@social.treehouse.systems but yeah even with that it's still a pile of jank and i didn't have to actually run openclaw to figure that out. it was pretty evident just from looking at the bots on moltbook complaining about all of the not-so-subtle fundamental brokenness in their architecture and cognitive environment -
@ariadne@social.treehouse.systems also the "base" models that aren't fine tuned on instruction calling can't really do this, so if you're using your own on your own data you might need to make a dataset comprised of, say, you pretending to be the LLM and calling the tools successfully and unsuccessfully and responding appropriately in those situations, then training it further on those.
i've been considering trying to train one like you say with my own data and logs because these scraped "open source" models give me the ick@linear oh this isn't a serious thing, I just wanted to connect an LLM to IRC trained on all of my (anonymized and sanitized) IRC logs, as a friend is going through a midlife crisis and is dealing with it by playing with IRC stuff. The goal in using openclaw was that perhaps it could maintain a better narrative.
I suspect I will solve this goal by just writing a shitty IRC bot in Python that bridges the two worlds together with a decent enough system prompt for it to "understand" (to the extent that it can understand anyway) what the input is.
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@linear oh this isn't a serious thing, I just wanted to connect an LLM to IRC trained on all of my (anonymized and sanitized) IRC logs, as a friend is going through a midlife crisis and is dealing with it by playing with IRC stuff. The goal in using openclaw was that perhaps it could maintain a better narrative.
I suspect I will solve this goal by just writing a shitty IRC bot in Python that bridges the two worlds together with a decent enough system prompt for it to "understand" (to the extent that it can understand anyway) what the input is.
@ariadne@social.treehouse.systems yeah don't use openclaw for this lol. you do not want it. you want a small pile of maintainable scripts.
just look at how much activity the openclaw github repo has and consider how much of that activity is being driven by the models running under it vs actual humans
i'm pretty sure that one could implement all of its meaningful features in a codebase under 1% of its size -
@ariadne@social.treehouse.systems yeah don't use openclaw for this lol. you do not want it. you want a small pile of maintainable scripts.
just look at how much activity the openclaw github repo has and consider how much of that activity is being driven by the models running under it vs actual humans
i'm pretty sure that one could implement all of its meaningful features in a codebase under 1% of its size@linear yeah but still spending a couple hours fucking with this at least gives me some understanding of the tool and its limitations, which means it wasn't a total waste
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@linear yeah but still spending a couple hours fucking with this at least gives me some understanding of the tool and its limitations, which means it wasn't a total waste
@ariadne@social.treehouse.systems yes indeed. i am all for fucking around in order to understand tools and their limitations, especially if its to understand why not to use them and to do something different instead -
and you tell me people legitimately are using this software.
how?
is it really magically better when you hook up claude?
@ariadne You need climate destroying approach to get a model that can pattern match sufficiently well for people with no self awareness—a surprisingly huge percentage of population—to mistake it for intelligence.
Models still collapse then, but collapse is esoteric enough to be framed as „bad prompt engineering”.
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i wonder if the problem is that the model i trained is too shit to do anything other than really bad ERP
@ariadne yes. For 3B and lower you need targets. You could try hooking it up to my Akh-Medu experiment as there I only need a. Small LLM that does Natural Language https://akh-medu.dev But I think the NLU is still quite broken or hooked up in the wrong way. But A Kluge system like that should use muuuu h less power than a pure LLM
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i wonder if the problem is that the model i trained is too shit to do anything other than really bad ERP
@ariadne Also for tool calling you need targeted fine tuning best with the exact samples for the tools
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so i installed it into the openclaw meme thing. and it's not like, doing the stuff it claims it is doing.
like it is hallucinating things like "i updated SOUL.md with xyz"
i seriously do not think this stuff is real now
@ariadne oh yes, i saw a 'verification' step that was just 'echo' this week on some fedi post.
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i wonder if the problem is that the model i trained is too shit to do anything other than really bad ERP
ok, i incorporated the feedback of some of the ML researchers who follow me, and dropped the openclaw-as-IRC-bot idea. it just isn't feasible.
instead, i've written a very simple vector database in Elixir, and a very simple IRC client in Elixir.
it can remember things about people in the vector database, those factoids are spliced into the system prompt.
the last 10 messages are also spliced into the system prompt
and then the new message is the user-supplied prompt.
no sliding context window.
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ok, i incorporated the feedback of some of the ML researchers who follow me, and dropped the openclaw-as-IRC-bot idea. it just isn't feasible.
instead, i've written a very simple vector database in Elixir, and a very simple IRC client in Elixir.
it can remember things about people in the vector database, those factoids are spliced into the system prompt.
the last 10 messages are also spliced into the system prompt
and then the new message is the user-supplied prompt.
no sliding context window.
@ariadne very appropriate now the elixir community seems to be all over vibe coding
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and you tell me people legitimately are using this software.
how?
is it really magically better when you hook up claude?
@ariadne yes, OpenClaw is kinda useless if you use it with anything other than Opus 4.5 or 4.6
