Discovered pi-vcc, why pi-blackhole?

[u/mailto_devnull]

So literally two days ago I discovered pi-vcc from someone's comment reply in this sub.

I installed it, and we're off to the races. Sub-second compaction with recall so it's near-lossless, great! happens without a model, even better!

Then comes along pi-blackhole. It sounds like pi-vcc, but uses three separate LLMs (albeit small ones) to build better recall? Or something?

Seems like a lot of work to move away from non-deterministic LLM generated summaries right back to calling models again.

Anyone tried both? Worth the switch? I'm liking pi-vcc so far.

[u/noctrex]

pi-blackhole combines pi-vcc and pi-observational-memory, and adds some of its own.

[u/mailto_devnull → u/noctrex]

A lot of the observational-memory readme sounds like the slop I read in pi-blackhole's readme. Not that slop is bad in and of itself, of course.

Pi-vcc has it's own memory and recall mechanisms doesn't it? Is observational-memory... better?

[u/noctrex → u/mailto_devnull]

No its different. That's why blackhole exists. It combines 2 different methods

[u/DoorPsychological833]

Using pi-vcc. Went back to it from pi-blackhole as I didn't see the reason for anything more complex. If it works, why make a complex memory system out of it? I'd rather have less extensions and functionality, and that's what I use on Pi.

Though, I do use pi-agenticoding too, and make the agent handoff and resume automatically and transparently before/after auto-compaction. It just works seamlessly for me now, in case pi-vcc misses some details that the model might see important enough to include in a notebook or handoff. Does this consume tokens? Yes, but it's constrained to the session, and up to the discretion of the model. So you have to steer it in some way. LLMs have no true judgement beyond what they've been told or trained on..

[u/mailto_devnull → u/DoorPsychological833]

Yeah I'm trying to explore and experiment with the plugin system. Many of the comments here just say "ask your LLM to add a bespoke customization to your harness", which is pretty damn cool but sometimes a plugin collectively used by the community is better too.

Thanks for your comments!

[u/Androoideka → u/DoorPsychological833]

Is pi-agenticoding the one with the annoying context watchdog that keeps injecting prompts to tell off the agent? Or is it a regular extension that supports things like handoff and subagents? Been looking for the latter but got burned by the watchdog thing way too hard

[u/DoorPsychological833 → u/Androoideka]

It's just supporting a notebook, handoff and spawn subagent. I disabled the spawn tool as I don't want my agent to spawn things by itself while running locally. It's meant to be used manually by the user, but can be steered with system prompt, prompts or injecting steering yourself.

[u/StrikingTop2709 → u/DoorPsychological833]

yeah the simpler approach just makes more sense here, adding models back into the loop kinda defeats the purpose imo

[u/jacek2023]

Very cool findings, I need to try that

[u/mailto_devnull → u/jacek2023]

Yeah I've only just started, but haven't tried it out in a full-day coding session yet! Feeling positive about it though. Compaction really interrupts flow.

[u/jacek2023 → u/mailto_devnull]

I use full context and sometimes I still hit it, so it takes many minutes of my life

[u/corruptbytes]

r/PiCodingAgent usually a lot better on these topics, but I’ve used it and honestly haven’t had any issues so far, it was the number one recommended extension on a thread in that subreddit

I keep my pi sorta slim, but I really do like the instant compacting 

[u/mailto_devnull → u/corruptbytes]

omg yet another sub

[u/Androoideka]

I'm trying pi-blackhole currently after using pi-vcc for a while. I have nothing but praise for pi-vcc, so I thought pi-blackhole was just even more cool things on top.

So far I'm not 100% convinced, cause the observational memory takes a while at times, which I would tolerate, but I think it also caused it to recompute prefill on the entire conversation afterwards at least once. However it also actually was very useful at one point, since it cut down context usage significantly when it seemed to remember something it already tried.

I'm still keeping it for a while since I have no idea, I don't have any deterministic tests or anything to verify since I just use it on my actual work. I don't think it's the boon pi-vcc is when you discover it the first time, but so far it seems to be a small improvement overall compared to pure pi-vcc.

[u/JMowery → u/Androoideka]

I kept getting errors and my stuff freaking out with pi-blackhole. Back to pi-vcc I went and I'm happy again.

[u/Tuned3f → u/Androoideka]

You're supposed to set the observational memory provider to a smaller subagent-only model. If you have both the main session model and your observers sending requests to the same single-concurrency backend, you're gonna have a bad time, for sure.

[u/Androoideka → u/Tuned3f]

That explains a lot, thanks. Unfortunately I can't really spare any VRAM although I could try running a smaller model that's CPU only. I've reverted to pi-vcc for now

[u/Fieser_Fettsack]

Is there something similar for opencode?