Comment on: How Compaction Works in Pi
Can someone recommend a Hermes alternative that is less token hungry? Pi did not work well for my use case.
Developers struggle with expensive, token‑hungry models and the lack of built‑in image processing, often spending time manually pruning and summarizing sessions to stay within context limits. TokenTrim automatically routes queries to the most cost‑effective model, adds on‑demand image handling, and continuously compacts context in real time, eliminating manual overhead and slashing token costs.
Can someone recommend a Hermes alternative that is less token hungry? Pi did not work well for my use case.
But what if the model you're using doesn't have image processing capabilities?
In my experience, the best approach to compaction is to never get to the point where you need compaction and to generally stay below about 30% context window utilization. Even for long agentic workflows this can be accomplished for quite a while, much longer than most people might think.Here's what I do for each of my sessions:1. For asides, off-topic work, or repetitive work that has already been done in the session, branch backwards (with /tree) and summarize.2. If I've exceeded 30% or the 'price-doubling' multi-tier pricing, prune (my custom extension).3. If I've already pruned and I'm stil
I want to like Pi but compaction is why I had to go back to Open Code…My problem is that when in a loop and it’s calling tools, it won’t check how close it is to the compacting limit until the whole loop returns to you for the next prompt. And so if you have a run that could go for hours, it’s a gamble if you’ll OOM or an interrupting compaction breaks context and stops the loop without continuing.There’s a few extensions that all try to solve this problem, but I’ve found none actually work :(
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