This is an interesting project and in some ways similar to an idea I had. My idea was actually just to aggregate primary texts (whatever public domain versions are available) for a wide range of philosophical and spiritual work and provide an easy way to include it as context in straight-forward LLM calls.
I've skimmed this announcement, your github repo and your site and it isn't clear to me, are these custom models? Are they fine-tuned from some base model? e.g. do you have 30 separate models?
We have no custom models and no fine tuning. It is the base model, Qwen3 235B for the free tier and we recommend Qwen3.6 27B for the local mode. So the figures are data, not weights. We have instruction files for every figure and additional voice profiles for the councils. The work was put into the iterations to improve the instructions. It is possible to fetch them from the CDN, for example: https://media.agoracosmica.org/instructions/jung/free_conver...
I like your primary texts idea. For our case we tried to keep the instructions lean to have them around 4k tokens, so that it also works in local mode for users with limited context.
Totally understand on managing context length. But in a sense, the work is just providing the library of primary texts (and given the public domain nature of these kinds of works, that seems both ethical and legal) and some mechanism to include them into the context as desired by the user.
As an example user story, maybe I want to get Plato's reaction to Buddha. It might be convenient to have a library of sutra's that I could grab extracts from in order to send to the instructed model for further reflection. That puts the context management into the users hands. From a UI perspective you would need a library interface, the ability to select extracts, some indication of context available vs. context used, etc.