waterbuffaloai

Yes, this is the exact engineering challenge I have been trying to solve. Currently, the improvements only include memories and skills update, for v1.5, this is what I am trying to solve too. Could you try the current version and let me know what you think?

users have option to type /wrong, then the local model will ask cloud model for the answer and learn from it. Could you try the current version and let me know your feedbacks?

I am also building a similar memory structure and decay mechanism for my local agent project, where I also use Ebbinghaus. One of the challenge I face is how to decide effectively what to save in the memory: Is it the model to decide what is important, summarize and save it to the memory? How to avoid redundancy and categorize the memory correctly so you could get the right hit and decide what to forget. I would love to learn more about your approach and what your thoughts on those points