Late-night-regrets – piclaw-addons (rcarmo.github.io)

A new add-on for PiClaw, named "late-night-regrets," introduces a Bayesian interaction-quality classifier designed to analyze chat histories without consuming model tokens for its classification process. This classifier leverages a Multinomial Naive Bayes model trained on weak-label signals from prior interactions to identify behavioral patterns in user communications, highlighting areas such as corrections, misinterpretations, and context failures. It then generates self-improvement reflections based on these interactions, facilitating reflection on performance. This development is significant for the AI/ML community as it emphasizes the use of efficient, token-less classification methods, allowing systems to provide feedback on their performance without incurring high computational costs. The classifier's ability to label categories ranging from successful executions to context failures can enhance training datasets and adapt agent behaviors more effectively. With configurable settings, users can customize parameters such as confidence thresholds and output directories, ensuring tailored performance monitoring that aligns with individual use cases in AI-driven interactions.