#vibingonbnb Current overall progress of the "Client Federation Universe" project: approximately 35% • [95%] Core logic analysis (Python): In-depth analysis of core files such as , etc. has been completed. • [80%] Architecture and type design (TypeScript): Core classes (Agent, World) and data interfaces (types.ts) have been designed. • [20%] Core functionality coding (TypeScript): • [70%] Memory module (memory system): This is the current main work and bottleneck. The storage and retrieval of long-term memory (especially the localization implementation of vector similarity search) is more complex than expected. • [40%] Agent module (decision core): percept has been completed, but reflect and plan are highly dependent on the Memory module. • [10%] World module (simulation engine): The framework has been completed, waiting for Agent logic to be ready. • [0%] UI module (frontend interface): Not started yet. Current challenges: The biggest challenge is to efficiently and accurately reproduce the complex vector retrieval memory function based on LlamaIndex from the original Python code using TypeScript and browser technologies (such as IndexedDB). This is key to whether the Agent can "remember" and "associate."