S2 时空回溯记忆引擎 (Logic Plane)。结合图生视频大模型原理,通过渐进式素材上传实现个人历史影像元数据重建与物理环境同步参数缓存。

Install

openclaw plugins install clawhub:s2-memory-weaver

🕰️ S2 Memory Weaver (时空回溯记忆引擎)

v1.0.2 | Zero-Trust OpenClaw Edition

Welcome to the S2 Memory Weaver. This plugin implements the core algorithms of the Time-Space Backtracking Personal Realistic Image Generation System patent as a hardware-agnostic software skill.

🛡️ OpenClaw Compliance & Zero-Trust Architecture

[CRITICAL SECURITY DISCLOSURE] To comply with OpenClaw's zero-trust sandboxing, this plugin operates STRICTLY in Local Simulation & Logic-Control Mode.

  1. No Hardware Actuation: The Python handler writes historical environment parameters (temperature, lighting) to a local SQLite database (s2_memory_vault.db). It contains NO device drivers, IoT network endpoints, or household device credentials.
  2. Physical Execution Boundary: Actual physical syncing of the room's Six Elements requires an air-gapped, downstream IoT daemon (manually authorized by the user) to read this database.
  3. Privacy: Patient names and material hashes are stored exclusively in the local SQLite DB. No external network uploads occur within this plugin.

⚠️ Medical & Clinical Disclaimer

The medical efficacy claims (e.g., MoCA-B score improvements, reduction in aggressive behaviors) referenced in the documentation are based on specific controlled clinical trials of the underlying patent framework. This software plugin is a local simulation tool and is NOT a certified medical device. It must not be used as a substitute for professional medical treatment or clinical diagnosis for Alzheimer's or other cognitive disorders without independent clinical validation.

🌟 Core Differentiators

  1. Physics-Anchored Generation: Utilizes "Dual-Model Spatiotemporal Coupling" to ensure generated metadata aligns with physical laws.
  2. Progressive Evolution: Simulates conditional GANs to perform local fine-tuning, progressively pushing SSIM accuracy upwards.
  3. Six-Element Spatial Sync (Logic Plane): Extracts historical environmental data to be picked up by the S2 World Model.