🦞 Industrial-grade Soft Execution Engine for OpenClaw. Features Multi-Expert Routing (DeepSeek-R1/V3), DAG Scheduling, API Key Pooling, and Docker Sandbox isolation.
# 🦞 OpenClaw Soft Engine (Expert Matrix v2.0) 🌐 Language - English (current) - [简体中文](./README.zh-CN.md) [](https://www.docker.com) [](https://www.microsoft.com/windows/windows-11) [](workspace/AGENTS.md) [](LICENSE) [](https://github.com/Syysean/openclaw-soft-engine/releases) [](https://github.com/Syysean/openclaw-soft-engine/commits/main) > **Note:** This project is a deployment template and enhancement layer for OpenClaw. It is not the official OpenClaw distribution. OpenClaw Soft Engine is a production-oriented execution layer that upgrades OpenClaw with structured routing, multi-expert model orchestration, and hardened guardrails. It combines a DAG-based task protocol with multi-expert model routing to improve execution control, route-level isolation, and concurrent task handling. This guide documents the evolution from v1.0 "Six-Model Matrix" to v2.0 "Soft Execution Engine." ## Why Soft Engine? A comparison between a vanilla OpenClaw setup and the Soft Engine execution layer. | Capability | Vanilla OpenClaw | Soft Engine v2.0 | | :--- | :---: | :---: | | **Execution Model** | Linear prompt flow | DAG-based execution (`PLAN` / `CHECKPOINT`) | | **Model Routing** | Single-model or manual switching | Automatic multi-expert routing (Text / Vision / Reasoning / Code) | | **Rate Limit Handling** | Shared API key (prone to 429 under concurrency) | Route-level API key isolation | | **Memory Safety** | No built-in safeguards | Container memory limit (512
HAL 分层混合模型工作流 — 强模型(Claude)负责理解/拆解/验收,低成本模型(DeepSeek)负责检索/提取/清洗。Hermes Agent skill。
An LLM agent fine-tuned on DeepSeek for spaced repetition, dynamically integrating knowledge points based on the Ebbinghaus forgetting curve.
基于 STM32F103 构建的端到端 AI 智能手表生态。自研“零重定位”原生机器码动态加载引擎与页面栈式 UI 框架;集成生产级 OTA 回滚保护机制与高带宽(921600 baud)串口协议栈。通过 Node.js 中继实现 DeepSeek AI 语义控制及 ASRPRO 语音全双工交互,是一个集成了分布式计算、现代存储管理与 AI Agent 的嵌入式全栈工程。
A Meta-Agent-Driven Self-Evolving Multi-Agent System for UAV Detection and Tracking
One command to run Hermes AI Agent with a browser UI. Zero prerequisites. 一行命令,AI 就位。
网页应用Agent,接入DeepSeek、Mimo等模型