Preamble¶
The core philosophy of DeepSeek Harness (DSH) is “everything is a plugin.” When building an enterprise-grade AI resource management system, unified management is required for IAM, MCP services, model gateways, and usage metering. This plugin is maintained by 01men and aims to provide a “Rongqi Custom Track (Gate 01)” — a DSH-based collaboration frontend for AI agents and humans. It integrates the cordis plugin form into DSH with one click, serving as a unified entry point for management console and business data interactions.
Plugin Positioning¶
- Name: Rongqi Custom Track (Gate 01)
- Type: Workflow / Enterprise Resource Management Platform
- License: MIT
- Core Value: Unifies business domains in the DSH ecosystem (IAM, model gateways, skills marketplace, etc.) into a single collaboration frontend, enabling coordinated operations between agents and humans.
Core Features¶
This plugin builds a complete Industry AI Workbench (IAW), including the following capabilities:
- Industry AI Workbench (IAW): Provides a five-space information architecture and industry graph packages.
- Unified Authentication and IAM: Supports organizational accounts and unified authentication.
- DingTalk Device Flow Login: Supports DingTalk device flow login as a connector.
- MCP Deployment Service: Provides deployment, monitoring, and governance for MCP services.
- Skills and Plugins Marketplace: Provides management and integration for the Skill/plugin marketplace.
- Model Access Gateway: Unified access to large language models with transparent usage metering.
- Business Data Layer: Provides business data support based on scene graphs.
- Collaboration Frontend Components: Includes
plugin-panel-core(panel),plugin-rq-card(execution card), andplugin-dingtalk-bridge(DingTalk bridge).
Installation and Enablement¶
Use the following command to add the plugin to DSH with one click:
dsh plugin add github:01men/RQ-DSH / npm @ybkk/gate-01
After installation, start the service to access the console.
Typical Usage¶
After starting the platform, the default URL is http://127.0.0.1:7300.
- Basic Startup:
npm start
On first startup, baseline initialization is performed and a platform administrator account is generated.
- Demo Mode:
If you need to quickly evaluate or demonstrate the platform, start it with seed data:
DEMO_SEED=1 npm start
In demo mode, complete demo data and accounts are automatically generated, and the unified password is `Ybk@2026`.
-
Management Console:
Openhttp://127.0.0.1:7300in a browser to enter the management console. -
Feature Self-Test:
npm run selftest
Architecture and Collaboration Rules¶
- Plugin Form: The plugin runs in cordis form. After connecting to the host, all data is accessed through a local proxy (zero browser CORS).
- Collaboration Iron Rule: Plugins are prohibited from directly accessing each other’s data. State changes must trigger events through the event bus. For example, the
iam.user.frozenevent causesauthnto revoke tokens.
Notes¶
- M0 Compliance Convergence: The platform has deprecated usage-based billing, resale, and revenue-sharing features. The business model has been adjusted to team-based plus domain asset pricing.
- Wallet Subsystem: The wallet/revenue-sharing subsystem has been taken offline and archived.
- Environment Variables: The organizational account password is taken from the
ADMIN_PASSWORDenvironment variable. If not set, a random password is generated and written to the logs. - Offline Support: Single-file and self-contained, with zero external CSS/JS/font dependencies, and supports offline use in intranet or private deployment environments.
- Intranet Deployment: To increase GitHub token limits or use private mirrors in intranet environments, configure them via environment variables.
Summary¶
01men/rq-dsh is a complete enterprise-grade AI resource management solution built on DSH. Through its plugin architecture, it integrates core capabilities such as identity authentication, model access, and skills marketplace into a unified collaboration frontend, making it suitable for teams that need to build internal AI governance systems or deploy private AI platforms.