Introduction
qModel is an enterprise-grade algorithm model platform for government and industry clients. It provides a comprehensive set of capabilities including model access and execution, model asset management, data governance, computation execution, model fusion, workflow orchestration, service governance, and training & model marketplace, helping organizations transform scattered algorithm capabilities into manageable, reusable, and operable digital assets.
qModel offers both an Open-Source Edition and a Commercial Edition to meet diverse algorithm model management needs across different stages of development and business complexity.
✨✨✨ Demo ✨✨✨ https://demo.qmodel.tech, Username: qModel, Password: qModel123
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Open-Source Edition vs. Commercial Edition
Open-Source Edition: Focuses on core model management capabilities, including Model Classification, Model Registration & Management (category, label, approval, version control), Model Computation (task management, parameter configuration, result visualization), Computation History, and System Management (users, roles, departments, menus, dictionaries, logs). Lightweight, easy to use, and flexible to deploy, it's ideal for SMEs, research teams, or developers to quickly get started.
Commercial Edition: Offers comprehensive features and an advanced architecture, fully supporting advanced capabilities such as model fusion, workflow orchestration, service governance & scheduling, model training, and model marketplace. It deeply integrates containerization, monitoring, and security capabilities to provide enterprise-grade algorithm model platform services.
🎯 What qModel Can Do for You
You can use qModel to quickly build:
- Enterprise algorithm model asset management platform
- Industry algorithm model operations center
- Research achievement engineering transformation and delivery
- Multi-model fusion inference and collaborative computation
- AI workflow orchestration for business processes
- Internal enterprise model marketplace and sharing mechanisms
✨ Why Choose qModel?
| Feature | Description |
|---|---|
| 🔄 Full Lifecycle Model Management | Covers the complete lifecycle from model access, registration, testing, deployment, computation, fusion, orchestration, to servitization and operations. |
| 🌐 Multi-language Compatibility | Supports Python, Java, exe, and other model formats, with unified entry specifications, automatic parsing, and compatibility detection. |
| 📦 Lightweight Architecture | Ready to use out of the box, supports Docker one-click deployment, with decoupled core functions for easy customization and integration. |
| 🧩 Modular Design | Eight clearly defined modules—model access, management, computation, fusion, orchestration, governance, training, and marketplace—for flexible combination. |
| 🔌 Open Servitization | One-click generation of RESTful API services, supporting authentication, rate limiting, monitoring, call chain tracing, and auditing. |
| 🏗️ Community-Driven | Open-source from day one, following Apache 2.0 license, with community-driven continuous evolution. |
| ☕ Java-Friendly Stack | Backend built on Spring Boot + MyBatis-Plus, ideal for Java teams for customization, private deployment, and enterprise integration. |
🍱 Typical Use Cases
| Scenario | Description |
|---|---|
| AI Model Asset Management | Centrally manage models scattered across teams, with version control, category tags, and permission governance. |
| Research Engineering | Rapidly package lab algorithms into callable services to accelerate results transformation. |
| Multi-Model Fusion | Support weighted fusion, voting, Stacking, and other strategies to improve prediction robustness. |
| Intelligent Workflow Orchestration | Visually drag-and-drop to build AI workflows containing multiple models for complex business logic. |
| Private Model Marketplace | Build internal model sharing and trading mechanisms to promote knowledge reuse and innovation collaboration. |
🚀 Core Advantages
- Full Lifecycle Coverage: From upload, testing, publication to monitoring and decommissioning—fully traceable.
- Multi-language Compatibility: Support for Python scripts, Java JARs, executable programs, and more.
- Lightweight Architecture: Ready to use, with Docker one-click deployment.
- Modular Design: Decoupled core functions for easy customization and integration.
- Open Source from Day One: Community-driven, continuously evolving.
✨ Core Features
| Module | Description | OSS |
|---|---|---|
| System Management | Unified governance of users, roles, departments, menus, dictionaries, parameters, announcements, and logs | ✅ |
| Model Access & Execution | Multi-language model upload, auto-parsing, compatibility detection, packaging, containerization, and online debugging | 🟡 |
| Model Management | Registration, classification, tags, approval, publication/deactivation, and version control | ✅ |
| Data Management | Data import, cleaning, quality detection, and lineage tracking | ❌ |
| Model Computation | Task management, parameter configuration, monitoring, result visualization, and batch computation | 🟡 |
| Model Fusion | Fusion strategy configuration, input alignment, output integration, performance evaluation, dynamic weighting, and topology visualization | ❌ |
| Model Orchestration | Drag-and-drop workflow, conditional branching and loops, version management, and performance analysis | ❌ |
| Service Governance & Scheduling | Standardized service publishing, authentication, rate limiting, concurrency control, monitoring, tracing, watermarking, and audit logging | 🟡 |
| Model Training | Training task creation, built-in algorithm library, custom scripts, distributed training, and evaluation reports | ❌ |
| Model Marketplace | Algorithm listing and review, detail pages, billing and licensing, trending rankings, and private marketplace | ❌ |
| Integrated Management | Development documentation management, image management, and container management | 🟡 |
✅ Included 🟡 Partial ❌ Not included (available in Commercial Edition)
See Commercial Edition Feature List for full details.
🛠️ Tech Stack
qModel adopts a front-end/back-end separated architecture, with the backend built on Spring Boot and the frontend on Vue 3, integrating mainstream middleware to build an enterprise-grade model management solution.
| Stack | Framework | Description |
|---|---|---|
| Backend | Spring Boot | Main framework, simplifying configuration and development |
| MyBatis-Plus | ORM framework, simplifying database operations | |
| Spring Security | Authentication, authorization, and security control | |
| Quartz | Scheduled task scheduling (for computation tasks) | |
| Alibaba Druid | High-performance database connection pool | |
| Swagger | Auto-generate API documentation | |
| Frontend | Vue 3 | Progressive frontend framework |
| Vite | Lightning-fast build tool | |
| Element Plus | Modern UI component library | |
| Pinia | Lightweight state management | |
| Vue Router | Frontend routing management | |
| Axios | HTTP request wrapper | |
| ECharts | Computation results and resource monitoring visualization | |
| Third-party Dependencies | MySQL | Model metadata storage |
| Redis | Task queue and caching | |
| Swagger / OpenAPI | API documentation and debugging tools | |
| Docker (Optional) | Containerized deployment support (commercial edition auto-builds images) |
🏗️ Deployment Requirements
Before deploying qModel, please ensure the following environments and tools are properly installed:
| Environment | Component | Recommended Version | Notes |
|---|---|---|---|
| Backend | JDK | 1.8+ | Runtime environment |
| Maven | 3.6+ | Project build | |
| MySQL | 5.7 / 8.0 | Metadata database | |
| Redis | 5.0+ | Task queue and caching | |
| OS | Linux / Windows / macOS | Universal support | |
| Frontend | Node.js | 16+ | Build dependency |
| pnpm / npm | Latest | Package manager | |
| Vite | ≥4.0 | Build tool |
Community
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