# qModel **Repository Path**: qiantongtech/qModel ## Basic Information - **Project Name**: qModel - **Description**: qModel 是一个以 模型全生命周期管理 为核心的开源模型平台,提供行业算法模型接入、注册、测试、部署、计算、融合、编排与服务化等能力,帮助企业与科研机构将算法资产转化为可运维、可复用、可治理的智能服务。平台支持 Python、Java、exe 等多语言模型格式,打通从实验到生产的工程链路,为传统算法的协同应用提供坚实底座。 - **Primary Language**: Java - **License**: Apache-2.0 - **Default Branch**: develop - **Homepage**: https://qmodel.tech/ - **GVP Project**: No ## Statistics - **Stars**: 15 - **Forks**: 8 - **Created**: 2025-12-31 - **Last Updated**: 2026-01-30 ## Categories & Tags **Categories**: Uncategorized **Tags**: 模型平台, 行业算法, 模型融合, 千模平台 ## README [banner.png](.gitee/banner.png)

JDK Spring Boot Vue License qModel Gitee Stars GitHub Stars

📖简体中文 | 📖English

## 🌈 Introduction **qModel** is an open-source model management platform centered around **full lifecycle management of AI models**. It provides capabilities including model ingestion, registration, testing, deployment, computation, fusion, orchestration, and service exposure—helping enterprises and research institutions transform algorithmic assets into intelligent services that are operable, reusable, and governable. The platform supports multiple model formats such as Python scripts, Java JARs, and executable binaries (`exe`), bridging the engineering gap from experimentation to production, and serving as a robust foundation for collaborative applications involving traditional algorithms. ✨✨✨**Live Demo**✨✨✨ demo.qmodel.tech (Username: `qModel`, Password: `qModel123`) > **qModel — Empowering models throughout their full lifecycle, driving continuous value through intelligence.** ## 🍱 Typical Use Cases | Scenario | Description | |----------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------| | **AI Model Asset Management** | Centralized governance of scattered models across teams, with version control, categorization, tagging, and permission management | | **Engineering Lab-to-Production Transition** | Rapidly package research algorithms into callable services to accelerate technology transfer | | **Multi-Model Fusion Inference** | Supports strategies like weighted averaging, voting, and stacking to enhance prediction robustness | | **Intelligent Workflow Orchestration** | Visually drag-and-drop to build AI workflows combining multiple models for complex business logic | | **Private Model Marketplace** | Establish internal model sharing and trading mechanisms to promote knowledge reuse and innovation | ## 🚀 Key Advantages - **Full lifecycle coverage**: From upload, testing, and release to monitoring and retirement—fully traceable - **Multi-language support**: Compatible with Python, Java, executables, and more - **Lightweight architecture**: Ready-to-run out of the box; supports one-click Docker deployment - **Modular design**: Core features are decoupled for easy integration and secondary development - **Open from day one**: Community-driven and continuously evolving ## ✨ Core Features | Module | Description | Open Source Status | |-------------------------------------|---------------------------------------------------------------------------------------------------------------------------|--------------------| | **System Management** | Unified governance of users, roles, departments, menus, dictionaries, parameters, announcements, and logs | ✅ Implemented | | **Model Categories** | Create and manage hierarchical model categories and tag groups | ✅ Implemented | | **Model Management** | Register, categorize, tag, approve, publish/retire, and version-control models | ✅ Implemented | | **Model Computation** | Manage tasks, configure parameters, visualize results, and download outputs (input data binding required manually in OSS) | ✅ Implemented | | **Computation History** | View historical tasks; filter by model, time, status; and revisit results | ✅ Implemented | | **Model Ingestion & Execution** | Upload multi-language models, auto-parse metadata, and perform compatibility checks | ❌ Planned | | **Model Packaging** | Standardized packaging guidelines and documentation | ❌ Planned | | **Service Governance & Scheduling** | Auto-generate RESTful APIs with authentication, rate limiting, concurrency control, call tracing, and watermarking | ❌ Planned | | **Documentation Center** | Integrated developer documentation management | ❌ Planned | > 💡 Note: Advanced features such as automated containerization, online debugging, model fusion, workflow orchestration, and training loop integration will be available in the commercial edition. Community contributions to extend the open-source version are warmly welcomed! ## 🛠️ Tech Stack qModel adopts a frontend-backend separated architecture: Spring Boot on the backend and Vue 3 on the frontend, integrated with mainstream middleware for enterprise-grade model management.
Tech LayerFrameworkDescription
BackendSpring BootMain application framework
MyBatis-PlusORM for simplified database operations
Spring SecurityAuthentication and authorization
QuartzScheduled task execution (e.g., batch computations)
Alibaba DruidHigh-performance database connection pool
SwaggerAuto-generated API documentation
FrontendVue 3Reactive UI framework
ViteUltra-fast build tool
Element PlusModern UI component library
PiniaLightweight state management
Vue RouterClient-side routing
AxiosHTTP client for API calls
EChartsVisualization of computation results and system metrics
Third-party DependenciesMySQLMetadata storage
RedisTask queue and caching
Docker (optional)Containerized deployment (auto-image building in commercial edition)
Local StorageStore model files and computation outputs
## 🏗️ Deployment Requirements Ensure the following environment is ready before deploying qModel:
EnvironmentComponentRecommended VersionNote
BackendJDK1.8+Runtime environment
Maven3.6+Project build tool
MySQL5.7 / 8.0Metadata database
Redis5.0+For task queues and caching
OSLinux / Windows / macOSFully supported
FrontendNode.js16+Build dependency
pnpm / npmLatestPackage manager
Vite≥4.0Build tool
## 🚨 Commercial Licensing qModel offers both **open-source** and **commercial** editions: - The **open-source edition** is ideal for learning, evaluation, and lightweight production use, licensed under Apache 2.0 (commercial use allowed with logo retention). - The **commercial edition** targets enterprise and government clients, offering advanced capabilities such as **automated containerization, model fusion, visual workflow orchestration, training-in-loop, and private model marketplace**, along with dedicated technical support and private repository access. 👉 For **custom branding licensing** or **commercial trial requests**, please join our official QQ group for consultation. ## 🚀 Quick Start 👉 View Quick Deployment Guide ## 👥 Community Support Join the official qModel QQ group to stay updated, ask questions, and share experiences! 👉 Join the QQ Group ## 🖼️ Screenshots
Login Page Dashboard
Model List Model Detail
Compute Tasks Task History
Login Page Dashboard
Model Category Model Input
Model List Compute Tasks