Enterprise-grade AI agent framework with multi-provider LLM management, secure knowledge bases and high-precision RAG, visual workflow orchestration, and multi-agent coordination.
Star History
Momentum
+143
STARS · LAST 30 DAYS
5
PER DAY
#69
MOST-STARRED Java
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +35 | +143 | +450 |
| Per day | 5 | 5 | 5 |
| Forks gained | +7 | +28 | +70 |
ruoyi-ai gained 143 stars in the last 30 days, about 5 a day, and now has 5.7K. It is about 3 years old and has averaged roughly 1.9K stars a year. It ranks #69 among Java repositories and #1,001 across all languages on GitHubRepo.
Trending Record
5
DAYS ON TRENDING
#701
BEST RANK
Sep 24, 2026
FIRST APPEARANCE
Active
STATUS TODAY
ruoyi-ai has maintained a continuous presence across global trending indexes, peaking at #701. Below is the 30-day activity profile:
💡 Overview
ruoyi-ai is an open-source project written in Java: Enterprise-grade AI agent framework with multi-provider LLM management, secure knowledge bases and high-precision RAG, visual workflow orchestration, and multi-agent coordination.
Engineered for speed, consistency, and developer ease, it solves common hurdles in agent, ai, knowledge. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Java for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ git clone https://github.com/ageerle/ruoyi-ai.git
cd ruoyi-ai⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
JDK 17 or higher (OpenJDK / GraalVM)
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
ruoyi-ai coordinates its core functionality through a modular Java pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with ruoyi-ai.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install ruoyi-ai using your package manager: `git clone https://github.com/ageerle/ruoyi-ai.git`
Initialize your project workspace or configuration file for ruoyi-ai.
Import ruoyi-ai into your codebase or invoke it directly from your terminal.
Execute your test suite or run `ruoyi-ai --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Java, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
ageerle/ruoyi-ai is currently ranked #1,001 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
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|---|---|---|---|---|
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| #1,000 | MarkEdit-app/MarkEdit | Swift | ★ 5.7K | Compare ↗ |
| #1,001 | ageerle/ruoyi-ai This Project | Java | ★ 5.7K | |
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Frequently Asked Questions
What does ruoyi-ai do? +
Enterprise-grade AI agent framework with multi-provider LLM management, secure knowledge bases and high-precision RAG, visual workflow orchestration, and multi-agent coordination.
What language is ruoyi-ai written in? +
The primary language is Java. Topics include: agent, ai, knowledge, mcp, rag.
Is ruoyi-ai actively maintained? +
Yes, the last recorded push was on Sep 23, 2026 with 5 open issues being tracked.
How many stars does ruoyi-ai have? +
ruoyi-ai has 5,726 stars and 1,409 forks on GitHub.
How does ruoyi-ai rank among GitHub repositories? +
With 5,726 stars, ageerle/ruoyi-ai is ranked #1,001 globally across all repositories tracked on GitHubRepo and #69 among Java projects.
What license is ruoyi-ai distributed under? +
The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.
