{"data":{"slug":"ageerle-ruoyi-ai","name":"ruoyi-ai","tagline":"一站式AI应用开发框架","github_url":"https://github.com/ageerle/ruoyi-ai","owner":"ageerle","repo":"ruoyi-ai","owner_avatar_url":"https://avatars.githubusercontent.com/u/32251822?v=4","primary_language":"Java","stars":5683,"forks":1403,"topics":["agent","ai","knowledge","mcp","rag"],"archived":false,"github_pushed_at":"2026-09-05T14:27:32+00:00","maintenance_label":"Very active","stars_delta_30d":73,"url":"https://www.graphcanon.com/tools/ageerle-ruoyi-ai","markdown_url":"https://www.graphcanon.com/tools/ageerle-ruoyi-ai.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/ageerle-ruoyi-ai","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=ageerle-ruoyi-ai","description":"An enterprise AI development framework for building AI agents. It provides unified management of multi-provider LLMs, secure enterprise knowledge bases with high-precision retrieval, visual workflow orchestration and multi-agent coordination. Compatible with mainstream Agent Skill standards, it enables developers to efficiently build production-gra","homepage_url":"https://doc.ruoyiai.chat","license":"MIT","open_issues":4,"watchers":43,"ai_summary":"企业级全栈AI平台，支持多智能体协同与RAG技术，提供模型和知识管理、流程编排等功能.","readme_excerpt":"## 🐳 Docker Deployment\n\nThis project provides two Docker deployment methods:\n\n---\n\n# Pin the image version. Public GHCR images do not require docker login.\ncp docs/docker/ruoyi-ai/.env.example docs/docker/ruoyi-ai/.env\nsed -i 's/^RUIYI_VERSION=.*/RUIYI_VERSION=v3.1.0/' docs/docker/ruoyi-ai/.env\n\n---\n\n### Method 2: Step-by-step Deployment (Source Build)\n\nIf you need to build backend services from source, follow these steps:\n\n#### Step 1: Deploy Backend Service\n\n```bash\n\n---\n\n## 📄 License\n\nThis project is licensed under the **MIT License**. See the [LICENSE](LICENSE) file for details.","github_created_at":"2024-01-16T04:16:41+00:00","created_at":"2026-07-15T10:38:50.950719+00:00","updated_at":"2026-09-20T04:24:42.191914+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"developer-tools","name":"Developer Tools","url":"https://www.graphcanon.com/categories/developer-tools","markdown_url":"https://www.graphcanon.com/categories/developer-tools.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/developer-tools"},{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"},{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"agent","name":"agent"},{"slug":"ai","name":"ai"},{"slug":"knowledge","name":"knowledge"},{"slug":"mcp","name":"mcp"},{"slug":"rag","name":"rag"}],"trust":{"provenance":{"is_fork":false,"github_id":743825398,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-08T06:01:23.338Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":1,"days_since_push":2,"last_release_at":"2026-08-04T07:24:20Z","stars_delta_30d":73,"open_issues_delta_30d":3},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-26T04:00:29.166Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-08T06:01:23.787Z"},"languages":{"value":["java"],"source":"github.language","observed_at":"2026-09-08T06:01:23.787Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-09-08T06:01:23.787Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When you need to integrate multiple vendor models into a single platform","For building custom knowledge bases with high precision search capabilities","If your project requires visualization of workflow design and orchestration"],"when_not_to_use":["Avoid if only simple AI functionalities are needed without complex model integration or management","Not recommended for teams preferring non-Java ecosystems as the platform is Java-centric","If immediate deployment and setup speed are critical, due to its enterprise-grade extensive features"],"source":"enrich:decision_facts","observed_at":"2026-07-16T18:40:44.358Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Ruoyi-ai is an enterprise-focused all-in-one AI app development framework with support for model management, multi-agent collaboration, and RAG technology."}]}}