{"data":{"slug":"dataelement-bisheng","name":"bisheng","tagline":"BISHENG is an open LLM devops platform for next generation Enterprise AI applications","github_url":"https://github.com/dataelement/bisheng","owner":"dataelement","repo":"bisheng","owner_avatar_url":"https://avatars.githubusercontent.com/u/103249391?v=4","primary_language":"Python","stars":11879,"forks":1941,"topics":["agent","ai","chatbot","enterprise","finetune","genai","gpt","langchian","llama","llm","llmdevops","llmops","ocr","openai","orchestration","python","rag","react","sft","workflow"],"archived":false,"github_pushed_at":"2026-08-18T11:46:00+00:00","maintenance_label":"Very active","stars_delta_30d":348,"url":"https://www.graphcanon.com/tools/dataelement-bisheng","markdown_url":"https://www.graphcanon.com/tools/dataelement-bisheng.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/dataelement-bisheng","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=dataelement-bisheng","description":"BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.","homepage_url":"http://www.bisheng.ai","license":"Apache-2.0","open_issues":122,"watchers":621,"ai_summary":"Offers comprehensive features such as GenAI workflow, RAG, Agent management, model and dataset management, evaluation, SFT, enterprise-level system management, and observability.","readme_excerpt":"## Quick start \n\nPlease ensure the following conditions are met before installing BISHENG:\n- CPU >= 4 Virtual Cores\n- RAM >= 16 GB\n- Docker 19.03.9+\n- Docker Compose 1.25.1+\n> Recommended hardware condition: 18 virtual cores, 48G. In addition to installing BISHENG, we will also install the following third-party components by default: ES, Milvus, and Onlyoffice.\n\nDownload BISHENG\n```bash\ngit clone https://github.com/dataelement/bisheng.git\n\n---\n\n# Enter the installation directory\ncd bisheng/docker\n\n---\n\n# Unzip and enter the installation directory\nunzip main.zip && cd bisheng-main/docker\n```\nStart BISHENG\n```bash\ndocker compose -f docker-compose.yml -p bisheng up -d\n```\nAfter the startup is complete, access http://IP:3001 in the browser. The login page will appear, proceed with user registration. \n\nBy default, the first registered user will become the system admin. \n\nFor more installation and deployment issues, refer to:：[Self-hosting](https://dataelem.feishu.cn/wiki/BSCcwKd4Yiot3IkOEC8cxGW7nPc)","github_created_at":"2023-08-28T10:00:24+00:00","created_at":"2026-07-07T17:37:06.340241+00:00","updated_at":"2026-08-18T12:00:50.897827+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"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":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"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":"chatbot","name":"chatbot"},{"slug":"enterprise","name":"enterprise"},{"slug":"finetune","name":"finetune"},{"slug":"genai","name":"genai"},{"slug":"gpt","name":"gpt"},{"slug":"langchian","name":"langchian"}],"trust":{"provenance":{"is_fork":false,"github_id":684031003,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-18T12:00:49.943Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":3,"days_since_push":0,"last_release_at":"2026-08-11T09:18:35Z","stars_delta_30d":348,"open_issues_delta_30d":9},"security_summary":{"status":"ok","scanner":"osv@v1","low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:08:48.275Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-18T12:00:50.576Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-08-18T12:00:50.576Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-18T12:00:50.576Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"min_ram_gb":16,"requires_docker":true},"constraints":{"min_ram_gb":16,"requires_docker":true},"when_to_use":["- When you need a unified solution that supports both GenAI workflows and RAG (Retrieval-Augmented Generation) capabilities, which are critical in enhancing the context understanding and response of L"],"when_not_to_use":["- If your project requires minimal resource consumption and does not demand high enterprise-level system management or advanced observability features, BISHENG might be overkill given its hardware and"],"source":"enrich:decision_facts","observed_at":"2026-07-11T15:38:56.107Z"},"constraint_facets":{"min_ram_gb":16,"requires_docker":true},"decision_summary":[{"label":"Requirements","value":"Min 16 GB RAM; Requires Docker"},{"label":"Adopt for","value":"BISHENG is a comprehensive open-source LLM DevOps platform designed specifically for next-generation Enterprise AI applications."}]}}