dataelement/bisheng
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. observed · 2026-08-28
Health v2 · maintenance only
94/100
- Activity 99
- Release rhythm 97
- Longevity 78
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: 11.0
- age_days: 1101
- days_rel: 22
- days_push: 7
- n_releases_24m: 31
Adoption not part of the score
11911 stars · 1950 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
BISHENG is an open-source LLM DevOps (LLMOps) platform for building enterprise AI applications, offering GenAI workflow orchestration, RAG, agents, unified model management, evaluation, SFT/fine-tuning, dataset management, and observability. It is a self-hosted Python/React platform used by large enterprises, including Fortune 500 companies.
Use cases
- build enterprise LLM applications with a visual workflow
- create RAG pipelines over company documents
- orchestrate AI agents with human-in-the-loop review
- manage and evaluate multiple LLM models centrally
- fine-tune models with SFT and manage datasets
- deploy a self-hosted chatbot platform for my company
- add observability to LLM app deployments
- extract data from documents with OCR in AI workflows
When to choose
- you need an enterprise-grade, self-hosted LLMOps platform combining workflows, RAG, agents, and evaluation
- you want human-in-the-loop intervention inside AI workflows
- you need unified model management plus fine-tuning (SFT) and dataset tooling in one platform
- your organization requires enterprise-level system management and observability for GenAI apps
When to avoid
- you only need a lightweight library or SDK to call LLMs from code
- you want a fully managed cloud service with no self-hosting overhead
- you need a minimal single-purpose RAG or chatbot tool rather than a full platform
- your team cannot operate a multi-component Python/Docker deployment
Facets
application · maturity active
agent-framework rag llm-inference workflow-automation chatbot ocr machine-learning data-science monitoring etl large-language-models chatbots developer-tools self-hosted erp python self-hosted cross-platform llmops llm-devops genai workflow-orchestration fine-tuning sft evaluation enterprise-ai model-management observability human-in-the-loop ai-agents retrieval-augmented-generation natural-language-processing automation docker web-server
1 source
- readme: https://github.com/dataelement/bisheng · fetched 2026-08-28 · 819fe7198dfd
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| dataelement/bisheng | main | 94 |
For agents
markdown · JSON · MCP: product_card(name="dataelement/bisheng")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem