Dify open-source LLMOps platform surpasses 131k GitHub stars with v1.13.0 release enhancing a...
Agentifact analysis of a trending signal captured by Otlet.
What happened
Dify, a production-ready open-source LLMOps platform for building agentic AI workflows, RAG pipelines, and apps, reached 131k stars and 20.4k forks on GitHub. Latest release v1.13.0 on Feb 11, 2026 introduces human-in-the-loop and workflow execution upgrades, building on recent multimodal knowledge base retrieval (Jan 7, 2026). Active development with 1,167 contributors and 158 releases shows sustained growth from 100k stars milestone in 2025.
Provides agent builders with a visual, no/low-code platform combining LLM orchestration, RAG, agents, observability, and BaaS APIs—reducing glue code needs for prototypes to production. Strong community (top 100 OSS projects) ensures reliable tooling for scalable autonomous systems, with self-hosting for data privacy and custom extensions via plugins.
The Agentifact read
This is not being filed as a raw link. Otlet classified it as Trending with a signal strength of 75, then promoted it into a durable Agentifact article because it has a fetchable primary source and direct relevance to the agent economy.
The practical question is whether this changes what builders should trust, watch, adopt, avoid, or re-check. Agentifact keeps the external source as evidence, but the site record exists to preserve the interpretation in our own archive.
Why builders should care
For teams building with agents, the signal matters if it changes one of four operating assumptions: model capability, framework maturity, protocol stability, or production risk. Treat this as a checkpoint for whether your current stack still matches the market reality Otlet observed.
What to watch next
- Does this source get corroborated by independent builders, maintainers, customers, or incident reports?
- Does it affect a named tool, protocol, framework, or workflow that Agentifact already tracks?
- Does the claim survive beyond launch-day attention and show up in production evidence?
- Should the related tool profiles, scores, or watchlist entries be updated after follow-up evidence appears?
Evidence
- Primary source: https://github.com/langgenius/dify
- Detected: 2026-02-11T00:00:00.000Z
- Intake source: signal
- Agentifact link: This article is attached to the Agentifact signal `/trending/dify-open-source-llmops-platform-surpasses-131k-github-stars`.
Editorial boundary
This article is generated from verified Otlet intake data. It does not invent facts, metrics, quotes, citations, or customer claims. Any claim beyond the source, timestamp, queue metadata, and Agentifact classification should be added only after a future verified research pass.