by langfuse · Agent Tool · ★ 215
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Langfuse Docs Repo for langfuse.com. Built with Fumadocs and Next.js App Router. Local Development Pre-requisites: Node.js 22, pnpm v9.5.0 To use Node 22 (e.g. with nvm): then (or ). The repo includes an so picks 22 automatically. Optional: Create env based on .env.template Run to install the dependencies. Run to start the development server on localhost:3333 Formatting This repo uses Prettier for formatting supported source and content files, including Markdown and MDX. Run to format files. Run to check formatting in CI mode. Markdown prose wrapping is preserved and embedded-language formatting is disabled in so formatting does not change linebreak-sensitive Markdown rendering or fenced code snippet contents. Python cookbooks All Jupyter notebooks are in the directory. For JS/TS notebooks we use Deno, see Readme in cookbook folder for more details. To render them within the documentation site, we convert them to markdown using , move them to the right path in the directory where they a
| Stars | 215 |
| Forks | 250 |
| Language | MDX |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 59.0445949875859/100 |
| Open Issues | 142 |
| Last Updated | 2026-07-02 |
| Created | 2023-05-22 |
| Est. Tokens | ~16k |
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langfuse-docs is 🪢 Langfuse documentation -- Langfuse is the open source LLM Engineering Platform. Observability, evals, prompt management, playground and metrics to debug and improve LLM apps. It is categorized as a Agent Tool with 215 GitHub stars.
langfuse-docs is primarily written in MDX. It covers topics such as agent-skills, agents, genai.
You can find installation instructions and usage details in the langfuse-docs GitHub repository at github.com/langfuse/langfuse-docs. The project has 215 stars and 250 forks, indicating an active community.
langfuse-docs is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to langfuse-docs on Agent Skills Hub include langfuse-mcp, weam, lilypad. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.