Every time I start a RAG/AI project, I end up repeating the same work: Docker setup vector database configuration embeddings project structure environment files starter APIs wiring everything together So I started building Metis — an open-source CLI that scaffolds a working AI development environment from a recipe. For example: metis init rag Metis can set up the Python app, Docker Compose, vector DB such as Qdrant/Chroma, embeddings, FastAPI starter code, and the surrounding project structure. The longer-term idea is to make AI project setup spec/recipe-driven , so developers spend less time assembling infrastructure and more time building the actual application. I'm actively developing it and would really value feedback from people building RAG / agentic applications. GitHub: https:/

  • 情报分类：项目价值、技术价值
  • 命中依据：开源CLI工具，简化GenAI项目搭建
  • 来源：Reddit · SideProject
  • 原作者：/u/NormalParsnip8216 https://www.reddit.com/user/NormalParsnip8216
  • 发布时间：2026/9/13 07:17:39