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mongodb-developer/GenAI-Showcase
MongoDB's Generative AI Showcase: an exhaustive collection of examples and sample applications covering Retrieval-Augmented Generation (RAG), AI agents, and industry-specific use cases.
A monorepo of MongoDB-flavored GenAI examples covering RAG, agents, and industry demos, split into notebooks, apps, workshops, and partner contributions. It's aimed at developers evaluating MongoDB Atlas as a vector store who want copy-pasteable starting points rather than a library to install.
The breadth is real — dozens of independent apps and notebooks spanning LangChain, LlamaIndex, voice agents, graph RAG, and multiple languages (Python, TS, Java), so there's a decent chance your specific stack combination already has an example. Each subfolder tends to be self-contained with its own README and requirements file rather than sharing a fragile common dependency tree, which limits blast radius when one example rots.
It's a loose collection with no shared abstractions or tests at the top level (CI only covers a notebook-widget-state hook, not actual example correctness), so quality and upkeep vary wildly folder to folder — some are polished demos, others look like one person's weekend hack. Everything assumes an Atlas cluster and pushes you toward MongoDB-specific vector search patterns, so the RAG/agent logic itself isn't really portable if you're on a different database. With 4200+ stars and constant partner PRs, expect drift: some notebooks will be using outdated SDK versions the day you clone them.