Generative AI, LLMs, and RAG have been at the forefront of technological innovation and discussion. Retrieval-augmented generation (RAG) has emerged as a powerful pattern for building LLM applications that can reason over your data, reducing hallucinations and providing up-to-date, contextually relevant answers.

Most of the time, I found the RAG tutorials involve a dedicated vector database like Pinecone, Weaviate, or Chroma. These are fantastic for production systems, but what should I use for local development, rapid prototyping, or smaller-scale applications? The overhead of setting up, managing, and paying for a database service is not a better choice when you just want to build something.