https://docs.dapr.io/developing-ai/rag/Recent content in RAG on Dapr DocsHugoenhttps://docs.dapr.io/developing-ai/rag/rag-quickstart/Mon, 01 Jan 0001 00:00:00 +0000https://docs.dapr.io/developing-ai/rag/rag-quickstart/<p>This quickstart runs a complete <code>DurableRAGPipeline</code> ingest-and-query cycle locally: documents are discovered from an object store, parsed, chunked, embedded with OpenAI, and written into a local <a href="https://github.com/pgvector/pgvector">pgvector</a> index. You&rsquo;ll then query that index and get back the document that answers your question.</p> <p>Pick whichever source matches how you&rsquo;ll actually deploy — the rest of the pipeline (embedding, pgvector, the worker/CLI commands, everything after &ldquo;Set up the environment&rdquo;) is identical either way:</p>