{
 "schema_version": 1,
 "generated": "2026-10-31",
 "id": "milvus-io-milvus--build-a-rag-pipeline-on-milvus",
 "repo": "milvus-io/milvus",
 "repo_url": "https://github.com/milvus-io/milvus",
 "repo_slug": "milvus-io-milvus",
 "title": "Build a RAG pipeline on Milvus",
 "page_title": "How to build a RAG pipeline on Milvus with Milvus",
 "summary": "Store document chunks in Milvus and retrieve them for an LLM, following the Build RAG tutorial.",
 "who": "A developer adding chat-with-your-docs to a product, using LangChain or LlamaIndex.",
 "problem": "Without a proper vector store, retrieval is slow and does not scale past a demo.",
 "outcome": "A RAG app that retrieves relevant chunks from Milvus and passes them to your LLM.",
 "steps": [
  "Install `pip install -U pymilvus` and set up Milvus Lite or connect to a server",
  "Follow the Build RAG with Milvus tutorial linked in the README",
  "Embed your chunks and insert them with their text as fields",
  "Retrieve with `client.search` and pass the returned text to your LLM",
  "Use the LangChain or LlamaIndex integration if you already use those frameworks"
 ],
 "agent_prompt": "Build a RAG pipeline for <documents> on milvus-io/milvus following the Build RAG with Milvus tutorial: chunk, embed with <model>, insert, retrieve top 3 with client.search and answer with <LLM>. Test it on <questions>.",
 "agents": [
  "claude-code",
  "codex",
  "cursor"
 ],
 "difficulty": "Intermediate",
 "time": "1 hour",
 "basis": "readme",
 "caveat": "The README links to the tutorial for full code; answer quality depends on your chunking and embedding model.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "go",
 "requirements": [
  "Python and the pymilvus SDK",
  "Milvus Lite for a local file, or a deployed Milvus server or Zilliz Cloud with credentials",
  "An embedding model to create vectors"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.9,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/milvus-io-milvus/build-a-rag-pipeline-on-milvus/",
 "md": "https://dedupedai.com/use-cases/milvus-io-milvus/build-a-rag-pipeline-on-milvus/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/milvus-io-milvus--build-a-rag-pipeline-on-milvus.json",
 "api_version": "v1"
}