{
 "schema_version": 1,
 "generated": "2026-10-26",
 "id": "wanmol-goal-flow--ingest-documents-into-milvus-knowledge-base",
 "repo": "wanmol/goal-flow",
 "repo_url": "https://github.com/wanmol/goal-flow",
 "repo_slug": "wanmol-goal-flow",
 "title": "Load documents into Milvus for retrieval in a workflow",
 "page_title": "How to load documents into Milvus for retrieval in a workflow with Goal Flow",
 "summary": "Extract, chunk, and embed your documents into Milvus, then point a workflow at the retriever.",
 "who": "A researcher or support engineer who has a set of internal documents and wants a workflow to answer questions from them.",
 "problem": "An LLM workflow cannot answer from private documents until they are indexed in a vector store.",
 "outcome": "A Milvus collection holding embedded chunks of your documents, which a workflow can query through the pluggable retriever.",
 "steps": [
  "Run `git clone` on the goalflow repository and `cd goalflow`.",
  "Run `pip install -e .` and set Milvus connection values in .env from .env.example.",
  "Read docs/knowledge-retrieval.md to confirm the ingestion CLI name and options.",
  "Run the document ingestion CLI on your document folder to extract, chunk, embed, and write to Milvus. (inferred, check the README)",
  "Set the retriever to Milvus in your workflow configuration and run one test question."
 ],
 "agent_prompt": "In the goalflow repo, follow docs/knowledge-retrieval.md to ingest the documents in <document-folder> into Milvus. Expected output is a Milvus collection with embedded chunks. Verify the ingestion count matches the number of input documents and run one retrieval query for <question>.",
 "agents": [
  "any"
 ],
 "difficulty": "Advanced",
 "time": "2 hours",
 "basis": "readme",
 "caveat": "The README does not state the ingestion command or the Milvus settings, so the exact invocation must come from docs/knowledge-retrieval.md.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "python",
 "requirements": [
  "Python 3.12",
  "Redis (cluster or standalone) and MySQL",
  "A cloned copy of the goalflow repository and a filled-in .env file copied from .env.example",
  "A Dify DSL export (.yml) if you want to transpile a visual flow"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.7,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/wanmol-goal-flow/ingest-documents-into-milvus-knowledge-base/",
 "md": "https://dedupedai.com/use-cases/wanmol-goal-flow/ingest-documents-into-milvus-knowledge-base/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/wanmol-goal-flow--ingest-documents-into-milvus-knowledge-base.json",
 "api_version": "v1"
}