DEDUPED Hot AI repos. Real use cases. What people build. Get the Monday 5

How to add full text and hybrid search to vector search with Milvus

Use BM25 full text search and sparse vectors alongside dense vectors for better recall.

Short answer: Connect to Milvus with MilvusClient using your server URI and token; then follow the Full Text Search with Milvus tutorial to enable BM25; follow the Hybrid Search with Milvus tutorial to combine dense and sparse embeddings. All steps.

Who it is forA search team whose semantic search misses exact names, codes and rare terms.

The problemDense vectors alone can miss exact keyword matches users expect.

The outcomeSearch that combines BM25 or learned sparse embeddings with dense semantic results.

What you need first

  • 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

Steps

  1. Connect to Milvus with MilvusClient using your server URI and token
  2. Follow the Full Text Search with Milvus tutorial to enable BM25
  3. Follow the Hybrid Search with Milvus tutorial to combine dense and sparse embeddings
  4. Compare results against dense-only search on real queries
  5. Turn on authentication, TLS and RBAC before exposing the server

Prompt for your agent

On my milvus-io/milvus server, add BM25 full text search and hybrid search for collection <name> following the README's tutorials. Compare hybrid and dense-only results on <queries> and recommend which to ship.

Caveat. Hybrid search setup lives in the linked tutorials, not in the README itself.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for milvus-io/milvus and "Add full text and hybrid search to vector search"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

Cursor, ChatGPT, others

Share: X LinkedIn Hacker News Email Copy link

Third-party repos we don't own. AI-written use cases can be wrong. Disclaimer