Milvus Hybrid Search

Combine dense embeddings and sparse keyword vectors in one Milvus search with SearchType.hybrid.

Code

milvus_db_hybrid_search.py

from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.milvus import Milvus, SearchType

vector_db = Milvus(
    collection="recipes", uri="/tmp/milvus_hybrid.db", search_type=SearchType.hybrid
)

knowledge = Knowledge(
    vector_db=vector_db,
)

knowledge.insert(
    url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf",
)

agent = Agent(knowledge=knowledge)
agent.print_response("How to make Tom Kha Gai", markdown=True)

Usage

1. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   

   uv venv --python 3.12
   .venv\Scripts\activate
   
2. Install dependencies

   uv pip install -U pymilvus pypdf openai agno
   
3. Set environment variables

   export OPENAI_API_KEY=xxx
   
4. Run Agent

   python milvus_db_hybrid_search.py