Milvus

Code

milvus_db.py

import asyncio

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

vector_db = Milvus(
    collection="recipes",
    uri="/tmp/milvus.db",
)

knowledge = Knowledge(
    name="My Milvus Knowledge Base",
    description="This is a knowledge base that uses a Milvus DB",
    vector_db=vector_db,
)

asyncio.run(
    knowledge.ainsert(
        name="Recipes",
        url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf",
        metadata={"doc_type": "recipe_book"},
    )
)

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

vector_db.delete_by_name("Recipes")

vector_db.delete_by_metadata({"doc_type": "recipe_book"})

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. Run Agent

   python milvus_db.py