Code
async_milvus_db_hybrid_search.py
Usage
1
Set up your virtual environment
2
Install dependencies
3
Set environment variables
4
Run Agent
Documentation Index
Fetch the complete documentation index at: /llms.txt
Use this file to discover all available pages before exploring further.
Run Milvus hybrid search asynchronously with ainsert() and aprint_response().
import asyncio
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,
)
agent = Agent(knowledge=knowledge)
if __name__ == "__main__":
asyncio.run(knowledge.ainsert(
url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf",
))
asyncio.run(agent.aprint_response("How to make Tom Kha Gai", markdown=True))
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
Install dependencies
uv pip install -U pymilvus pypdf openai agno
Set environment variables
export OPENAI_API_KEY=xxx
Run Agent
python async_milvus_db_hybrid_search.py
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