Code
async_qdrant_db.py
import asyncio
from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.qdrant import Qdrant
COLLECTION_NAME = "thai-recipes"
vector_db = Qdrant(collection=COLLECTION_NAME, url="http://localhost:6333")
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))
Usage
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U qdrant-client pypdf openai agno
3
Run Qdrant
docker run -d --name qdrant -p 6333:6333 qdrant/qdrant:latest
4
Run Agent
python async_qdrant_db.py