Qdrant Async

Code

cookbook/08_knowledge/vector_db/qdrant_db/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

   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 qdrant-client pypdf openai agno
   
3. Run Qdrant

   docker run -d --name qdrant -p 6333:6333 qdrant/qdrant:latest
   
4. Run Agent

   python cookbook/08_knowledge/vector_db/qdrant_db/async_qdrant_db.py