> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2-studio-tools-doc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Qdrant Async

## Code

```python cookbook/08_knowledge/vector_db/qdrant_db/async_qdrant_db.py theme={null}
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

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U qdrant-client pypdf openai agno
    ```
  </Step>

  <Step title="Run Qdrant">
    ```bash theme={null}
    docker run -d --name qdrant -p 6333:6333 qdrant/qdrant:latest
    ```
  </Step>

  <Step title="Run Agent">
    ```bash theme={null}
    python cookbook/08_knowledge/vector_db/qdrant_db/async_qdrant_db.py
    ```
  </Step>
</Steps>