cognee/docs/kr/setup-configuration/community-maintained/qdrant.md

Qdrant

Use Qdrant as a vector store through a community-maintained adapter

Qdrant is a vector search engine that stores embeddings and performs similarity searches. It supports both cloud-hosted and self-hosted deployments.

Cognee can use Qdrant as a [vector store](/setup-configuration/vector-stores) backend through this [community-maintained](/setup-configuration/community-maintained/overview) [adapter](https://github.com/topoteretes/cognee-community/tree/main/packages/vector/qdrant).

Installation

This adapter is a separate package from core Cognee. Before installing, complete the Cognee installation and ensure your environment is configured with LLM and embedding providers. After that, install the adapter package:

uv pip install cognee-community-vector-adapter-qdrant

Configuration

Run a local Qdrant instance:

```bash  theme={null}
docker run -p 6333:6333 -p 6334:6334 \
    -v "$(pwd)/qdrant_storage:/qdrant/storage:z" \
    qdrant/qdrant
```

Configure in Python:

```python  theme={null}
from cognee_community_vector_adapter_qdrant import register
from cognee import config

register()

config.set_vector_db_config({
    "vector_db_provider": "qdrant",
    "vector_db_url": "http://localhost:6333",
    "vector_db_key": "",
})
```

Or via environment variables:

```dotenv  theme={null}
VECTOR_DB_PROVIDER="qdrant"
VECTOR_DB_URL="http://localhost:6333"
VECTOR_DB_KEY=""
```

Get your API key and URL from the [Qdrant Cloud](https://qdrant.tech/documentation/cloud/) dashboard.

```python  theme={null}
from cognee_community_vector_adapter_qdrant import register
from cognee import config

register()

config.set_vector_db_config({
    "vector_db_provider": "qdrant",
    "vector_db_url": "https://your-cluster.qdrant.io",
    "vector_db_key": "your_api_key",
})
```

Or via environment variables:

```dotenv  theme={null}
VECTOR_DB_PROVIDER="qdrant"
VECTOR_DB_URL="https://your-cluster.qdrant.io"
VECTOR_DB_KEY="your_api_key"
```

Important Notes

Import and call `register()` from the adapter package before using Qdrant with Cognee. This registers the adapter with Cognee's provider system. Ensure `EMBEDDING_DIMENSIONS` matches your embedding model. See [Embedding Providers](/setup-configuration/embedding-providers) for configuration.

Changing dimensions requires recreating collections or running prune.prune_system().

Resources

Official documentation GitHub repository FAQ docs assistant example. Official vector providers All community integrations Configuration guide

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