Qdrant is a vector database that can store documents and vector embeddings. It can run as a self-hosted version or a managed Qdrant Cloud solution. The configuration is almost identical for both options, except for the API key that Qdrant Cloud provides.
Environment Variables:
| Name | Required | Description | Default |
|---|---|---|---|
DATASTORE |
Yes | Datastore name, set to qdrant |
|
BEARER_TOKEN |
Yes | Secret token | |
OPENAI_API_KEY |
Yes | OpenAI API key | |
QDRANT_URL |
Yes | Qdrant instance URL | http://localhost |
QDRANT_PORT |
Optional | TCP port for Qdrant HTTP communication | 6333 |
QDRANT_GRPC_PORT |
Optional | TCP port for Qdrant GRPC communication | 6334 |
QDRANT_API_KEY |
Optional | Qdrant API key for Qdrant Cloud | |
QDRANT_COLLECTION |
Optional | Qdrant collection name | document_chunks |
For a hosted Qdrant Cloud version, provide the Qdrant instance URL and the API key from the Qdrant Cloud UI.
Example:
QDRANT_URL="https://YOUR-CLUSTER-URL.aws.cloud.qdrant.io"
QDRANT_API_KEY="<YOUR_QDRANT_CLOUD_CLUSTER_API_KEY>"The other parameters are optional and can be changed if needed.
For a self-hosted version, use Docker containers or the official Helm chart for deployment. The only
required parameter is the QDRANT_URL that points to the Qdrant server URL.
Example:
QDRANT_URL="http://YOUR_HOST.example.com:6333"The other parameters are optional and can be changed if needed.
A suite of integration tests verifies the Qdrant integration. To run it, start a local Qdrant instance in a Docker container.
docker run -p "6333:6333" -p "6334:6334" qdrant/qdrant:v1.0.3Then, launch the test suite with this command:
pytest ./tests/datastore/providers/qdrant/test_qdrant_datastore.py