QdrantSink

QdrantSink integrates with Qdrant vector search engine to manage vector data, enabling powerful search capabilities and efficient data storage.

The QdrantSink class provides functionality for storing and querying vector data within the Qdrant vector search engine, which is known for its performance in handling large-scale vector datasets.

Properties

Required properties:

• url: The connection URL to the Qdrant service.
• api_key: The API key for authenticating with the Qdrant API.
• collection_name: The name of the collection within Qdrant where the data will be stored. You can define the collection name to any string you want.

Optional properties:

Local Development

from neumai.SinkConnectors import QdrantSink

# Configure the QdrantSink with the necessary connection information
qdrant_sink = QdrantSink(
    url = "your-qdrant-url",
    api_key = "your-api-key",
    collection_name = "collection-name"
)