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Qdrant

Exports data to a Qdrant collection.

Data Mapping​

Here's how CocoIndex data elements map to Qdrant elements during export:

CocoIndex ElementQdrant Element
an export targeta unique collection
a collected rowa point
a fielda named vector, if fits into Qdrant vector; or a field within payload otherwise

The following vector types fit into Qdrant vector:

  • One-dimensional vectors with fixed dimension, e.g. Vector[Float32, N], Vector[Float64, N] and Vector[Int64, N]. We map them to dense vectors.
  • Two-dimensional vectors whose inner layer is a one-dimensional vector with fixed dimension, e.g. Vector[Vector[Float32, N]], Vector[Vector[Int64, N]], Vector[Vector[Float64, N]]. The outer layer may or may not have a fixed dimension. We map them to multivectors.
vector type mapping to Qdrant

Since vectors in Qdrant must have fixed dimension, we only map vectors of number types with fixed dimension to Qdrant vectors. For all other vector types, we map to Qdrant payload as JSON arrays.

Spec​

The spec takes the following fields:

  • connection (auth reference to QdrantConnection, optional): The connection to the Qdrant instance. QdrantConnection has the following fields:

    • grpc_url (str): The gRPC URL of the Qdrant instance, e.g. http://localhost:6334/.
    • api_key (str, optional). API key to authenticate requests with.

    If connection is not provided, will use local Qdrant instance at http://localhost:6334/ by default.

  • collection_name (str, required): The name of the collection to export the data to.

You can find an end-to-end example here.

Example​

Text Embedding Qdrant Example