Qdrant

If you’re new to Unstructured, read this note first.

Before you can create a destination connector, you must first sign up for Unstructured. After you sign up, the Unstructured user interface (UI) appears, which you use to create the destination connector.

After you create the destination connector, add it along with a source connector to a workflow. Then run the worklow as a job. To learn how, try out the hands-on UI quickstart or watch the 4-minute video tutorial.

You can also create destination connectors with the Unstructured API. Learn how.

If you need help, reach out to the community on Slack, or contact us directly.

You are now ready to start creating a destination connector! Keep reading to learn how.

Send processed data from Unstructured to Qdrant.

The requirements are as follows.

• For the Unstructured UI or the Unstructured API, only Qdrant Cloud is supported.
• For Unstructured Ingest, Qdrant Cloud, Qdrant local, and Qdrant client-server are supported.

The following video shows how to set up Qdrant Cloud:

• For Qdrant local, the path to the local Qdrant installation, for example: /qdrant/local

• For Qdrant client-server, the Qdrant server URL, for example: http://localhost:6333

• For Qdrant Cloud:

  • A Qdrant account.

  • A Qdrant cluster.

  • The cluster’s URL. To get this URL, do the following:

    1. Sign in to your Qdrant Cloud account.
    2. On the sidebar, under Dashboard, click Clusters.
    3. Click the cluster’s name.
    4. Note the value of the Endpoint field, for example: https://<random-guid>.<region-id>.<cloud-provider>.cloud.qdrant.io.

  • A Qdrant API key.

• The name of the target collection on the Qdrant local installation, Qdrant server, or Qdrant Cloud cluster.

  Qdrant requires the target collection to exist before Unstructured can write to the collection. The following example code demonstrates the use of the Python Qdrant Client to create a collection on a Qdrant Cloud cluster, configuring the collection for vectors with 3072 dimensions:

  Python

  from qdrant_client import QdrantClient, models
  import os
  
  client = QdrantClient(
      url=os.getenv("QDRANT_URL"),
      api_key=os.getenv("QDRANT_API_KEY")
  )
  
  client.create_collection(
      collection_name=os.getenv("QDRANT_COLLECTION"),
      vectors_config=models.VectorParams(
          size=3072,
          distance=models.Distance.COSINE
      )
  )
  
  collection = client.get_collection(
                   collection_name=os.getenv("QDRANT_COLLECTION")
               )
  
  print(f"The collection named '{os.getenv("QDRANT_COLLECTION")}' exists and " +
        f"has a status of '{collection.status}'.")
  

To create the destination connector:

1. On the sidebar, click Connectors.
2. Click Destinations.
3. Cick New or Create Connector.
4. Give the connector some unique Name.
5. In the Provider area, click Qdrant.
6. Click Continue.
7. Follow the on-screen instructions to fill in the fields as described later on this page.
8. Click Save and Test.

Fill in the following fields:

• Name (required): A unique name for this connector.
• URL (required): The target Qdrant cluster’s URL.
• Collection Name (required): The name of the target collection on the cluster.
• Batch Size The maximum number of records to be transmitted per batch. The default is 50 if not otherwise specified.
• API Key (required): The Qdrant API key value.