Managing Data

Before inserting data into the vector store, a collection must be created. To create a collection, please follow the guidelines on the Managing Collections page.

Once you've created your first collection, you can easily starting managing your data.

📘

Creating a collection

For this tutorial, we'll use an example collection named product_catalog:

Python

from qwak.vector_store import VectorStoreClient

client = VectorStoreClient()
catalog_collection = client.create_collection(name="product_catalog",
                                              description="A product catalog",
                                              dimension=3,
                                              metric="cosine")

Upserting vectors

Upserting vectors allows you to either add new or replace existing vectors.

• Each vector must have a unique UUID4 formatted ID.
• The vector size must match the dimension of the collection

from qwak.vector_store import VectorStoreClient

client = VectorStoreClient()
collection = client.get_collection_by_name("product_catalog")

collection.upsert(
    ids=[
      "70165628-d42c-48b7-bba1-f86006b201c0"
    ],
    vectors=[
      [0.1, 0.2, 0.3]
    ],
    properties=[{
        "name": "Shoes",
        "color": "yellow",
        "size": "large"
    }]
)

Searching vectors

Searching vectors allows your to find vector similarity based on a reference vector

• The vector size must match the dimension of the collection
• Choose properties to include in the vector response.
• The similarity distance and matched vectors may be optionally returned in the response

from qwak.vector_store import VectorStoreClient

client = VectorStoreClient()
collection = client.get_collection_by_name("product_catalog")

search_results = collection.search(output_properties=["name", "color", "size"],
                                   vector=[0.1, 0.2, 0.3],
                                   top_results=5,
                                   include_id=True,
                                   include_vector=False,
                                   include_distance=False
                                  )

Deleting vectors

Deleting a vector is made by supplying the UUID of the saved vector.

from qwak.vector_store import VectorStoreClient

client = VectorStoreClient()
collection = client.get_collection_by_name("product_catalog")

collection.delete(
    vector_ids=["70165628-d42c-48b7-bba1-f86006b201c0"]
)