Retrieving documents by their ids

from relevanceai import Client

client = Client(token=YOUR_ACTIVATION_TOKEN)
ds = client.Dataset("quickstart")

ids_to_retrieve = ["1", "2"]
ds.get(ids_to_retrieve)

ids that don't belong in the dataset will just return a document with just the _id.

Retrieve a random sample of documents

ds.get_documents(number_of_documents=20)

Retrieve all documents

ds.get_all_documents()

Retrieve documents options

You can freely adjust how the retrieve documents are returned.

Selected fields only

For all the above retrieve functions, you can choose which fields to include when retrieving the documents.

ds.get_documents(number_of_documents=20, select_fields=["name", "reviews.rating"])

By default we return all the vectors, but you can choose to remove them simply with include_vector=False

ds.get_documents(number_of_documents=20, include_vector=False)

Sort documents

You can sort documents by different fields as well desc for descending order, asc for ascending order.

ds.get_documents(sort=[{"reviews.rating":"desc"}])

The sort is multi-level as well, to further sort documents with same values.

ds.get_documents(sort=[{"reviews.rating":"desc"}, {"reviews.numHelpful":"desc"}])

Filter documents

You can retrieve documents that meet your filter criteria. Below is the simple way of doing it.

filters = ds["name"] == "Fire Tablet, 7 Display, Wi-Fi, 8 GB - Includes Special Offers, Magenta"
ds.get_documents(number_of_documents=20, filters=filters)

For the more advanced filtering options:

filters = [
    {
        "field": "name",
        "filter_type": "exact_match",
        "condition": "==",
        "condition_value": "Fire Tablet, 7 Display, Wi-Fi, 8 GB - Includes Special Offers, Magenta"
    }
]
ds.get_documents(number_of_documents=20, filters=filters)

For more filter options check out: Filters