Retrieving data
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
Updated 9 months ago