Construct vector search queries
Just as you did in the previous step, you can explore the search results using an aggregation pipeline.
Querying with the aggregation builder​
Navigate to the Collections tab of your database deployment.
Navigate to the Aggregation tab from the navbar under your collection details.
Click the Add Stage button and type $search in the select input.
Add the following code for the
$search
stage.{
index: "vectorsearch",
knnBeta: {
vector: `vector goes here`,
path: "plot_embedding",
k: 20
}
}The stage uses the
vectorsearch
index. Rather than using the 'text' operator as we did for full-text searches, we are using the knnBeta operator this time.For now, this stage will break. You will need to pass it a vector in the
vector
property.Paste the following vector to replace the
vector goes here
text.
Click to see the vector for `apprentice sorcerer`
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Add the following implementation for the
$project
stage to filter the returned fields.{
title: 1,
year: 1,
"imdb.rating": 1,
fullplot: 1,
poster: 1,
released: 1,
genres: 1
}You should now see a list of related movies. Those movies may, or may not, contain the words
apprentice
orsorcerer
. Our search returns results that are similar in context, but not in content.