Copy the Sample Query
This query searches for documents that include text in the plot
field of your sample movies data that is semantically related to the term "time travel".
[
{
"$vectorSearch": {
"index": "vector_index",
//vector embeddings of the movie plots
"path": "plot_embedding",
//vector embeddings of the search term "Time Travel"
"queryVector": 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"numCandidates": 150,
"limit": 10
}
},
{
"$project": {
"_id": 0,
"plot": 1,
"title": 1,
"score": { $meta: "vectorSearchScore" }
}
}
]
What does this query do?
What does this query do?
This query uses the $vectorSearch
stage to:
Compare vector embeddings of the search term "Time Travel" against vector embeddings of movie plots in the
plot_embedding
field of thesample_mflix.embedded_moves
collection.Consider up to the 150 most similar movie plots and return the top 10 results.
It uses the $project
stage to:
Only include the movie
plot
andtitle
fields in the results.Add a
score
field to show the relevance of each result to the search term.
The output of the query will be 10 movie plots, titles, and their scores that are semantically related to "Time Travel"
Next: Run the query in Atlas
Navigate to the Collections tab to view the Data Explorer. And click into the sample_mflix.embedded_movies collection. Then click into the Aggregations tab.
In the Aggregations tab, go to the </> TEXT view on the top right corner and paste the query into the code editor.