nearest-neighborword-embeddingvespavector-databasesemantic-search
How to view Vespa Embedding?
I tried the following block of code to implement nearest neighbor search algorithm in Vespa. https://docs.vespa.ai/en/nearest-neighbor-search-guide.html I was able to run it successfully but was unable to identify where this Vector DB/Embedding is getting saved.
I want to query the embedding column, which I was unable to see, however I am able to see the Title, track and other columns.
Solution
Just add "summary" to the indexing statement in your schema:
field embedding type tensor<float>(x[384]) {
indexing: input title | embed e5 | attribute | index | summary
You can configure different sets of fields to be returned for different queries by configuring multiple document summaries.
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