Add movie recommendation example using IMap and similarity search [AI-298] #710
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TomaszGaweda
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TomaszGaweda
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Two nits, overall good job :)
| // transform user input to vector | ||
| float[] query = embeddingModel.embed(userInput).content().vector(); | ||
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| // find & output top 10 similar matches of plot summary to given text |
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maybe we could do 2 in 1 (via some flag etc), so code wouldn't be commented?
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VectorPredicates.nearestNeighbours is not yet available even in 6.0-SNAPSHOT, so the example would not compile
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ok, then for now it's better to remove the commented code, as someone may try to use it
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ok, that will be probably less confusing: a82b3b5
...e-recommendation/src/main/java/com/hazelcast/samples/ai/movies/TextSimilaritySearchImap.java
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…/movies/TextSimilaritySearchImap.java Co-authored-by: Tomasz Gawęda <[email protected]>
…for embedding entry processor
TomaszGaweda
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TomaszGaweda
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Few comments, but I don't think re-review will be need, so approving in advance :) Good job!
| // transform user input to vector | ||
| float[] query = embeddingModel.embed(userInput).content().vector(); | ||
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| // find & output top 10 similar matches of plot summary to given text |
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ok, then for now it's better to remove the commented code, as someone may try to use it
| + "took " + Timer.secondsElapsed(start) + " seconds"); | ||
| } | ||
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| public static class MovieMetadata implements Serializable { |
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vector field is mutable. this could be avoided, in this case it is more a matter of taste. both solutions would be equally simple
| TextSimilaritySearchImap.offloaded = false; | ||
| TextSimilaritySearchImap.main(new String[]{"200% cars " + System.lineSeparator()}); | ||
| } | ||
| } No newline at end of file |
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nit, line endings:
| } | |
| } | |
| */ | ||
| public class TextSimilaritySearchImap { | ||
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| static boolean offloaded = true; |
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can you write a quick comment what it means "offloaded" in this particular case? Will be easier to understand for people.
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First from a series of AI related examples. This example demonstrates the idea of similarity search implemented in a straight-forward, simple but not the most efficient way. This is example code for an upcoming blog post.
Fixes https://hazelcast.atlassian.net/browse/AI-298
Note to reviewers: the PR contains quite large files (~80MB) - movie data.
Checklist: