Text_similarity_reranker retriever rework to be evaluated during rewrite phase #114085
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pmpailis
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…/elasticsearch into text_similarity_reranker_rework
...rg/elasticsearch/xpack/inference/rank/textsimilarity/TextSimilarityRankRetrieverBuilder.java
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| - length: { hits.hits: 2 } | ||
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| - match: { hits.hits.0._id: "doc_2" } | ||
| - match: { hits.hits.0._rank: 1 } |
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_rank has now been removed as with rrf.
elasticsearchmachine
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Pinging @elastic/es-search-relevance (Team:Search Relevance) |
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TextSimilarityRankDoc.java needs randomized serialization tests and we need to ensure whatever utilizes this named object (looks like RankDocsQueryBuilder and RankDocsRetrieverBuilder) exercise using this new named object some how.
We don't want to miss adding this new named object to the named serialization objects and such.
server/src/main/java/org/elasticsearch/action/search/SearchPhaseController.java
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...c/main/java/org/elasticsearch/xpack/inference/rank/textsimilarity/TextSimilarityRankDoc.java
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…ion; converting rankdoc to versionednamedwriteable; and adding serialization tests for textsimilarityrankdoc
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...rg/elasticsearch/xpack/inference/rank/textsimilarity/TextSimilarityRankRetrieverBuilder.java
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| testImplementation(testArtifact(project(':server'))) | ||
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| clusterModules project(xpackModule('rank-rrf')) | ||
| clusterModules project(xpackModule('inference')) |
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Why is rrf requiring inference?
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I've added this to actually exercise different semantic_reranking and rrf combinations (in 800_rrf_with_text_similarity_reranker_retriever.yml ) . AFAICT clusterModules is a test-only dependency, so there shouldn't be any changes in runtime dependencies.
However, I wasn't certain myself on what place would be the best for hosting such combined tests (needing code from both inference and rank-rrf ) so I'm really open to any alternatives :)
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run elasticsearch-ci/part-1 |
pmpailis
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Now that #112648 has been merged, in this PR we handle the
text_similarity_rerankerretriever next, so that it can be evaluated during the rewrite phase and be transformed to a flattenedRankDocsRetrieverBuilder. This will enable us to support composition and many search features, including highlighting, aggregations, and collapsing.