-
Notifications
You must be signed in to change notification settings - Fork 25.3k
Fix minscore propagation in text similarity reranker #129223
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Fix minscore propagation in text similarity reranker #129223
Conversation
Small changes in BlobContainer interface and wrapper. Relates ES-11815
…129054) The reason the test fails is that operations contained _seq_no field with different doc value types (with no skippers and with skippers) and this isn't allowed, since field types need to be consistent in a Lucene index. The initial operations were generated not knowing about the fact the index mode was set to logsdb or time_series. Causing the operations to not have doc value skippers. However when replaying the operations via following engine, the operations did have doc value skippers. The fix is to set `index.seq_no.index_options` to `points_and_doc_values`, so that the initial operations are indexed without doc value skippers. This test doesn't gain anything from storing seqno with doc value skippers, so there is no loss of testing coverage. Closes elastic#128541
This ensures we package an aggregation zip with all artifacts we want to publish to maven central as part of a release. Running zipAggregation will produce a zip file in the build/nmcp/zip folder. The content of this zip is meant to match the maven artifacts we have currently declared as dra maven artifacts.
Runs a sanity check after loading a block of values. Previously we were doing a quick check if assertions were enabled. Now we do two quick checks all the time. Better - we attach information about how a block was loaded when there's a problem. Relates to elastic#128959
The functionality in `PhaseCacheManagement` was already project-aware, but these tests were still using deprecated methods.
This adds some testing tools for verifying vector recall and latency directly without having to spin up an entire ES node and running a rally track. Its pretty barebones and takes inspiration from lucene-util, but I wanted access to our own formats and tooling to make our lives easier. Here is an example config file. This will build the initial index, run queries at num_candidates: 50, then again at num_candidates 100 (without reindexing, and re-using the cached nearest neighbors). ``` [{ "doc_vectors" : "path", "query_vectors" : "path", "num_docs" : 10000, "num_queries" : 10, "index_type" : "hnsw", "num_candidates" : 50, "k" : 10, "hnsw_m" : 16, "hnsw_ef_construction" : 200, "index_threads" : 4, "reindex" : true, "force_merge" : false, "vector_space" : "maximum_inner_product", "dimensions" : 768 }, { "doc_vectors" : "path", "query_vectors" : "path", "num_docs" : 10000, "num_queries" : 10, "index_type" : "hnsw", "num_candidates" : 100, "k" : 10, "hnsw_m" : 16, "hnsw_ef_construction" : 200, "vector_space" : "maximum_inner_product", "dimensions" : 768 } ] ``` To execute: ``` ./gradlew :qa:vector:checkVec --args="/Path/to/knn_tester_config.json" ``` Calling `./gradlew :qa:vector:checkVecHelp` gives some guidance on how to use it, additionally providing a way to run it via java directly (useful to bypass gradlew guff).
Add a spec test of `LOOKUP JOIN` against a time series index.
This is part of an iterative process to make ILM project-aware.
…t {lookup-join.LookupJoinOnTimeSeriesIndex ASYNC} elastic#129078
…9076) The `ClusterState` parameter of the `asyncPredicate` is not used anywhere.
…t {lookup-join.LookupJoinOnTimeSeriesIndex SYNC} elastic#129082
…est {p0=upgraded_cluster/70_ilm/Test Lifecycle Still There And Indices Are Still Managed} elastic#129097
…est {p0=upgraded_cluster/90_ml_data_frame_analytics_crud/Get mixed cluster outlier_detection job} elastic#129098
…ollowedWithEnvironmentVariableFiles elastic#128867
…27613) This PR introduces 3 new settings: indices.merge.disk.check_interval, indices.merge.disk.watermark.high, and indices.merge.disk.watermark.high.max_headroom that control if the threadpool merge executor starts executing new merges when the disk space is getting low. The intent of this change is to avoid the situation where in-progress merges exhaust the available disk space on the node's local filesystem. To this end, the thread pool merge executor periodically monitors the available disk space, as well as the current disk space estimates required by all in-progress (currently running) merges on the node, and will NOT schedule any new merges if the disk space is getting low (by default below the 5% limit of the total disk space, or 100 GB, whichever is smaller (same as the disk allocation flood stage level)).
…tic#128735) This PR introduces a new include_vectors option to the _source retrieval context. When set to false, vectors are excluded from the returned _source. This is especially efficient when used with synthetic source, as it avoids loading vector fields entirely. By default, vectors remain included unless explicitly excluded.
…kSpaceTests testAvailableDiskSpaceMonitorWhenFileSystemStatErrors elastic#129149
…ic#129033) * Add transport version for ML inference Mistral chat completion * Add changelog for Mistral Chat Completion version fix * Revert "Add changelog for Mistral Chat Completion version fix" This reverts commit 7a57416.
All we care about is if reindex is true or false. We shouldn't worry about force merge. Because if reindex is true, we will create the directory, if its false, we won't.
…kSpaceTests testUnavailableBudgetBlocksNewMergeTasksFromStartingExecution elastic#129148
* Google Vertex AI completion model, response entity and tests * Fixed GoogleVertexAiServiceTest for Service configuration * Changelog * Removed downcasting and using `moveToFirstToken` * Create GoogleVertexAiChatCompletionResponseHandler for streaming and non streaming responses * Added unit tests * PR feedback * Removed googlevertexaicompletion model. Using just GoogleVertexAiChatCompletionModel for completion and chat completion * Renamed uri -> nonStreamingUri. Added streamingUri and getters in GoogleVertexAiChatCompletionModel * Moved rateLimitGroupHashing to subclasses of GoogleVertexAiModel * Fixed rate limit has of GoogleVertexAiRerankModel and refactored uri for GoogleVertexAiUnifiedChatCompletionRequest --------- Co-authored-by: lhoet-google <[email protected]> Co-authored-by: Jonathan Buttner <[email protected]>
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Pull Request Overview
This PR fixes an issue where the min_score parameter was not correctly propagated in the text similarity reranker by updating both the filtering logic in the retriever builder and the associated test cases.
- Fixed min_score validation and filtering behavior via inclusive comparison
- Added new test cases and updated existing ones to verify correct min_score handling
- Propagated the min_score parameter across relevant builder components
Reviewed Changes
Copilot reviewed 7 out of 7 changed files in this pull request and generated 1 comment.
Show a summary per file
File | Description |
---|---|
x-pack/plugin/inference/src/yamlRestTest/resources/rest-api-spec/test/inference/70_text_similarity_rank_retriever.yml | Adds new YAML tests to verify min_score functionality (including edge cases) |
x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/rank/textsimilarity/TextSimilarityRankRetrieverBuilder.java | Applies filtering based on min_score after reranking and introduces a new node feature for the fix |
x-pack/plugin/inference/src/main/java/org/elasticsearch/xpack/inference/InferenceFeatures.java | Registers the new node feature for min_score fix |
server/src/test/java/org/elasticsearch/search/retriever/RankDocsRetrieverBuilderTests.java | Updates test case factory to include an explicit null minScore parameter |
server/src/main/java/org/elasticsearch/search/retriever/RankDocsRetrieverBuilder.java | Introduces a new field and logic to propagate min_score with an inclusive comparison |
server/src/main/java/org/elasticsearch/search/retriever/CompoundRetrieverBuilder.java | Propagates the min_score parameter from the compound retriever |
server/src/main/java/org/elasticsearch/search/retriever/RankDocsRetrieverBuilder.java
Show resolved
Hide resolved
Pinging @elastic/es-search (Team:Search) |
server/src/main/java/org/elasticsearch/search/retriever/RankDocsRetrieverBuilder.java
Outdated
Show resolved
Hide resolved
…t-propagate-min-score-correctly
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Changes look good, one cleanup comment and waiting on a clean CI build.
server/src/main/java/org/elasticsearch/search/retriever/RankDocsRetrieverBuilder.java
Outdated
Show resolved
Hide resolved
…t-propagate-min-score-correctly
@mridula-s109 can you please also backport to 9.0? Thank you |
If we're backporting to 9.0, this should also go to 8.18, seeing as those are sibling releases |
@kderusso So should i backport these changes to both 9.0 and 8.18? |
@mridula-s109 yes, please backport to both as this is a bug fix. |
Thanks @kathleen, will do the same! |
* propgating retrievers to inner retrievers * test feature taken care of * Small changes in concurrent multipart upload interfaces (elastic#128977) Small changes in BlobContainer interface and wrapper. Relates ES-11815 * Unmute FollowingEngineTests#testProcessOnceOnPrimary() test (elastic#129054) The reason the test fails is that operations contained _seq_no field with different doc value types (with no skippers and with skippers) and this isn't allowed, since field types need to be consistent in a Lucene index. The initial operations were generated not knowing about the fact the index mode was set to logsdb or time_series. Causing the operations to not have doc value skippers. However when replaying the operations via following engine, the operations did have doc value skippers. The fix is to set `index.seq_no.index_options` to `points_and_doc_values`, so that the initial operations are indexed without doc value skippers. This test doesn't gain anything from storing seqno with doc value skippers, so there is no loss of testing coverage. Closes elastic#128541 * [Build] Add support for publishing to maven central (elastic#128659) This ensures we package an aggregation zip with all artifacts we want to publish to maven central as part of a release. Running zipAggregation will produce a zip file in the build/nmcp/zip folder. The content of this zip is meant to match the maven artifacts we have currently declared as dra maven artifacts. * ESQL: Check for errors while loading blocks (elastic#129016) Runs a sanity check after loading a block of values. Previously we were doing a quick check if assertions were enabled. Now we do two quick checks all the time. Better - we attach information about how a block was loaded when there's a problem. Relates to elastic#128959 * Make `PhaseCacheManagementTests` project-aware (elastic#129047) The functionality in `PhaseCacheManagement` was already project-aware, but these tests were still using deprecated methods. * Vector test tools (elastic#128934) This adds some testing tools for verifying vector recall and latency directly without having to spin up an entire ES node and running a rally track. Its pretty barebones and takes inspiration from lucene-util, but I wanted access to our own formats and tooling to make our lives easier. Here is an example config file. This will build the initial index, run queries at num_candidates: 50, then again at num_candidates 100 (without reindexing, and re-using the cached nearest neighbors). ``` [{ "doc_vectors" : "path", "query_vectors" : "path", "num_docs" : 10000, "num_queries" : 10, "index_type" : "hnsw", "num_candidates" : 50, "k" : 10, "hnsw_m" : 16, "hnsw_ef_construction" : 200, "index_threads" : 4, "reindex" : true, "force_merge" : false, "vector_space" : "maximum_inner_product", "dimensions" : 768 }, { "doc_vectors" : "path", "query_vectors" : "path", "num_docs" : 10000, "num_queries" : 10, "index_type" : "hnsw", "num_candidates" : 100, "k" : 10, "hnsw_m" : 16, "hnsw_ef_construction" : 200, "vector_space" : "maximum_inner_product", "dimensions" : 768 } ] ``` To execute: ``` ./gradlew :qa:vector:checkVec --args="/Path/to/knn_tester_config.json" ``` Calling `./gradlew :qa:vector:checkVecHelp` gives some guidance on how to use it, additionally providing a way to run it via java directly (useful to bypass gradlew guff). * ES|QL: refactor generative tests (elastic#129028) * Add a test of LOOKUP JOIN against a time series index (elastic#129007) Add a spec test of `LOOKUP JOIN` against a time series index. * Make ILM `ClusterStateWaitStep` project-aware (elastic#129042) This is part of an iterative process to make ILM project-aware. * Mute org.elasticsearch.xpack.esql.qa.mixed.MixedClusterEsqlSpecIT test {lookup-join.LookupJoinOnTimeSeriesIndex ASYNC} elastic#129078 * Remove `ClusterState` param from ILM `AsyncBranchingStep` (elastic#129076) The `ClusterState` parameter of the `asyncPredicate` is not used anywhere. * Mute org.elasticsearch.xpack.esql.qa.mixed.MixedClusterEsqlSpecIT test {lookup-join.LookupJoinOnTimeSeriesIndex SYNC} elastic#129082 * Mute org.elasticsearch.upgrades.UpgradeClusterClientYamlTestSuiteIT test {p0=upgraded_cluster/70_ilm/Test Lifecycle Still There And Indices Are Still Managed} elastic#129097 * Mute org.elasticsearch.upgrades.UpgradeClusterClientYamlTestSuiteIT test {p0=upgraded_cluster/90_ml_data_frame_analytics_crud/Get mixed cluster outlier_detection job} elastic#129098 * Mute org.elasticsearch.packaging.test.DockerTests test081SymlinksAreFollowedWithEnvironmentVariableFiles elastic#128867 * Threadpool merge executor is aware of available disk space (elastic#127613) This PR introduces 3 new settings: indices.merge.disk.check_interval, indices.merge.disk.watermark.high, and indices.merge.disk.watermark.high.max_headroom that control if the threadpool merge executor starts executing new merges when the disk space is getting low. The intent of this change is to avoid the situation where in-progress merges exhaust the available disk space on the node's local filesystem. To this end, the thread pool merge executor periodically monitors the available disk space, as well as the current disk space estimates required by all in-progress (currently running) merges on the node, and will NOT schedule any new merges if the disk space is getting low (by default below the 5% limit of the total disk space, or 100 GB, whichever is smaller (same as the disk allocation flood stage level)). * Add option to include or exclude vectors from _source retrieval (elastic#128735) This PR introduces a new include_vectors option to the _source retrieval context. When set to false, vectors are excluded from the returned _source. This is especially efficient when used with synthetic source, as it avoids loading vector fields entirely. By default, vectors remain included unless explicitly excluded. * Remove direct minScore propagation to inner retrievers * cleaned up skip * Mute org.elasticsearch.index.engine.ThreadPoolMergeExecutorServiceDiskSpaceTests testAvailableDiskSpaceMonitorWhenFileSystemStatErrors elastic#129149 * Add transport version for ML inference Mistral chat completion (elastic#129033) * Add transport version for ML inference Mistral chat completion * Add changelog for Mistral Chat Completion version fix * Revert "Add changelog for Mistral Chat Completion version fix" This reverts commit 7a57416. * Correct index path validation (elastic#129144) All we care about is if reindex is true or false. We shouldn't worry about force merge. Because if reindex is true, we will create the directory, if its false, we won't. * Mute org.elasticsearch.index.engine.ThreadPoolMergeExecutorServiceDiskSpaceTests testUnavailableBudgetBlocksNewMergeTasksFromStartingExecution elastic#129148 * Implemented completion task for Google VertexAI (elastic#128694) * Google Vertex AI completion model, response entity and tests * Fixed GoogleVertexAiServiceTest for Service configuration * Changelog * Removed downcasting and using `moveToFirstToken` * Create GoogleVertexAiChatCompletionResponseHandler for streaming and non streaming responses * Added unit tests * PR feedback * Removed googlevertexaicompletion model. Using just GoogleVertexAiChatCompletionModel for completion and chat completion * Renamed uri -> nonStreamingUri. Added streamingUri and getters in GoogleVertexAiChatCompletionModel * Moved rateLimitGroupHashing to subclasses of GoogleVertexAiModel * Fixed rate limit has of GoogleVertexAiRerankModel and refactored uri for GoogleVertexAiUnifiedChatCompletionRequest --------- Co-authored-by: lhoet-google <[email protected]> Co-authored-by: Jonathan Buttner <[email protected]> * Fixing minscore filtering in the text similarity reranker * ES|QL - kNN function initial support (elastic#127322) * Remove optional seed from ES|QL SAMPLE (elastic#128887) * Remove optional seed from ES|QL SAMPLE * make it clear that seed is for testing * [Inference API] Add "rerank" task type to "elastic" provider (elastic#126022) * Rename target destination for microbenchmarks (elastic#128878) * Include direct memory and non-heap memory in ML memory calculations (take elastic#2) (elastic#128742) * Include direct memory and non-heap memory in ML memory calculations. * Reduce ML_ONLY heap size, so that direct memory is accounted for. * [CI] Auto commit changes from spotless * changelog * improve docs * Reuse direct memory to heap factor * feature flag --------- Co-authored-by: elasticsearchmachine <[email protected]> * Throw better exception for unsupported aggregations over shape fields (elastic#129139) * Update Test Framework To Handle Query Rewrites That Rely on Non-Null Searchers (elastic#129160) * Update ReproduceInfoPrinter to correctly print a reproduction line for Lucene & build candidate upgrade tests (elastic#129044) * Increment inference stats counter for shard bulk inference calls (elastic#129140) This change updates the inference stats counter to include chunked inference calls performed by the shard bulk inference filter on all semantic text fields. It ensures that usage of inference on semantic text fields is properly recorded in the stats. * Synthetic source: avoid storing multi fields of type text and match_only_text by default. (elastic#129126) Don't store text and match_only_text field by default when source mode is synthetic and a field is a multi field or when there is a suitable multi field. Without this change, ES would store field otherwise twice in a multi-field configuration. For example: ``` ... "os": { "properties": { "name": { "ignore_above": 1024, "type": "keyword", "fields": { "text": { "type": "match_only_text" } } } ... ``` In this case, two stored fields were added, one in case for the `name` field and one for `name.text` multi-field. This change prevents this, and would never store a stored field when text or match_only_text field is a multi-field. * Adding `scheduled_report_id` field to kibana reporting template (elastic#127827) * Adding scheduled_report_id field to kibana reporting template * Incrementing stack template registry version * ES|QL: Add FORK generative tests (elastic#129135) * ES|QL Completion command syntax change (elastic#129189) * propagated minscore to rankdsocsretrieverbuilder * Modified the file to include minscore and the test case to verify it * Revert "Use IndexOrDocValuesQuery in NumberFieldType#termQuery implementations (elastic#128293)" (elastic#129206) This reverts commit de7c91c. * Fixed the rankdocsretriever builder * Update docs/changelog/129223.yaml * Update 129223.yaml * trying to introduce cluster featureS * included cluster features in the test * Fixed the merge issue * [CI] Auto commit changes from spotless * Removed local variable from RankDocsRetrieverBuilder * Update RankDocsRetrieverBuilder.java --------- Co-authored-by: Tanguy Leroux <[email protected]> Co-authored-by: Martijn van Groningen <[email protected]> Co-authored-by: Rene Groeschke <[email protected]> Co-authored-by: Nik Everett <[email protected]> Co-authored-by: Niels Bauman <[email protected]> Co-authored-by: Benjamin Trent <[email protected]> Co-authored-by: Luigi Dell'Aquila <[email protected]> Co-authored-by: Bogdan Pintea <[email protected]> Co-authored-by: elasticsearchmachine <[email protected]> Co-authored-by: Albert Zaharovits <[email protected]> Co-authored-by: Jim Ferenczi <[email protected]> Co-authored-by: Jan-Kazlouski-elastic <[email protected]> Co-authored-by: Leonardo Hoet <[email protected]> Co-authored-by: lhoet-google <[email protected]> Co-authored-by: Jonathan Buttner <[email protected]> Co-authored-by: Carlos Delgado <[email protected]> Co-authored-by: Jan Kuipers <[email protected]> Co-authored-by: Tim Grein <[email protected]> Co-authored-by: Ievgen Degtiarenko <[email protected]> Co-authored-by: elasticsearchmachine <[email protected]> Co-authored-by: Ignacio Vera <[email protected]> Co-authored-by: Mike Pellegrini <[email protected]> Co-authored-by: Moritz Mack <[email protected]> Co-authored-by: Ying Mao <[email protected]> Co-authored-by: Ioana Tagirta <[email protected]> Co-authored-by: Aurélien FOUCRET <[email protected]>
* propgating retrievers to inner retrievers * test feature taken care of * Small changes in concurrent multipart upload interfaces (#128977) Small changes in BlobContainer interface and wrapper. Relates ES-11815 * Unmute FollowingEngineTests#testProcessOnceOnPrimary() test (#129054) The reason the test fails is that operations contained _seq_no field with different doc value types (with no skippers and with skippers) and this isn't allowed, since field types need to be consistent in a Lucene index. The initial operations were generated not knowing about the fact the index mode was set to logsdb or time_series. Causing the operations to not have doc value skippers. However when replaying the operations via following engine, the operations did have doc value skippers. The fix is to set `index.seq_no.index_options` to `points_and_doc_values`, so that the initial operations are indexed without doc value skippers. This test doesn't gain anything from storing seqno with doc value skippers, so there is no loss of testing coverage. Closes #128541 * [Build] Add support for publishing to maven central (#128659) This ensures we package an aggregation zip with all artifacts we want to publish to maven central as part of a release. Running zipAggregation will produce a zip file in the build/nmcp/zip folder. The content of this zip is meant to match the maven artifacts we have currently declared as dra maven artifacts. * ESQL: Check for errors while loading blocks (#129016) Runs a sanity check after loading a block of values. Previously we were doing a quick check if assertions were enabled. Now we do two quick checks all the time. Better - we attach information about how a block was loaded when there's a problem. Relates to #128959 * Make `PhaseCacheManagementTests` project-aware (#129047) The functionality in `PhaseCacheManagement` was already project-aware, but these tests were still using deprecated methods. * Vector test tools (#128934) This adds some testing tools for verifying vector recall and latency directly without having to spin up an entire ES node and running a rally track. Its pretty barebones and takes inspiration from lucene-util, but I wanted access to our own formats and tooling to make our lives easier. Here is an example config file. This will build the initial index, run queries at num_candidates: 50, then again at num_candidates 100 (without reindexing, and re-using the cached nearest neighbors). ``` [{ "doc_vectors" : "path", "query_vectors" : "path", "num_docs" : 10000, "num_queries" : 10, "index_type" : "hnsw", "num_candidates" : 50, "k" : 10, "hnsw_m" : 16, "hnsw_ef_construction" : 200, "index_threads" : 4, "reindex" : true, "force_merge" : false, "vector_space" : "maximum_inner_product", "dimensions" : 768 }, { "doc_vectors" : "path", "query_vectors" : "path", "num_docs" : 10000, "num_queries" : 10, "index_type" : "hnsw", "num_candidates" : 100, "k" : 10, "hnsw_m" : 16, "hnsw_ef_construction" : 200, "vector_space" : "maximum_inner_product", "dimensions" : 768 } ] ``` To execute: ``` ./gradlew :qa:vector:checkVec --args="/Path/to/knn_tester_config.json" ``` Calling `./gradlew :qa:vector:checkVecHelp` gives some guidance on how to use it, additionally providing a way to run it via java directly (useful to bypass gradlew guff). * ES|QL: refactor generative tests (#129028) * Add a test of LOOKUP JOIN against a time series index (#129007) Add a spec test of `LOOKUP JOIN` against a time series index. * Make ILM `ClusterStateWaitStep` project-aware (#129042) This is part of an iterative process to make ILM project-aware. * Mute org.elasticsearch.xpack.esql.qa.mixed.MixedClusterEsqlSpecIT test {lookup-join.LookupJoinOnTimeSeriesIndex ASYNC} #129078 * Remove `ClusterState` param from ILM `AsyncBranchingStep` (#129076) The `ClusterState` parameter of the `asyncPredicate` is not used anywhere. * Mute org.elasticsearch.xpack.esql.qa.mixed.MixedClusterEsqlSpecIT test {lookup-join.LookupJoinOnTimeSeriesIndex SYNC} #129082 * Mute org.elasticsearch.upgrades.UpgradeClusterClientYamlTestSuiteIT test {p0=upgraded_cluster/70_ilm/Test Lifecycle Still There And Indices Are Still Managed} #129097 * Mute org.elasticsearch.upgrades.UpgradeClusterClientYamlTestSuiteIT test {p0=upgraded_cluster/90_ml_data_frame_analytics_crud/Get mixed cluster outlier_detection job} #129098 * Mute org.elasticsearch.packaging.test.DockerTests test081SymlinksAreFollowedWithEnvironmentVariableFiles #128867 * Threadpool merge executor is aware of available disk space (#127613) This PR introduces 3 new settings: indices.merge.disk.check_interval, indices.merge.disk.watermark.high, and indices.merge.disk.watermark.high.max_headroom that control if the threadpool merge executor starts executing new merges when the disk space is getting low. The intent of this change is to avoid the situation where in-progress merges exhaust the available disk space on the node's local filesystem. To this end, the thread pool merge executor periodically monitors the available disk space, as well as the current disk space estimates required by all in-progress (currently running) merges on the node, and will NOT schedule any new merges if the disk space is getting low (by default below the 5% limit of the total disk space, or 100 GB, whichever is smaller (same as the disk allocation flood stage level)). * Add option to include or exclude vectors from _source retrieval (#128735) This PR introduces a new include_vectors option to the _source retrieval context. When set to false, vectors are excluded from the returned _source. This is especially efficient when used with synthetic source, as it avoids loading vector fields entirely. By default, vectors remain included unless explicitly excluded. * Remove direct minScore propagation to inner retrievers * cleaned up skip * Mute org.elasticsearch.index.engine.ThreadPoolMergeExecutorServiceDiskSpaceTests testAvailableDiskSpaceMonitorWhenFileSystemStatErrors #129149 * Add transport version for ML inference Mistral chat completion (#129033) * Add transport version for ML inference Mistral chat completion * Add changelog for Mistral Chat Completion version fix * Revert "Add changelog for Mistral Chat Completion version fix" This reverts commit 7a57416. * Correct index path validation (#129144) All we care about is if reindex is true or false. We shouldn't worry about force merge. Because if reindex is true, we will create the directory, if its false, we won't. * Mute org.elasticsearch.index.engine.ThreadPoolMergeExecutorServiceDiskSpaceTests testUnavailableBudgetBlocksNewMergeTasksFromStartingExecution #129148 * Implemented completion task for Google VertexAI (#128694) * Google Vertex AI completion model, response entity and tests * Fixed GoogleVertexAiServiceTest for Service configuration * Changelog * Removed downcasting and using `moveToFirstToken` * Create GoogleVertexAiChatCompletionResponseHandler for streaming and non streaming responses * Added unit tests * PR feedback * Removed googlevertexaicompletion model. Using just GoogleVertexAiChatCompletionModel for completion and chat completion * Renamed uri -> nonStreamingUri. Added streamingUri and getters in GoogleVertexAiChatCompletionModel * Moved rateLimitGroupHashing to subclasses of GoogleVertexAiModel * Fixed rate limit has of GoogleVertexAiRerankModel and refactored uri for GoogleVertexAiUnifiedChatCompletionRequest --------- * Fixing minscore filtering in the text similarity reranker * ES|QL - kNN function initial support (#127322) * Remove optional seed from ES|QL SAMPLE (#128887) * Remove optional seed from ES|QL SAMPLE * make it clear that seed is for testing * [Inference API] Add "rerank" task type to "elastic" provider (#126022) * Rename target destination for microbenchmarks (#128878) * Include direct memory and non-heap memory in ML memory calculations (take #2) (#128742) * Include direct memory and non-heap memory in ML memory calculations. * Reduce ML_ONLY heap size, so that direct memory is accounted for. * [CI] Auto commit changes from spotless * changelog * improve docs * Reuse direct memory to heap factor * feature flag --------- * Throw better exception for unsupported aggregations over shape fields (#129139) * Update Test Framework To Handle Query Rewrites That Rely on Non-Null Searchers (#129160) * Update ReproduceInfoPrinter to correctly print a reproduction line for Lucene & build candidate upgrade tests (#129044) * Increment inference stats counter for shard bulk inference calls (#129140) This change updates the inference stats counter to include chunked inference calls performed by the shard bulk inference filter on all semantic text fields. It ensures that usage of inference on semantic text fields is properly recorded in the stats. * Synthetic source: avoid storing multi fields of type text and match_only_text by default. (#129126) Don't store text and match_only_text field by default when source mode is synthetic and a field is a multi field or when there is a suitable multi field. Without this change, ES would store field otherwise twice in a multi-field configuration. For example: ``` ... "os": { "properties": { "name": { "ignore_above": 1024, "type": "keyword", "fields": { "text": { "type": "match_only_text" } } } ... ``` In this case, two stored fields were added, one in case for the `name` field and one for `name.text` multi-field. This change prevents this, and would never store a stored field when text or match_only_text field is a multi-field. * Adding `scheduled_report_id` field to kibana reporting template (#127827) * Adding scheduled_report_id field to kibana reporting template * Incrementing stack template registry version * ES|QL: Add FORK generative tests (#129135) * ES|QL Completion command syntax change (#129189) * propagated minscore to rankdsocsretrieverbuilder * Modified the file to include minscore and the test case to verify it * Revert "Use IndexOrDocValuesQuery in NumberFieldType#termQuery implementations (#128293)" (#129206) This reverts commit de7c91c. * Fixed the rankdocsretriever builder * Update docs/changelog/129223.yaml * Update 129223.yaml * trying to introduce cluster featureS * included cluster features in the test * Fixed the merge issue * [CI] Auto commit changes from spotless * Removed local variable from RankDocsRetrieverBuilder * Update RankDocsRetrieverBuilder.java --------- Co-authored-by: Tanguy Leroux <[email protected]> Co-authored-by: Martijn van Groningen <[email protected]> Co-authored-by: Rene Groeschke <[email protected]> Co-authored-by: Nik Everett <[email protected]> Co-authored-by: Niels Bauman <[email protected]> Co-authored-by: Benjamin Trent <[email protected]> Co-authored-by: Luigi Dell'Aquila <[email protected]> Co-authored-by: Bogdan Pintea <[email protected]> Co-authored-by: elasticsearchmachine <[email protected]> Co-authored-by: Albert Zaharovits <[email protected]> Co-authored-by: Jim Ferenczi <[email protected]> Co-authored-by: Jan-Kazlouski-elastic <[email protected]> Co-authored-by: Leonardo Hoet <[email protected]> Co-authored-by: lhoet-google <[email protected]> Co-authored-by: Jonathan Buttner <[email protected]> Co-authored-by: Carlos Delgado <[email protected]> Co-authored-by: Jan Kuipers <[email protected]> Co-authored-by: Tim Grein <[email protected]> Co-authored-by: Ievgen Degtiarenko <[email protected]> Co-authored-by: elasticsearchmachine <[email protected]> Co-authored-by: Ignacio Vera <[email protected]> Co-authored-by: Mike Pellegrini <[email protected]> Co-authored-by: Moritz Mack <[email protected]> Co-authored-by: Ying Mao <[email protected]> Co-authored-by: Ioana Tagirta <[email protected]> Co-authored-by: Aurélien FOUCRET <[email protected]>
Summary
This PR addresses an issue where the
min_score
parameter wasn't being properly propagated in the text similarity reranker. The fix ensures that documents are correctly filtered based on the specified minimum score threshold.Changes
Fixed min_score Validation and Filtering:
min_score
values greater than or equal to zero>=
) instead of exclusive (>
)Test Case Updates:
min_score = 0
to verify edge case handlingmin_score
values to ensure proper filteringBug Fix Verification
The bug has been verified as fixed by running a test query with
min_score: 10
. The query now correctly returns no results when no documents meet the minimum score threshold:Test Results
All Tests Passing Successfully ✅
All test cases related to the text similarity rank retriever are now passing, including the newly added tests for

min_score
functionality. The test suite shows: