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Enhance vector store observability support

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* Consolidate usage of “db.collection.name” attribute to track table name, collection name, index name, document name, or whatever concept a vector database uses to store data. Removed “db.index” that was use sometimes instead of “db.collection.name”. This usage is in line with the OpenTelemetry Semantic Conventions.
* Configure query response content to be included as a “span event” instead of a “span attribute” if the backend system supports that, similar to how we do for the model observations.
* Structure vector store observation attributes in dedicated enums, including one for the Spring AI Kinds to avoid hard-coding the same value in a lot of places. This follows the OpenTelemetry Semantic Conventions as much as possible. Also, adopt Spring usual non-null-by-default strategy as much as possible.
* Align vector store conventions to the chat model ones, and follow alphabetical order for values. This is particularly useful for the convention classes, for which the Micrometer performance of exporting telemetry data improves when key values are added already sorted to the context.
* Fix flaky test in Mistral AI.
* Improve Qdrant integration tests.

Signed-off-by: Thomas Vitale <ThomasVitale@users.noreply.github.com>
This commit is contained in:
Thomas Vitale
2024-08-22 08:23:43 +02:00
committed by Christian Tzolov
parent 99d679f232
commit 036093a42b
74 changed files with 1456 additions and 836 deletions
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5
vector-stores/spring-ai-opensearch-store/src/main/java/org/springframework/ai/vectorstore/OpenSearchVectorStore.java
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@@ -55,6 +55,7 @@ import java.util.stream.Collectors;
* @author Jemin Huh
* @author Soby Chacko
* @author Christian Tzolov
* @author Thomas Vitale
* @since 1.0.0
*/
public class OpenSearchVectorStore extends AbstractObservationVectorStore implements InitializingBean {
@@ -261,9 +262,9 @@ public class OpenSearchVectorStore extends AbstractObservationVectorStore implem
@Override
public Builder createObservationContextBuilder(String operationName) {
return VectorStoreObservationContext.builder(VectorStoreProvider.OPENSEARCH.value(), operationName)
.withCollectionName(this.index)
.withDimensions(this.embeddingModel.dimensions())
.withSimilarityMetric(getSimilarityFunction())
.withIndexName(this.index);
.withSimilarityMetric(getSimilarityFunction());
}
private String getSimilarityFunction() {

49
vector-stores/spring-ai-opensearch-store/src/test/java/org/springframework/ai/vectorstore/OpenSearchVectorStoreObservationIT.java
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@@ -36,6 +36,7 @@ import org.opensearch.client.transport.httpclient5.ApacheHttpClient5TransportBui
import org.opensearch.testcontainers.OpensearchContainer;
import org.springframework.ai.document.Document;
import org.springframework.ai.embedding.EmbeddingModel;
import org.springframework.ai.observation.conventions.SpringAiKind;
import org.springframework.ai.observation.conventions.VectorStoreProvider;
import org.springframework.ai.openai.OpenAiEmbeddingModel;
import org.springframework.ai.openai.api.OpenAiApi;
@@ -60,6 +61,7 @@ import static org.hamcrest.Matchers.hasSize;
/**
* @author Christian Tzolov
* @author Thomas Vitale
*/
@EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
@Testcontainers
@@ -118,19 +120,22 @@ public class OpenSearchVectorStoreObservationIT {
.doesNotHaveAnyRemainingCurrentObservation()
.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
.that()
.hasContextualNameEqualTo("vector_store opensearch add")
.hasContextualNameEqualTo("opensearch add")
.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "add")
.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
VectorStoreProvider.OPENSEARCH.value())
.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "none")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "none")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "none")
.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(),
SpringAiKind.VECTOR_STORE.value())
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_QUERY_CONTENT.asString(), "none")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_DIMENSION_COUNT.asString(), "1536")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_COLLECTION_NAME.asString(),
OpenSearchVectorStore.DEFAULT_INDEX_NAME)
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_NAMESPACE.asString(), "none")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_FIELD_NAME.asString(), "none")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_SIMILARITY_METRIC.asString(), "cosine")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_QUERY_TOP_K.asString(), "none")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_QUERY_SIMILARITY_THRESHOLD.asString(),
"none")
.hasBeenStarted()
.hasBeenStopped();
@@ -150,20 +155,24 @@ public class OpenSearchVectorStoreObservationIT {
.doesNotHaveAnyRemainingCurrentObservation()
.hasObservationWithNameEqualTo(DefaultVectorStoreObservationConvention.DEFAULT_NAME)
.that()
.hasContextualNameEqualTo("vector_store opensearch query")
.hasContextualNameEqualTo("opensearch query")
.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_OPERATION_NAME.asString(), "query")
.hasLowCardinalityKeyValue(LowCardinalityKeyNames.DB_SYSTEM.asString(),
VectorStoreProvider.OPENSEARCH.value())
.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(), "vector_store")
.hasLowCardinalityKeyValue(LowCardinalityKeyNames.SPRING_AI_KIND.asString(),
SpringAiKind.VECTOR_STORE.value())
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.QUERY.asString(), "What is Great Depression")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DIMENSIONS.asString(), "1536")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.COLLECTION_NAME.asString(), "none")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.NAMESPACE.asString(), "none")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.FIELD_NAME.asString(), "none")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_METRIC.asString(), "cosine")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.TOP_K.asString(), "1")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.SIMILARITY_THRESHOLD.asString(), "0.0")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_QUERY_CONTENT.asString(),
"What is Great Depression")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_DIMENSION_COUNT.asString(), "1536")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_COLLECTION_NAME.asString(),
OpenSearchVectorStore.DEFAULT_INDEX_NAME)
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_NAMESPACE.asString(), "none")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_FIELD_NAME.asString(), "none")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_SIMILARITY_METRIC.asString(), "cosine")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_QUERY_TOP_K.asString(), "1")
.hasHighCardinalityKeyValue(HighCardinalityKeyNames.DB_VECTOR_QUERY_SIMILARITY_THRESHOLD.asString(),
"0.0")
.hasBeenStarted()
.hasBeenStopped();