Make chat history available to RetrievalAugmentationAdvisor

spring-ai-core/src/main/java/org/springframework/ai/chat/client/advisor/RetrievalAugmentationAdvisor.java

@@ -102,8 +102,11 @@ public static Builder builder() {
 	public AdvisedRequest before(AdvisedRequest request) {
 		Map<String, Object> context = new HashMap<>(request.adviseContext());
 
-		// 0. Create a query from the user text and parameters.
-		Query originalQuery = new Query(new PromptTemplate(request.userText(), request.userParams()).render());
+		// 0. Create a query from the user text, parameters, and conversation history.
+		Query originalQuery = Query.builder()
+			.text(new PromptTemplate(request.userText(), request.userParams()).render())
+			.history(request.messages())
+			.build();
 
 		// 1. Transform original user query based on a chain of query transformers.
 		Query transformedQuery = originalQuery;

spring-ai-integration-tests/src/test/java/org/springframework/ai/integration/tests/client/advisor/RetrievalAugmentationAdvisorIT.java

@@ -24,7 +24,10 @@
 import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
 
 import org.springframework.ai.chat.client.ChatClient;
+import org.springframework.ai.chat.client.advisor.AbstractChatMemoryAdvisor;
+import org.springframework.ai.chat.client.advisor.MessageChatMemoryAdvisor;
 import org.springframework.ai.chat.client.advisor.RetrievalAugmentationAdvisor;
+import org.springframework.ai.chat.memory.InMemoryChatMemory;
 import org.springframework.ai.chat.model.ChatResponse;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.document.DocumentReader;
@@ -34,6 +37,8 @@
 import org.springframework.ai.integration.tests.TestApplication;
 import org.springframework.ai.openai.OpenAiChatModel;
 import org.springframework.ai.rag.preretrieval.query.expansion.MultiQueryExpander;
+import org.springframework.ai.rag.preretrieval.query.transformation.CompressionQueryTransformer;
+import org.springframework.ai.rag.preretrieval.query.transformation.RewriteQueryTransformer;
 import org.springframework.ai.rag.preretrieval.query.transformation.TranslationQueryTransformer;
 import org.springframework.ai.rag.retrieval.search.VectorStoreDocumentRetriever;
 import org.springframework.ai.reader.markdown.MarkdownDocumentReader;
@@ -103,6 +108,76 @@ void ragBasic() {
 		evaluateRelevancy(question, chatResponse);
 	}
 
+	@Test
+	void ragWithCompression() {
+		MessageChatMemoryAdvisor memoryAdvisor = MessageChatMemoryAdvisor.builder(new InMemoryChatMemory()).build();
+
+		RetrievalAugmentationAdvisor ragAdvisor = RetrievalAugmentationAdvisor.builder()
+			.queryTransformers(CompressionQueryTransformer.builder()
+				.chatClientBuilder(ChatClient.builder(this.openAiChatModel))
+				.build())
+			.documentRetriever(VectorStoreDocumentRetriever.builder().vectorStore(this.pgVectorStore).build())
+			.build();
+
+		ChatClient chatClient = ChatClient.builder(this.openAiChatModel)
+			.defaultAdvisors(memoryAdvisor, ragAdvisor)
+			.build();
+
+		String conversationId = "007";
+
+		ChatResponse chatResponse1 = chatClient.prompt()
+			.user("Where does the adventure of Anacletus and Birba take place?")
+			.advisors(advisors -> advisors.param(AbstractChatMemoryAdvisor.CHAT_MEMORY_CONVERSATION_ID_KEY,
+					conversationId))
+			.call()
+			.chatResponse();
+
+		assertThat(chatResponse1).isNotNull();
+		String response1 = chatResponse1.getResult().getOutput().getText();
+		System.out.println(response1);
+
+		ChatResponse chatResponse2 = chatClient.prompt()
+			.user("Did they meet any cow?")
+			.advisors(advisors -> advisors.param(AbstractChatMemoryAdvisor.CHAT_MEMORY_CONVERSATION_ID_KEY,
+					conversationId))
+			.call()
+			.chatResponse();
+
+		assertThat(chatResponse2).isNotNull();
+		String response2 = chatResponse2.getResult().getOutput().getText();
+		System.out.println(response2);
+		assertThat(response2.toLowerCase()).containsIgnoringCase("Fergus");
+	}
+
+	@Test
+	void ragWithRewrite() {
+		String question = "Where are the main characters going?";
+
+		RetrievalAugmentationAdvisor ragAdvisor = RetrievalAugmentationAdvisor.builder()
+			.queryTransformers(RewriteQueryTransformer.builder()
+				.chatClientBuilder(ChatClient.builder(this.openAiChatModel))
+				.targetSearchSystem("vector store")
+				.build())
+			.documentRetriever(VectorStoreDocumentRetriever.builder().vectorStore(this.pgVectorStore).build())
+			.build();
+
+		ChatResponse chatResponse = ChatClient.builder(this.openAiChatModel)
+			.build()
+			.prompt()
+			.user(question)
+			.advisors(ragAdvisor)
+			.call()
+			.chatResponse();
+
+		assertThat(chatResponse).isNotNull();
+
+		String response = chatResponse.getResult().getOutput().getText();
+		System.out.println(response);
+		assertThat(response).containsIgnoringCase("Loch of the Stars");
+
+		evaluateRelevancy(question, chatResponse);
+	}
+
 	@Test
 	void ragWithTranslation() {
 		String question = "Hvor finder Anacletus og Birbas eventyr sted?";