Fix MessageChatMemoryAdvisor in streaming case.

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/client/advisor/MessageChatMemoryAdvisorIT.java

@@ -138,4 +138,56 @@ void shouldHandleNonExistentConversation() {
 		testHandleNonExistentConversation();
 	}
 
+	@Test
+	void shouldStoreCompleteContentInStreamingMode() {
+		// Arrange
+		String conversationId = "streaming-test-" + System.currentTimeMillis();
+		ChatMemory chatMemory = MessageWindowChatMemory.builder()
+			.chatMemoryRepository(new InMemoryChatMemoryRepository())
+			.build();
+
+		// Create MessageChatMemoryAdvisor with the conversation ID
+		MessageChatMemoryAdvisor advisor = MessageChatMemoryAdvisor.builder(chatMemory)
+			.conversationId(conversationId)
+			.build();
+
+		ChatClient chatClient = ChatClient.builder(chatModel).defaultAdvisors(advisor).build();
+
+		// Act - Use streaming API
+		String userInput = "Tell me a short joke about programming";
+
+		// Collect the streaming responses
+		List<String> streamedResponses = new ArrayList<>();
+		chatClient.prompt()
+			.user(userInput)
+			.advisors(a -> a.param(ChatMemory.CONVERSATION_ID, conversationId))
+			.stream()
+			.content()
+			.collectList()
+			.block();
+
+		// Wait a moment to ensure all processing is complete
+		try {
+			Thread.sleep(500);
+		}
+		catch (InterruptedException e) {
+			Thread.currentThread().interrupt();
+		}
+
+		// Assert - Check that the memory contains the complete content
+		List<Message> memoryMessages = chatMemory.get(conversationId);
+
+		// Should have at least 2 messages (user + assistant)
+		assertThat(memoryMessages).hasSizeGreaterThanOrEqualTo(2);
+
+		// First message should be the user message
+		assertThat(memoryMessages.get(0).getText()).isEqualTo(userInput);
+
+		// Last message should be the assistant's response and should have content
+		Message assistantMessage = memoryMessages.get(memoryMessages.size() - 1);
+		assertThat(assistantMessage.getText()).isNotEmpty();
+
+		logger.info("Assistant response stored in memory: {}", assistantMessage.getText());
+	}
+
 }

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

@@ -20,14 +20,18 @@
 import java.util.List;
 
 import org.springframework.util.Assert;
+import reactor.core.publisher.Flux;
+import reactor.core.publisher.Mono;
 import reactor.core.scheduler.Scheduler;
 
+import org.springframework.ai.chat.client.ChatClientMessageAggregator;
 import org.springframework.ai.chat.client.ChatClientRequest;
 import org.springframework.ai.chat.client.ChatClientResponse;
 import org.springframework.ai.chat.client.advisor.api.Advisor;
 import org.springframework.ai.chat.client.advisor.api.AdvisorChain;
 import org.springframework.ai.chat.client.advisor.api.BaseAdvisor;
 import org.springframework.ai.chat.client.advisor.api.BaseChatMemoryAdvisor;
+import org.springframework.ai.chat.client.advisor.api.StreamAdvisorChain;
 import org.springframework.ai.chat.memory.ChatMemory;
 import org.springframework.ai.chat.messages.Message;
 import org.springframework.ai.chat.messages.UserMessage;
@@ -109,6 +113,21 @@ public ChatClientResponse after(ChatClientResponse chatClientResponse, AdvisorCh
 		return chatClientResponse;
 	}
 
+	@Override
+	public Flux<ChatClientResponse> adviseStream(ChatClientRequest chatClientRequest,
+			StreamAdvisorChain streamAdvisorChain) {
+		// Get the scheduler from BaseAdvisor
+		Scheduler scheduler = this.getScheduler();
+
+		// Process the request with the before method
+		return Mono.just(chatClientRequest)
+			.publishOn(scheduler)
+			.map(request -> this.before(request, streamAdvisorChain))
+			.flatMapMany(streamAdvisorChain::nextStream)
+			.transform(flux -> new ChatClientMessageAggregator().aggregateChatClientResponse(flux,
+					response -> this.after(response, streamAdvisorChain)));
+	}
+
 	public static Builder builder(ChatMemory chatMemory) {
 		return new Builder(chatMemory);
 	}