Spring AI AWS Bedrock, persistent chat memory (jdbc and cassandra), and Spring AI's MessageChatMemoryAdvisor lead to 400 from Bedrock

Bug description Whenever using JDBC or Cassandra for persistent chat memory, if the "ASSISTANT" is the latest message in a conversation (defined by chatId), the call Bedrock receives is malformed and gives us a 400. A subsequent message to the same chat after the error then works just fine - this cycle continues.

This issue does NOT appear with the in-memory tooling or with the PromptChatMemoryAdvisor.

error logs: [dispatcherServlet] in context with path [] threw exception [Request processing failed: software.amazon.awssdk.services.bedrockruntime.model.ValidationException: A conversation must start with a user message. Try again with a conversation that starts with a user message. (Service: BedrockRuntime, Status Code: 400, Request ID: 17f8c248-ba1d-451a-862f-2595936bec1a)] with root cause...

Environment SpringAI 1.0.0-M7 Java 17 PostgreSQL and Cassadra DB (both running in Docker) AWS Bedrock with amazon.nova-lite-v1:0 as the converse model

Steps to reproduce With the above environment, set up persistent memory with the MessageChatMemoryAdvisor. Send your first message with a chatId. Send a second message to that chatId now that the "ASSISTANT" is logged for the latest message as the "type". Error should produce.

Expected behavior I would expect MessageChatMemoryAdvisor to adhere to Bedrock's contract of a message.

Minimal Complete Reproducible example

Controller:

@PostMapping
    public String chat( 
                        @RequestParam String userMessage,
                        @RequestParam String chatId) {
        return chatService.chatNonStreaming(userMessage, chatId);
    }

Service:

    public ChatService(ChatModel chatModel, VectorStore vectorStore, ChatMemory chatMemory) {
        this.chatClient = ChatClient.builder(chatModel)
                .defaultSystem("""
                You are a support agent for a user. Respond in a friendly, helpful, and joyful manner.
            """)
                .defaultAdvisors(
                        new PromptChatMemoryAdvisor(chatMemory),
                        new QuestionAnswerAdvisor(vectorStore),
                        new SimpleLoggerAdvisor()
                )
                .build();
    }

      public String chatNonStreaming(String userMessage, String chatId) {
          ChatResponse response = this.chatClient.prompt()
                  .user(userMessage)
                  .advisors(a -> a
                          .param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                          .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 100))
                  .call()
                  .chatResponse();

          return response.getResult().getOutput().getText();
    }

build.gradle:

ext {
    set('springAiVersion', "1.0.0-M7")
}

dependencies {
    // AI
    implementation 'org.springframework.ai:spring-ai-starter-model-bedrock'
    implementation 'org.springframework.ai:spring-ai-starter-model-bedrock-converse'
    implementation 'org.springframework.ai:spring-ai-starter-vector-store-pgvector'
    implementation 'org.springframework.ai:spring-ai-advisors-vector-store'
    implementation 'org.springframework.ai:spring-ai-starter-model-chat-memory-jdbc'

    // AWS
    implementation platform("io.awspring.cloud:spring-cloud-aws-dependencies:3.3.0")

    // Spring Integration
    implementation 'org.springframework.integration:spring-integration-core'
    implementation("org.springframework.integration:spring-integration-aws:3.0.9")

    // web
    implementation 'org.springframework.boot:spring-boot-starter-web'
}

dependencyManagement {
    imports {
        mavenBom "org.springframework.ai:spring-ai-bom:${springAiVersion}"
    }
}

application.yml:

logging:
  level:
    org:
      springframework:
        ai:
          chat:
            client:
              advisor: DEBUG
spring:
  application:
    name: ${NAME}
  ai:
    bedrock:
      aws:
        region: us-east-1
        access-key: ${ACCESS_KEY}
        secret-key: ${SECRET_KEY}
      converse:
        chat:
          options:
            model: amazon.nova-lite-v1:0
  datasource:
    url: jdbc: ${DATABASE_URL}
    username: ${DATABASE_USERNAME}
    password: ${DATABASE_PASSWORD}

server:
  port: 8080