Langchain4j笔记
模型配置
模型使用阿里的千问，可免费使用一定额度
在Spring Boot配置文件中：
langchain4j.community.dashscope.api-key=sk-* 你的API KEY
langchain4j.community.dashscope.model-name=qwen-max
依赖：
<dependency>
<groupId>dev.langchain4j</groupId>
<artifactId>langchain4j-community-dashscope-spring-boot-starter</artifactId>
<version>1.0.0-beta3</version>
</dependency>
<dependency>
<groupId>dev.langchain4j</groupId>
<artifactId>langchain4j-spring-boot-starter</artifactId>
<version>1.0.0-beta3</version>
</dependency>先简单写个config
@Configuration
public class LangChainConfig {
@Value("${langchain4j.community.dashscope.api-key}")
private String apiKey;
@Bean
public ChatLanguageModel chatLanguageModel() {
return QwenChatModel.builder()
.apiKey(apiKey)
.modelName("qwen-max")
.build();
}
}这样就创建好模型了！
也可以直接在配置文件里写
ChatLanguageModel测试
@Autowired
ChatLanguageModel chatLanguageModel;
@Test
void testLowLevel() {
String res = chatLanguageModel.chat("Hello, What's your name?");
System.out.println(res);
}@AiService
可以自动注入ChatLanguageModel（前提是把第二个chat方法给注释掉）
@AiService
public interface Assistant {
String chat(String userMessage);
String chat(@MemoryId int memoryId, @UserMessage String userMessage);
} @Autowired
Assistant assistant;
@Test
void testAssistant() {
String res = assistant.chat("Hello, what is your name");
System.out.println(res);
// Hello! I'm Qwen, an AI assistant created by Alibaba Cloud. It's nice to meet you. How can I assist you today?
}记忆功能
这是第一种比较麻烦的，也就是把所有的请求和回复都加到下一次请求中
@Test
public void testModel() {
UserMessage firstUserMessage = UserMessage.from("Hello, my name is Klaus");
AiMessage firstAiMessage = chatLanguageModel.chat(firstUserMessage).aiMessage(); // Hi Klaus, how can I help you?
System.out.println(firstAiMessage.text());
UserMessage secondUserMessage = UserMessage.from("What is my name?");
AiMessage secondAiMessage = chatLanguageModel.chat(firstUserMessage, firstAiMessage, secondUserMessage).aiMessage(); // Klaus
System.out.println(secondAiMessage.text());
}第二种使用chatMemory，可以看到我们在这里重新builder了assistant
@Test
void testMemory() {
ChatMemory chatMemory = MessageWindowChatMemory.withMaxMessages(10);
Assistant assistant = AiServices.builder(Assistant.class)
.chatLanguageModel(chatLanguageModel)
.chatMemory(chatMemory)
.build();
String answer = assistant.chat("Hello! My name is Klaus.");
System.out.println(answer); // Hello Klaus! How can I assist you today?
String answerWithName = assistant.chat("What is my name?");
System.out.println(answerWithName); // Your name is Klaus.
}如果我们不想让memory共享呢，就可以指定id，一个id只能看到自己id内的memory
@Test
void testSelfMemory() {
Assistant assistant = AiServices.builder(Assistant.class)
.chatLanguageModel(chatLanguageModel)
.chatMemoryProvider(memoryId -> MessageWindowChatMemory.withMaxMessages(10))
.build();
System.out.println(assistant.chat(1, "Hello, my name is Klaus"));
// Hi Klaus! How can I assist you today?
System.out.println(assistant.chat(2, "Hello, my name is Francine"));
// Hello Francine! How can I assist you today?
System.out.println(assistant.chat(1, "What is my name?"));
// Your name is Klaus.
System.out.println(assistant.chat(2, "What is my name?"));
// Your name is Francine.
}