LangChain4j AiServices 实现聊天记忆

ChatMemory

上次说到ChatMessage手动的维护和管理是比较麻烦的，因此LangChain4j提出了ChatMemory的概念。它的本质是ChatMessage的容器。

可以看下ChatMemory这个接口的方法，它内部封装了一个List的ChatMessage。

要注意的是：

LLM的上下文窗口都是有一定限制的，针对不同的LLM可能限制的令牌数量有所不同，这意味着他们在任何给定时间可以处理的令牌数量都有上限，这可能会导致整个窗口对话超出限制。

每个令牌都有成本，所以每次调用LLM的成本会逐渐增加。

通过ChatMemory可以结合ApiServices组件可以实现聊天记忆功能。

以下是官方提供的几个示例：

简单的聊天记忆

package com.chatglm.demo;
import dev.langchain4j.memory.ChatMemory;
import dev.langchain4j.memory.chat.MessageWindowChatMemory;
import dev.langchain4j.model.openai.OpenAiChatModel;
import dev.langchain4j.service.AiServices;
/**
 * 聊天记忆
 */
public class ServiceWithMemoryExample {
    /**
     * 定义一个带有单个方法的接口
     */
    interface Assistant {
        String chat(String message);
    }
    public static void main(String[] args) {
        // 创建ChatLanguageModel组件作为AiServices的基础组件
        OpenAiChatModel openAiChatModel = OpenAiChatModel.withApiKey("demo");
        // 创建MessageWindowChatMemory充当滑动窗口
        ChatMemory chatMemory = MessageWindowChatMemory.withMaxMessages(10);
        // 利用Apiservices组件实现Assistant接口并接入chatMemory
        Assistant assistant = AiServices.builder(Assistant.class)
                .chatLanguageModel(openAiChatModel)
                .chatMemory(chatMemory)
                .build();
        String answer = assistant.chat("你好，我叫小A.");
        System.out.println(answer);
        String answerWithName = assistant.chat("我叫什么名字?");
        System.out.println(answerWithName); 
    }
}

AI回答：

多用户聊天记忆

package com.chatglm.demo;
import dev.langchain4j.memory.chat.MessageWindowChatMemory;
import dev.langchain4j.model.openai.OpenAiChatModel;
import dev.langchain4j.service.AiServices;
import dev.langchain4j.service.MemoryId;
import dev.langchain4j.service.UserMessage;
/**
 * 每个用户单独的聊天内存
 */
public class ServiceWithMemoryForEachUserExample {
    interface Assistant {
        String chat(@MemoryId int memoryId, @UserMessage String userMessage);
    }
    public static void main(String[] args) {
        Assistant assistant = AiServices.builder(Assistant.class)
                .chatLanguageModel(OpenAiChatModel.withApiKey(""))
                .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.
    }
}

聊天记忆持久化

依赖：

  org.mapdb mapdb 3.0.9   org.jetbrains.kotlin kotlin-stdlib

package com.chatglm.demo;
import dev.langchain4j.data.message.ChatMessage;
import dev.langchain4j.memory.ChatMemory;
import dev.langchain4j.memory.chat.MessageWindowChatMemory;
import dev.langchain4j.model.openai.OpenAiChatModel;
import dev.langchain4j.service.AiServices;
import dev.langchain4j.store.memory.chat.ChatMemoryStore;
import org.mapdb.DB;
import org.mapdb.DBMaker;
import java.util.List;
import java.util.Map;
import static dev.langchain4j.data.message.ChatMessageDeserializer.messagesFromJson;
import static dev.langchain4j.data.message.ChatMessageSerializer.messagesToJson;
import static org.mapdb.Serializer.STRING;
/**
 * 持久的聊天记忆
 */
public class ServiceWithPersistentMemoryExample {
    interface Assistant {
        String chat(String message);
    }
    public static void main(String[] args) {
        ChatMemory chatMemory = MessageWindowChatMemory.builder()
                .maxMessages(10)
                .chatMemoryStore(new PersistentChatMemoryStore())
                .build();
        Assistant assistant = AiServices.builder(Assistant.class)
                .chatLanguageModel(OpenAiChatModel.withApiKey("demo"))
                .chatMemory(chatMemory)
                .build();
        String answer = assistant.chat("你是什么智能");
        System.out.println(answer); // Hello Klaus! How can I assist you today?
        // Now, comment out the two lines above, uncomment the two lines below, and run again.
        // String answerWithName = assistant.chat("What is my name?");
        // System.out.println(answerWithName); // Your name is Klaus.
    }
    // You can create your own implementation of ChatMemoryStore and store chat memory whenever you'd like
    static class PersistentChatMemoryStore implements ChatMemoryStore {
        private final DB db = DBMaker.fileDB("chat-memory.db").transactionEnable().make();
        private final Map map = db.hashMap("messages", STRING, STRING).createOrOpen();
        @Override
        public List getMessages(Object memoryId) {
            String json = map.get((String) memoryId);
            return messagesFromJson(json);
        }
        @Override
        public void updateMessages(Object memoryId, List messages) {
            String json = messagesToJson(messages);
            map.put((String) memoryId, json);
            db.commit();
        }
        @Override
        public void deleteMessages(Object memoryId) {
            map.remove((String) memoryId);
            db.commit();
        }
    }
}

多用户聊天记忆持久化

package com.chatglm.demo;
import dev.langchain4j.data.message.ChatMessage;
import dev.langchain4j.memory.chat.ChatMemoryProvider;
import dev.langchain4j.memory.chat.MessageWindowChatMemory;
import dev.langchain4j.model.openai.OpenAiChatModel;
import dev.langchain4j.service.AiServices;
import dev.langchain4j.service.MemoryId;
import dev.langchain4j.service.UserMessage;
import dev.langchain4j.store.memory.chat.ChatMemoryStore;
import org.mapdb.DB;
import org.mapdb.DBMaker;
import java.util.List;
import java.util.Map;
import static dev.langchain4j.data.message.ChatMessageDeserializer.messagesFromJson;
import static dev.langchain4j.data.message.ChatMessageSerializer.messagesToJson;
import static org.mapdb.Serializer.INTEGER;
import static org.mapdb.Serializer.STRING;
/**
 * 每个用户持久的聊天记忆
 */
public class ServiceWithPersistentMemoryForEachUserExample {
    interface Assistant {
        String chat(@MemoryId int memoryId, @UserMessage String userMessage);
    }
    public static void main(String[] args) {
        PersistentChatMemoryStore store = new PersistentChatMemoryStore();
        ChatMemoryProvider chatMemoryProvider = memoryId -> MessageWindowChatMemory.builder()
                .id(memoryId)
                .maxMessages(10)
                .chatMemoryStore(store)
                .build();
        Assistant assistant = AiServices.builder(Assistant.class)
                .chatLanguageModel(OpenAiChatModel.withApiKey("demo"))
                .chatMemoryProvider(chatMemoryProvider)
                .build();
        System.out.println(assistant.chat(1, "Hello, my name is Klaus"));
        System.out.println(assistant.chat(2, "Hi, my name is Francine"));
        // Now, comment out the two lines above, uncomment the two lines below, and run again.
        // System.out.println(assistant.chat(1, "What is my name?"));
        // System.out.println(assistant.chat(2, "What is my name?"));
    }
    // You can create your own implementation of ChatMemoryStore and store chat memory whenever you'd like
    static class PersistentChatMemoryStore implements ChatMemoryStore {
        private final DB db = DBMaker.fileDB("multi-user-chat-memory.db").transactionEnable().make();
        private final Map map = db.hashMap("messages", INTEGER, STRING).createOrOpen();
        @Override
        public List getMessages(Object memoryId) {
            String json = map.get((int) memoryId);
            return messagesFromJson(json);
        }
        @Override
        public void updateMessages(Object memoryId, List messages) {
            String json = messagesToJson(messages);
            map.put((int) memoryId, json);
            db.commit();
        }
        @Override
        public void deleteMessages(Object memoryId) {
            map.remove((int) memoryId);
            db.commit();
        }
    }
}

分类:热门推荐日期:2024-06-15浏览:1评论:0

ChatMemory

简单的聊天记忆

多用户聊天记忆

聊天记忆持久化

多用户聊天记忆持久化

记忆 令牌

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