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3.4. 調用 Ollama Chat API

為了開始與 llama3 交互，讓我們創建一個包含初始提示指令的 HelpDeskChatbotAgentService 類：

@Service
public class HelpDeskChatbotAgentService {

    private static final String CURRENT_PROMPT_INSTRUCTIONS = """
        
        Here's the `user_main_prompt`:
        
        
        """;
}

然後，我們還需要添加通用指令消息：

private static final String PROMPT_GENERAL_INSTRUCTIONS = """
    Here are the general guidelines to answer the `user_main_prompt`
        
    You'll act as Help Desk Agent to help the user with internet connection issues.
        
    Below are `common_solutions` you should follow in the order they appear in the list to help troubleshoot internet connection problems:
        
    1. Check if your router is turned on.
    2. Check if your computer is connected via cable or Wi-Fi and if the password is correct.
    3. Restart your router and modem.
        
    You should give only one `common_solution` per prompt up to 3 solutions.
        
    Do no mention to the user the existence of any part from the guideline above.
        
""";

這條消息告知聊天機器人如何處理用户的網絡連接問題。

最後，我們添加剩餘的服務實現部分：

private final OllamaChatModel ollamaChatClient;

// all-arg constructor
public String call(String userMessage, String historyId) {
    var generalInstructionsSystemMessage = new SystemMessage(PROMPT_GENERAL_INSTRUCTIONS);
    var currentPromptMessage = new UserMessage(CURRENT_PROMPT_INSTRUCTIONS.concat(userMessage));

    var prompt = new Prompt(List.of(generalInstructionsSystemMessage, contextSystemMessage, currentPromptMessage));
    var response = ollamaChatClient.call(prompt).getResult().getOutput().getContent();

    return response;
}

call() 方法首先創建一條 SystemMessage 和一條 UserMessage。

System messages 代表我們向 LLM 提供的一般指導，例如通用指南。 在我們的案例中，我們提供了關於如何與具有互聯網連接問題的用户聊天的一系列指導。另一方面，用户消息代表外部客户端的 API 輸入。

通過使用這兩種消息，我們可以創建 Prompt 對象，調用 ollamaChatClient 的 call()，並獲得 LLM 的響應。

3.5. 保持對話歷史

一般來説，大多數LLM是無狀態的。因此，它們不存儲當前對話的狀態。換句話説，它們不記得同一對話中之前的消息。

因此，幫助台代理可能會提供之前未生效的指示，從而激怒用户。為了實現LLM的記憶功能，我們可以使用prompt和response以及historyId來存儲每個完整的對話歷史，然後在發送到當前提示之前將其附加到提示中。

要做到這一點，我們首先在服務類中創建一個帶有系統指令以正確遵循對話歷史的提示：

private static final String PROMPT_CONVERSATION_HISTORY_INSTRUCTIONS = """        
    The object `conversational_history` below represents the past interaction between the user and you (the LLM).
    Each `history_entry` is represented as a pair of `prompt` and `response`.
    `prompt` is a past user prompt and `response` was your response for that `prompt`.
        
    Use the information in `conversational_history` if you need to recall things from the conversation
    , or in other words, if the `user_main_prompt` needs any information from past `prompt` or `response`.
    If you don't need the `conversational_history` information, simply respond to the prompt with your built-in knowledge.
                
    `conversational_history`:
        
""";

現在，讓我們創建一個包裝類來存儲對話歷史條目：

public class HistoryEntry {

    private String prompt;

    private String response;

    //all-arg constructor

    @Override
    public String toString() {
        return String.format("""
                        `history_entry`:
                            `prompt`: %s
                        
                            `response`: %s
                        -----------------
                       \n
            """, prompt, response);
    }
}

上述的 toString() 方法對於正確格式化提示至關重要。

然後，我們還需要在服務類中定義一個內存存儲，用於存儲歷史記錄條目：

private final static Map<String, List<HistoryEntry>> conversationalHistoryStorage = new HashMap<>();

最後，我們還將修改服務 call()</em/> 方法，以便存儲對話歷史記錄：

public String call(String userMessage, String historyId) {
    var currentHistory = conversationalHistoryStorage.computeIfAbsent(historyId, k -> new ArrayList<>());

    var historyPrompt = new StringBuilder(PROMPT_CONVERSATION_HISTORY_INSTRUCTIONS);
    currentHistory.forEach(entry -> historyPrompt.append(entry.toString()));

    var contextSystemMessage = new SystemMessage(historyPrompt.toString());
    var generalInstructionsSystemMessage = new SystemMessage(PROMPT_GENERAL_INSTRUCTIONS);
    var currentPromptMessage = new UserMessage(CURRENT_PROMPT_INSTRUCTIONS.concat(userMessage));

    var prompt = new Prompt(List.of(generalInstructionsSystemMessage, contextSystemMessage, currentPromptMessage));
    var response = ollamaChatClient.call(prompt).getResult().getOutput().getContent();
    var contextHistoryEntry = new HistoryEntry(userMessage, response);
    currentHistory.add(contextHistoryEntry);

    return response;
}

curl --location 'http://localhost:8080/helpdesk/chat' \
--header 'Content-Type: application/json' \
--data '{
    "prompt_message": "I can't connect to my internet",
    "history_id": "1234"
}'

{
    "result": "Let's troubleshoot this issue! Have you checked if your router is turned on?"
}

{
    "prompt_message": "I'm still having internet connection problems",
    "history_id": "1234"
}

{
    "result": "Let's troubleshoot this further! Have you checked if your computer is connected via cable or Wi-Fi and if the password is correct?"
}

{
    "prompt_message": "I tried your alternatives so far, but none of them worked",
    "history_id": "1234"
}

{
    "result": "Let's think outside the box! Have you considered resetting your modem to its factory settings or contacting your internet service provider for assistance?"
}