实现提示 (Dialogflow)

查看以下提示，实施良好的对话设计做法 添加到“操作”中

预期变化

在“用户说”中处理此问题在 Dialogflow 中输入。此外，请使用多个 可映射到同一操作的 intent，其中每个 intent 都可以通过 一组不同的“用户说”词组。

提供有用的提示，并优雅地失败

有时，您的 Action 会因未收到输入而无法继续前进 （称为非输入）或无法识别用户的输入（称为非匹配）。 当发生这种情况时，Google 助理会先尝试确定用户是否需要 来触发其他 Action。如果 Google 助理与用户输入的内容不符 另一个 Action 时，用户可在该 Action 的上下文中继续。 这种情况随时都可能发生，因此最佳做法是 对话中每个回合都出现 no-input 和 no-match 的情况。 使用后备选项，您可以帮助用户回到正轨。

为此，请在 conv.data 对象中初始化 fallbackCount 变量， 并将其设为 0。准备一组包含两个后备提示（为清晰起见而上报）， 以及结束对话的最后后备提示。

然后，创建一个后备意图（最好为 代理）。在 intent 处理程序中，从 conv.data 中提取回退计数 递增它；如果小于 3，则从数组中提取提示。 （总分 3）。如果计数为 4 或更多，请使用最后一个 提示。在所有不是回退 intent 的 intent 中，请将回退计数重置为 0。 理想情况下，应针对特定 intent 设置回退的模板。

Node.js

const GENERAL_FALLBACK = [
   'Sorry, what was that?',
   'I didn\'t quite get that. I can help you find good local restaurants, what do you want to know about?',
];

const LIST_FALLBACK = [
   'Sorry, what was that?',
   'I didn\'t catch that. Could you tell me which one you prefer?',
];

const FINAL_FALLBACK = 'I\'m sorry I\'m having trouble here. Let\'s talk again later.';

const handleFallback = (conv, promptFetch, callback) => {
 conv.data.fallbackCount = parseInt(conv.data.fallbackCount, 10);
 conv.data.fallbackCount++;
 if (conv.data.fallbackCount > 2) {
   conv.close(promptFetch.getFinalFallbackPrompt());
 } else {
   callback();
 }
}
// Intent handlers below
const generalFallback = (conv) => {
  handleFallback = (conv, promptFetch, () => {
    conv.ask(GENERAL_FALLBACK[conv.data.fallbackCount],
      getGeneralNoInputPrompts());
 });
}

const listFallback = (conv) => {
  handleFallback = (conv, promptFetch, () => {
   conv.ask(LIST_FALLBACK[conv.data.fallbackCount],
       getGeneralNoInputPrompts());
 });
}

const nonFallback = (conv) => {
  conv.data.fallbackCount = 0;
  conv.ask('A non-fallback message here');
}

Java

private static final List<String> GENERAL_FALLBACK =
    Arrays.asList(
        "Sorry, what was that?",
        "I didn\'t quite get that. I can tell you all about IO, like date or location, or about the sessions. What do you want to know about?");
private static final List<String> LIST_FALLBACK =
    Arrays.asList(
        "Sorry, what was that?",
        "I didn\'t catch that. Could you tell me which one you liked?");
private static final List<String> FINAL_FALLBACK =
    Arrays.asList("I\'m sorry I\'m having trouble here. Maybe we should try this again later.");

@ForIntent("General Fallback")
public ActionResponse generalFallback(ActionRequest request) {
  ResponseBuilder responseBuilder = getResponseBuilder(request);
  int fallbackCount = (Integer) request.getConversationData().get("fallbackCount");
  fallbackCount++;
  request.getConversationData().put("fallbackCount", fallbackCount);
  if (fallbackCount > 2) {
    responseBuilder.add(getRandomPromptFromList(FINAL_FALLBACK)).endConversation();
  } else {
    responseBuilder.add(getRandomPromptFromList(GENERAL_FALLBACK));
  }
  return responseBuilder.build();
}

private String getRandomPromptFromList(List<String> prompts) {
  Random rand = new Random();
  int i = rand.nextInt(prompts.size());
  return prompts.get(i);
}

@ForIntent("List Fallback")
public ActionResponse listFallback(ActionRequest request) {
  ResponseBuilder responseBuilder = getResponseBuilder(request);
  int fallbackCount = (Integer) request.getConversationData().get("fallbackCount");
  fallbackCount++;
  request.getConversationData().put("fallbackCount", fallbackCount);
  if (fallbackCount > 2) {
    responseBuilder.add(getRandomPromptFromList(FINAL_FALLBACK)).endConversation();
  } else {
    responseBuilder.add(getRandomPromptFromList(LIST_FALLBACK));
  }
  return responseBuilder.build();
}

@ForIntent("Non Fallback")
public ActionResponse nonFallback(ActionRequest request) {
  ResponseBuilder responseBuilder = getResponseBuilder(request);
  request.getConversationData().put("fallbackCount", 0);
  responseBuilder.add("Non Fallback message");
  return responseBuilder.build();
}

随时准备为您提供帮助

创建一个意图来监听“我可以做什么？”等帮助短语、 “你能告诉我什么”或“帮助”。在此 intent 中，提供一些（轮播） 简要介绍代理可以执行的操作，并将用户定向到 可能的操作。理想情况下，您还可以在 Dialogflow 中使用后续帮助 intent， 为不同的可操作的 intent 创建不同的帮助场景。

Node.js

const HELP_PROMPTS = [
   'There\'s a lot you might want to know about the local restaurants, and I can tell you all about it, like where it is and what kind of food they have. What do you want to know?',
   'I\'m here to help, so let me know if you need any help figuring out where or what to eat. What do you want to know?',
];

// Intent handler
const help = (conv) => {
 reply(conv, promptFetch.getHelpPrompt(), // fetches random entry from HELP_PROMPTS
     promptFetch.getGeneralNoInputPrompts());
}

Java

private static final List<String> HELP_PROMPTS =
    Arrays.asList(
        "There's a lot you might want to know about IO, and I can tell you all about it, like where it is and what the sessions are. What do you want to know?",
        "IO can be a little overwhelming, so I\'m here to help. Let me know if you need any help figuring out the event, like when it is, or what the sessions are. What do you want to know?");

@ForIntent("Help")
public ActionResponse help(ActionRequest request) {
  return getResponseBuilder(request).add(getRandomPromptFromList(HELP_PROMPTS)).build();
}

允许用户重放信息

使用代理函数封装所有 app.ask(output) 方法，该函数会将 输出到 conv.data.lastPrompt。创建一个用于监听的重复 intent 例如“什么？”“再说一遍”或“你能不能” 重复一下？”创建一个重复前缀数组，该前缀可用于 确认用户要求重复某些内容。重复中 intent 处理程序，使用重复前缀和ask() conv.data.lastPrompt 的值。请注意 SSML 起始标记（如果在上一个提示中使用）。

Node.js

const REPEAT_PREFIX = [
    'Sorry, I said ',
    'Let me repeat that. ',
];

const reply = (conv, inputPrompt, noInputPrompts) => {
  conv.data.lastPrompt = inputPrompt;
  conv.data.lastNoInputPrompts = noInputPrompts;
  conv.ask(inputPrompt, noInputPrompts);
}
// Intent handlers
const normalIntent = (conv) => {
  reply(conv, 'Hey this is a question', SOME_NO_INPUT_PROMPTS);
}

const repeat = (conv) => {
  let repeatPrefix = promptFetch.getRepeatPrefix(); // randomly chooses from REPEAT_PREFIX
  // Move SSML start tags over
  if (conv.data.lastPrompt.startsWith(promptFetch.getSSMLPrefix())) {
    conv.data.lastPrompt =
        conv.data.lastPrompt.slice(promptFetch.getSSMLPrefix().length);
    repeatPrefix = promptFetch.getSSMLPrefix() + repeatPrefix;
  }
  conv.ask(repeatPrefix + conv.data.lastPrompt,
      conv.data.lastNoInputPrompts);
}

Java

private final List<String> REPEAT_PREFIX = Arrays.asList("Sorry, I said ", "Let me repeat that.");

private final String SsmlPrefix = "<speak>";

@ForIntent("Normal Intent")
public ActionResponse normalIntent(ActionRequest request) {
  ResponseBuilder responseBuilder = getResponseBuilder(request);
  responseBuilder.getConversationData().put("lastPrompt", "Hey this is a question");
  return responseBuilder.build();
}

@ForIntent("repeat")
public ActionResponse repeat(ActionRequest request) {
  ResponseBuilder responseBuilder = getResponseBuilder(request);
  String repeatPrefix = getRandomPromptFromList(REPEAT_PREFIX);
  // Move SSML start tags over
  String lastPrompt = (String) responseBuilder.getConversationData().get("lastPrompt");
  if (lastPrompt.startsWith(SsmlPrefix)) {
    String newLastPrompt = lastPrompt.substring(SsmlPrefix.length());
    responseBuilder.getConversationData().put("lastPrompt", newLastPrompt);
    repeatPrefix = SsmlPrefix + repeatPrefix;
  }
  responseBuilder.add(repeatPrefix + lastPrompt);
  return responseBuilder.build();
}

根据用户偏好打造个性化对话体验

你的 Action 可以询问用户的偏好，并记住他们的偏好。 这样，您以后与该用户的对话就会个性化。

此示例 Action 为用户提供邮政编码的天气预报。以下 示例代码询问用户是否希望操作记住他们的邮政编码 供后续对话使用。

Node.js

app.intent('weather_report', (conv) => {
  let zip = conv.arguments.get('zipcode');
  conv.data.zip = zip;
  conv.ask(getWeatherReport(zip));
  conv.ask(new Confirmation(`Should I remember ${zip} for next time?`));
});

app.intent('remember_zip', (conv, params, confirmation) => {
  if (confirmation) {
    conv.user.storage.zip = conv.data.zip;
    conv.close('Great! See you next time.');
  } else conv.close('Ok, no problem.');
});

Java

@ForIntent("weather_report")
public ActionResponse weatherReport(ActionRequest request) {
  ResponseBuilder responseBuilder = getResponseBuilder(request);
  String zip = (String) request.getArgument("location").getStructuredValue().get("zipCode");
  responseBuilder.getConversationData().put("zip", zip);
  responseBuilder.add(getWeatherReport(zip));
  responseBuilder.add(
      new Confirmation().setConfirmationText("Should I remember " + zip + " for next time?"));
  return responseBuilder.build();
}

@ForIntent("remember_zip")
public ActionResponse rememberZip(ActionRequest request) {
  ResponseBuilder responseBuilder = getResponseBuilder(request);
  if (request.getUserConfirmation()) {
    responseBuilder.getUserStorage().put("zip", responseBuilder.getConversationData().get("zip"));
    responseBuilder.add("Great! See you next time.").endConversation();
  } else {
    responseBuilder.add("Ok, no problem.").endConversation();
  }
  return responseBuilder.build();
}

在第一次对话时询问用户所在地的邮政编码， 可以在下一次调用时跳过该提示，并使用相同的邮政编码。 您仍应提供逃生路线（例如，允许投屏的建议内容信息条） 来另选一个邮政编码）但减少整个区域范围内 就能打造更加顺畅的体验

Node.js

app.intent('weather_report', (conv) => {
  let zip = conv.arguments.get('zipcode');
  if (zip) {
    conv.close(getWeatherReport(zip));
  } else if (conv.user.storage.zip) {
    conv.ask(new SimpleResponse(getWeatherReport(conv.user.storage.zip)));
    conv.ask(new Suggestions('Try another zipcode'));
  } else {
    conv.ask('What\'s your zip code?');
  }
});

app.intent('provide_zip_df', (conv) => {
  conv.user.storage.zip = conv.arguments.get('zipcode');
  conv.close(getWeatherReport(conv.user.storage.zip));
});

Java

public ActionResponse weatherReport2(ActionRequest request) {
  ResponseBuilder responseBuilder = getResponseBuilder(request);
  String zip = (String) request.getArgument("location").getStructuredValue().get("zipCode");
  if (zip != null) {
    responseBuilder.add(getWeatherReport(zip)).endConversation();
  } else if ((zip = (String) responseBuilder.getUserStorage().get("zip")) != null) {
    responseBuilder.add(new SimpleResponse().setTextToSpeech(getWeatherReport(zip)));
    responseBuilder.add(new Suggestion().setTitle("Try another zipcode"));
  } else {
    responseBuilder.add("What's your zip code?");
  }
  return responseBuilder.build();
}

针对回访用户进行自定义

在对话之间保持某种状态可确保对话更自然 提升回访用户的体验打造这种体验的第一步是 以不同的方式问候回访用户。例如，您可以缩小问候语或 根据以往的对话展示有用信息。为此，请使用 传入的 AppRequest.User lastSeen 属性，用于确定用户是否 之前与您的 Action 有过互动的情况。如果包含 lastSeen 属性 请求载荷中，您可以使用与往常不同的问候语。

以下代码使用 Node.js 客户端库获取 last.seen。

Node.js

// This function is used to handle the welcome intent
// In Dialogflow, the Default Welcome Intent ('input.welcome' action)
// In Actions SDK, the 'actions.intent.MAIN' intent
const welcome = (conv) => {
  if (conv.user.last.seen) {
    conv.ask(`Hey you're back...`);
  } else {
    conv.ask('Welcome to World Cities Trivia!...');
  }
}

Java

// This function is used to handle the welcome intent
// In Dialogflow, the Default Welcome Intent ('input.welcome' action)
// In Actions SDK, the 'actions.intent.MAIN' intent
public ActionResponse welcome(ActionRequest request) {
  ResponseBuilder responseBuilder = getResponseBuilder(request);
  if (request.getUser().getLastSeen() != null) {
    responseBuilder.add("Hey you're back...");
  } else {
    responseBuilder.add("Welcome to Number Genie!...");
  }
  return responseBuilder.build();
}

您可以根据实际的问候语定制响应， 的值为 lastSeen。例如，最后一次互动发生多次的用户 在前一天使用了该 Action 的用户。

对话音量控制

在受支持的设备上，用户可以通过 Google 助理控制设备音量 “调高音量”或“调高音量”等指令 音量调高到百分之 50”。如果您有用于处理相似训练短语的意图， intent 优先。建议让 Google 助理来处理这些问题 用户请求，除非您的 Action 有特定理由。