Skapa egna uppmaningar för att samla in användarindata
Artikel
GÄLLER FÖR: SDK v4
En konversation mellan en robot och en användare handlar ofta om att be (fråga) användaren om information, parsa användarens svar och sedan agera på den informationen. Roboten bör spåra kontexten för en konversation så att den kan hantera sitt beteende och komma ihåg svar på tidigare frågor. En robots tillstånd är information som den spårar för att svara korrekt på inkommande meddelanden.
Bot Framework JavaScript-, C#- och Python-SDK:erna fortsätter att stödjas, men Java SDK dras tillbaka med slutligt långsiktigt stöd som slutar i november 2023.
Befintliga robotar som skapats med Java SDK fortsätter att fungera.
Exempelroboten ställer en rad frågor till användaren, validerar några av deras svar och sparar indata. Följande diagram visar relationen mellan roboten, användarprofilen och konversationsflödesklasserna.
En UserProfile klass för den användarinformation som roboten samlar in.
En ConversationFlow klass som styr vårt konversationstillstånd när du samlar in användarinformation.
En inre ConversationFlow.Question uppräkning för att spåra var du befinner dig i konversationen.
En userProfile klass för den användarinformation som roboten samlar in.
En conversationFlow klass som styr vårt konversationstillstånd när du samlar in användarinformation.
En inre conversationFlow.question uppräkning för att spåra var du befinner dig i konversationen.
En UserProfile klass för den användarinformation som roboten samlar in.
En ConversationFlow klass som styr vårt konversationstillstånd när du samlar in användarinformation.
En inre ConversationFlow.Question uppräkning för att spåra var du befinner dig i konversationen.
En UserProfile klass för den användarinformation som roboten samlar in.
En ConversationFlow klass som styr vårt konversationstillstånd när du samlar in användarinformation.
En inre ConversationFlow.Question uppräkning för att spåra var du befinner dig i konversationen.
Användartillståndet spårar användarens namn, ålder och valda datum, och konversationstillståndet spårar det du senast bad användaren om.
Eftersom du inte planerar att distribuera den här roboten konfigurerar du användar- och konversationstillstånd för att använda minneslagring.
Du använder robotens meddelandevändarhanterare plus egenskaper för användar- och konversationstillstånd för att hantera konversationsflödet och insamlingen av indata. I roboten registrerar du informationen om tillståndsegenskapen som tas emot under varje iteration av meddelandevändarhanteraren.
Skapa användar- och konversationstillståndsobjekt vid start och använd dem via beroendeinmatning i robotkonstruktorn.
Startup.cs
// Create the Bot Adapter with error handling enabled.
services.AddSingleton<IBotFrameworkHttpAdapter, AdapterWithErrorHandler>();
// Create the storage we'll be using for User and Conversation state. (Memory is great for testing purposes.)
services.AddSingleton<IStorage, MemoryStorage>();
// Create the User state.
services.AddSingleton<UserState>();
// Create the Conversation state.
services.AddSingleton<ConversationState>();
Skapa användar- och konversationstillståndsobjekt i index.js och använd dem i robotkonstruktorn.
index.js
// Catch-all for errors.
adapter.onTurnError = async (context, error) => {
// This check writes out errors to console log .vs. app insights.
// NOTE: In production environment, you should consider logging this to Azure
robotar/customPromptBot.js
class CustomPromptBot extends ActivityHandler {
constructor(conversationState, userState) {
super();
// The state management objects for the conversation and user.
this.conversationState = conversationState;
this.userState = userState;
Konstruera CustomPromptBot i metoden getBot med hjälp av instanserna ConversationState och UserState som tillhandahålls av Spring-containern. Konstruktorn för CustomPromptBot lagrar referenser till ConversationState och UserState som tillhandahölls under starten.
Application.java
@Bean
public Bot getBot(
ConversationState conversationState,
UserState userState
) {
return new CustomPromptBot(conversationState, userState);
}
CustomPromptBot.java
private final BotState userState;
private final BotState conversationState;
public CustomPromptBot(ConversationState conversationState, UserState userState) {
this.conversationState = conversationState;
this.userState = userState;
Skapa användar- och konversationstillståndsobjekt i app.py och använd dem i robotkonstruktorn.
app.py
CONVERSATION_STATE = ConversationState(MEMORY)
# Create Bot
BOT = CustomPromptBot(CONVERSATION_STATE, USER_STATE)
# Listen for incoming requests on /api/messages.
robotar/custom_prompt_bot.py
class CustomPromptBot(ActivityHandler):
def __init__(self, conversation_state: ConversationState, user_state: UserState):
if conversation_state is None:
raise TypeError(
"[CustomPromptBot]: Missing parameter. conversation_state is required but None was given"
)
if user_state is None:
raise TypeError(
"[CustomPromptBot]: Missing parameter. user_state is required but None was given"
)
self.conversation_state = conversation_state
self.user_state = user_state
Skapa egenskapsåtkomster för egenskaper för användarprofil och konversationsflöde och anropa GetAsync sedan för att hämta egenskapsvärdet från tillstånd.
Robotar/CustomPromptBot.cs
protected override async Task OnMessageActivityAsync(ITurnContext<IMessageActivity> turnContext, CancellationToken cancellationToken)
{
var conversationStateAccessors = _conversationState.CreateProperty<ConversationFlow>(nameof(ConversationFlow));
var flow = await conversationStateAccessors.GetAsync(turnContext, () => new ConversationFlow(), cancellationToken);
var userStateAccessors = _userState.CreateProperty<UserProfile>(nameof(UserProfile));
var profile = await userStateAccessors.GetAsync(turnContext, () => new UserProfile(), cancellationToken);
Innan svängen slutar anropar du SaveChangesAsync för att skriva tillståndsändringar i lagringen.
Innan svängen slutar anropar du saveChanges för att skriva tillståndsändringar i lagringen.
/**
* Override the ActivityHandler.run() method to save state changes after the bot logic completes.
*/
async run(context) {
await super.run(context);
// Save any state changes. The load happened during the execution of the Dialog.
await this.conversationState.saveChanges(context, false);
await this.userState.saveChanges(context, false);
}
Skapa egenskapsåtkomster för egenskaper för användarprofil och konversationsflöde och anropa get sedan för att hämta egenskapsvärdet från tillstånd.
I konstruktorn skapar du tillståndsegenskapsåtkomsterna och konfigurerar tillståndshanteringsobjekten (skapade ovan) för vår konversation.
robotar/custom_prompt_bot.py
async def on_message_activity(self, turn_context: TurnContext):
# Get the state properties from the turn context.
profile = await self.profile_accessor.get(turn_context, UserProfile)
flow = await self.flow_accessor.get(turn_context, ConversationFlow)
Innan svängen slutar anropar du SaveChangesAsync för att skriva tillståndsändringar i lagringen.
# Save changes to UserState and ConversationState
await self.conversation_state.save_changes(turn_context)
await self.user_state.save_changes(turn_context)
Meddelandevändarhanterare
När du hanterar meddelandeaktiviteter använder meddelandehanteraren en hjälpmetod för att hantera konversationen och fråga användaren. Hjälpmetoden beskrivs i följande avsnitt.
async def on_message_activity(self, turn_context: TurnContext):
# Get the state properties from the turn context.
profile = await self.profile_accessor.get(turn_context, UserProfile)
flow = await self.flow_accessor.get(turn_context, ConversationFlow)
await self._fill_out_user_profile(flow, profile, turn_context)
# Save changes to UserState and ConversationState
await self.conversation_state.save_changes(turn_context)
await self.user_state.save_changes(turn_context)
Fylla i användarprofilen
Roboten uppmanar användaren att ange information baserat på vilken fråga, om någon, som roboten ställde i föregående tur. Indata parsas med hjälp av en valideringsmetod.
Varje valideringsmetod följer en liknande design:
Returvärdet anger om indata är ett giltigt svar för den här frågan.
Om valideringen godkänns genererar den ett parsat och normaliserat värde att spara.
Om verifieringen misslyckas skapar den ett meddelande som roboten kan be om informationen med igen.
{
var input = turnContext.Activity.Text?.Trim();
string message;
switch (flow.LastQuestionAsked)
{
case ConversationFlow.Question.None:
await turnContext.SendActivityAsync("Let's get started. What is your name?", null, null, cancellationToken);
flow.LastQuestionAsked = ConversationFlow.Question.Name;
break;
case ConversationFlow.Question.Name:
if (ValidateName(input, out var name, out message))
{
profile.Name = name;
await turnContext.SendActivityAsync($"Hi {profile.Name}.", null, null, cancellationToken);
await turnContext.SendActivityAsync("How old are you?", null, null, cancellationToken);
flow.LastQuestionAsked = ConversationFlow.Question.Age;
break;
}
else
{
await turnContext.SendActivityAsync(message ?? "I'm sorry, I didn't understand that.", null, null, cancellationToken);
break;
}
case ConversationFlow.Question.Age:
if (ValidateAge(input, out var age, out message))
{
profile.Age = age;
await turnContext.SendActivityAsync($"I have your age as {profile.Age}.", null, null, cancellationToken);
await turnContext.SendActivityAsync("When is your flight?", null, null, cancellationToken);
flow.LastQuestionAsked = ConversationFlow.Question.Date;
break;
}
else
{
await turnContext.SendActivityAsync(message ?? "I'm sorry, I didn't understand that.", null, null, cancellationToken);
break;
}
case ConversationFlow.Question.Date:
if (ValidateDate(input, out var date, out message))
{
profile.Date = date;
await turnContext.SendActivityAsync($"Your cab ride to the airport is scheduled for {profile.Date}.");
await turnContext.SendActivityAsync($"Thanks for completing the booking {profile.Name}.");
await turnContext.SendActivityAsync($"Type anything to run the bot again.");
flow.LastQuestionAsked = ConversationFlow.Question.None;
profile = new UserProfile();
break;
}
else
{
await turnContext.SendActivityAsync(message ?? "I'm sorry, I didn't understand that.", null, null, cancellationToken);
break;
}
}
}
robotar/customPromptBot.js
// Manages the conversation flow for filling out the user's profile.
static async fillOutUserProfile(flow, profile, turnContext) {
const input = turnContext.activity.text;
let result;
switch (flow.lastQuestionAsked) {
// If we're just starting off, we haven't asked the user for any information yet.
// Ask the user for their name and update the conversation flag.
case question.none:
await turnContext.sendActivity("Let's get started. What is your name?");
flow.lastQuestionAsked = question.name;
break;
// If we last asked for their name, record their response, confirm that we got it.
// Ask them for their age and update the conversation flag.
case question.name:
result = this.validateName(input);
if (result.success) {
profile.name = result.name;
await turnContext.sendActivity(`I have your name as ${ profile.name }.`);
await turnContext.sendActivity('How old are you?');
flow.lastQuestionAsked = question.age;
break;
} else {
// If we couldn't interpret their input, ask them for it again.
// Don't update the conversation flag, so that we repeat this step.
await turnContext.sendActivity(result.message || "I'm sorry, I didn't understand that.");
break;
}
// If we last asked for their age, record their response, confirm that we got it.
// Ask them for their date preference and update the conversation flag.
case question.age:
result = this.validateAge(input);
if (result.success) {
profile.age = result.age;
await turnContext.sendActivity(`I have your age as ${ profile.age }.`);
await turnContext.sendActivity('When is your flight?');
flow.lastQuestionAsked = question.date;
break;
} else {
// If we couldn't interpret their input, ask them for it again.
// Don't update the conversation flag, so that we repeat this step.
await turnContext.sendActivity(result.message || "I'm sorry, I didn't understand that.");
break;
}
// If we last asked for a date, record their response, confirm that we got it,
// let them know the process is complete, and update the conversation flag.
case question.date:
result = this.validateDate(input);
if (result.success) {
profile.date = result.date;
await turnContext.sendActivity(`Your cab ride to the airport is scheduled for ${ profile.date }.`);
await turnContext.sendActivity(`Thanks for completing the booking ${ profile.name }.`);
await turnContext.sendActivity('Type anything to run the bot again.');
flow.lastQuestionAsked = question.none;
profile = {};
break;
} else {
// If we couldn't interpret their input, ask them for it again.
// Don't update the conversation flag, so that we repeat this step.
await turnContext.sendActivity(result.message || "I'm sorry, I didn't understand that.");
break;
}
}
}
CustomPromptBot.java
private static CompletableFuture<Void> fillOutUserProfile(ConversationFlow flow,
UserProfile profile,
TurnContext turnContext) {
String input = "";
if (StringUtils.isNotBlank(turnContext.getActivity().getText())) {
input = turnContext.getActivity().getText().trim();
}
switch (flow.getLastQuestionAsked()) {
case None:
return turnContext.sendActivity("Let's get started. What is your name?", null, null)
.thenRun(() -> {flow.setLastQuestionAsked(ConversationFlow.Question.Name);});
case Name:
Triple<Boolean, String, String> nameValidationResult = validateName(input);
if (nameValidationResult.getLeft()) {
profile.setName(nameValidationResult.getMiddle());
return turnContext.sendActivity(String.format("Hi %s.", profile.getName()), null, null)
.thenCompose(result -> turnContext.sendActivity("How old are you?", null, null))
.thenRun(() -> { flow.setLastQuestionAsked(ConversationFlow.Question.Age); });
} else {
if (StringUtils.isNotBlank(nameValidationResult.getRight())) {
return turnContext.sendActivity(nameValidationResult.getRight(), null, null)
.thenApply(result -> null);
} else {
return turnContext.sendActivity("I'm sorry, I didn't understand that.", null, null)
.thenApply(result -> null);
}
}
case Age:
Triple<Boolean, Integer, String> ageValidationResult = ValidateAge(input);
if (ageValidationResult.getLeft()) {
profile.setAge(ageValidationResult.getMiddle());
return turnContext.sendActivity(String.format("I have your age as %d.", profile.getAge()), null, null)
.thenCompose(result -> turnContext.sendActivity("When is your flight?", null, null))
.thenRun(() -> { flow.setLastQuestionAsked(ConversationFlow.Question.Date); });
} else {
if (StringUtils.isNotBlank(ageValidationResult.getRight())) {
return turnContext.sendActivity(ageValidationResult.getRight(), null, null)
.thenApply(result -> null);
} else {
return turnContext.sendActivity("I'm sorry, I didn't understand that.", null, null)
.thenApply(result -> null);
}
}
case Date:
Triple<Boolean, String, String> dateValidationResult = ValidateDate(input);
AtomicReference<UserProfile> profileReference = new AtomicReference<UserProfile>(profile);
if (dateValidationResult.getLeft()) {
profile.setDate(dateValidationResult.getMiddle());
return turnContext.sendActivity(
String.format("Your cab ride to the airport is scheduled for %s.",
profileReference.get().getDate()))
.thenCompose(result -> turnContext.sendActivity(
String.format("Thanks for completing the booking %s.", profileReference.get().getDate())))
.thenCompose(result -> turnContext.sendActivity("Type anything to run the bot again."))
.thenRun(() -> {
flow.setLastQuestionAsked(ConversationFlow.Question.None);
profileReference.set(new UserProfile());
});
} else {
if (StringUtils.isNotBlank(dateValidationResult.getRight())) {
return turnContext.sendActivity(dateValidationResult.getRight(), null, null)
.thenApply(result -> null);
} else {
return turnContext.sendActivity("I'm sorry, I didn't understand that.", null, null)
.thenApply(result -> null);
}
}
default:
return CompletableFuture.completedFuture(null);
}
robotar/custom_prompt_bot.py
async def _fill_out_user_profile(
self, flow: ConversationFlow, profile: UserProfile, turn_context: TurnContext
):
user_input = turn_context.activity.text.strip()
# ask for name
if flow.last_question_asked == Question.NONE:
await turn_context.send_activity(
MessageFactory.text("Let's get started. What is your name?")
)
flow.last_question_asked = Question.NAME
# validate name then ask for age
elif flow.last_question_asked == Question.NAME:
validate_result = self._validate_name(user_input)
if not validate_result.is_valid:
await turn_context.send_activity(
MessageFactory.text(validate_result.message)
)
else:
profile.name = validate_result.value
await turn_context.send_activity(
MessageFactory.text(f"Hi {profile.name}")
)
await turn_context.send_activity(
MessageFactory.text("How old are you?")
)
flow.last_question_asked = Question.AGE
# validate age then ask for date
elif flow.last_question_asked == Question.AGE:
validate_result = self._validate_age(user_input)
if not validate_result.is_valid:
await turn_context.send_activity(
MessageFactory.text(validate_result.message)
)
else:
profile.age = validate_result.value
await turn_context.send_activity(
MessageFactory.text(f"I have your age as {profile.age}.")
)
await turn_context.send_activity(
MessageFactory.text("When is your flight?")
)
flow.last_question_asked = Question.DATE
# validate date and wrap it up
elif flow.last_question_asked == Question.DATE:
validate_result = self._validate_date(user_input)
if not validate_result.is_valid:
await turn_context.send_activity(
MessageFactory.text(validate_result.message)
)
else:
profile.date = validate_result.value
await turn_context.send_activity(
MessageFactory.text(
f"Your cab ride to the airport is scheduled for {profile.date}."
)
)
await turn_context.send_activity(
MessageFactory.text(
f"Thanks for completing the booking {profile.name}."
)
)
await turn_context.send_activity(
MessageFactory.text("Type anything to run the bot again.")
)
flow.last_question_asked = Question.NONE
Parsa och verifiera indata
Roboten använder följande villkor för att verifiera indata.
Namnet måste vara en icke-tom sträng. Det normaliseras genom att trimma blanksteg.
Åldern måste vara mellan 18 och 120 år. Det normaliseras genom att returnera ett heltal.
Datumet måste vara ett datum eller en tidpunkt minst en timme i framtiden.
Det normaliseras genom att bara returnera datumdelen av de parsade indata.
Kommentar
För ålders- och datumindata använder exemplet biblioteken Microsoft/Recognizers-Text för att utföra den inledande parsningen.
Det här är bara ett sätt att parsa indata. Mer information om dessa bibliotek finns i projektets README.
private static bool ValidateName(string input, out string name, out string message)
{
name = null;
message = null;
if (string.IsNullOrWhiteSpace(input))
{
message = "Please enter a name that contains at least one character.";
}
else
{
name = input.Trim();
}
return message is null;
}
private static bool ValidateAge(string input, out int age, out string message)
{
age = 0;
message = null;
// Try to recognize the input as a number. This works for responses such as "twelve" as well as "12".
try
{
// Attempt to convert the Recognizer result to an integer. This works for "a dozen", "twelve", "12", and so on.
// The recognizer returns a list of potential recognition results, if any.
var results = NumberRecognizer.RecognizeNumber(input, Culture.English);
foreach (var result in results)
{
// The result resolution is a dictionary, where the "value" entry contains the processed string.
if (result.Resolution.TryGetValue("value", out var value))
{
age = Convert.ToInt32(value);
if (age >= 18 && age <= 120)
{
return true;
}
}
}
message = "Please enter an age between 18 and 120.";
}
catch
{
message = "I'm sorry, I could not interpret that as an age. Please enter an age between 18 and 120.";
}
return message is null;
}
private static bool ValidateDate(string input, out string date, out string message)
{
date = null;
message = null;
// Try to recognize the input as a date-time. This works for responses such as "11/14/2018", "9pm", "tomorrow", "Sunday at 5pm", and so on.
// The recognizer returns a list of potential recognition results, if any.
try
{
var results = DateTimeRecognizer.RecognizeDateTime(input, Culture.English);
// Check whether any of the recognized date-times are appropriate,
// and if so, return the first appropriate date-time. We're checking for a value at least an hour in the future.
var earliest = DateTime.Now.AddHours(1.0);
foreach (var result in results)
{
// The result resolution is a dictionary, where the "values" entry contains the processed input.
var resolutions = result.Resolution["values"] as List<Dictionary<string, string>>;
foreach (var resolution in resolutions)
{
// The processed input contains a "value" entry if it is a date-time value, or "start" and
// "end" entries if it is a date-time range.
if (resolution.TryGetValue("value", out var dateString)
|| resolution.TryGetValue("start", out dateString))
{
if (DateTime.TryParse(dateString, out var candidate)
&& earliest < candidate)
{
date = candidate.ToShortDateString();
return true;
}
}
}
}
message = "I'm sorry, please enter a date at least an hour out.";
}
catch
{
message = "I'm sorry, I could not interpret that as an appropriate date. Please enter a date at least an hour out.";
}
return false;
}
robotar/customPromptBot.js
// Validates name input. Returns whether validation succeeded and either the parsed and normalized
// value or a message the bot can use to ask the user again.
static validateName(input) {
const name = input && input.trim();
return name !== undefined
? { success: true, name: name }
: { success: false, message: 'Please enter a name that contains at least one character.' };
};
// Validates age input. Returns whether validation succeeded and either the parsed and normalized
// value or a message the bot can use to ask the user again.
static validateAge(input) {
// Try to recognize the input as a number. This works for responses such as "twelve" as well as "12".
try {
// Attempt to convert the Recognizer result to an integer. This works for "a dozen", "twelve", "12", and so on.
// The recognizer returns a list of potential recognition results, if any.
const results = Recognizers.recognizeNumber(input, Recognizers.Culture.English);
let output;
results.forEach(result => {
// result.resolution is a dictionary, where the "value" entry contains the processed string.
const value = result.resolution.value;
if (value) {
const age = parseInt(value);
if (!isNaN(age) && age >= 18 && age <= 120) {
output = { success: true, age: age };
return;
}
}
});
return output || { success: false, message: 'Please enter an age between 18 and 120.' };
} catch (error) {
return {
success: false,
message: "I'm sorry, I could not interpret that as an age. Please enter an age between 18 and 120."
};
}
}
// Validates date input. Returns whether validation succeeded and either the parsed and normalized
// value or a message the bot can use to ask the user again.
static validateDate(input) {
// Try to recognize the input as a date-time. This works for responses such as "11/14/2018", "today at 9pm", "tomorrow", "Sunday at 5pm", and so on.
// The recognizer returns a list of potential recognition results, if any.
try {
const results = Recognizers.recognizeDateTime(input, Recognizers.Culture.English);
const now = new Date();
const earliest = now.getTime() + (60 * 60 * 1000);
let output;
results.forEach(result => {
// result.resolution is a dictionary, where the "values" entry contains the processed input.
result.resolution.values.forEach(resolution => {
// The processed input contains a "value" entry if it is a date-time value, or "start" and
// "end" entries if it is a date-time range.
const datevalue = resolution.value || resolution.start;
// If only time is given, assume it's for today.
const datetime = resolution.type === 'time'
? new Date(`${ now.toLocaleDateString() } ${ datevalue }`)
: new Date(datevalue);
if (datetime && earliest < datetime.getTime()) {
output = { success: true, date: datetime.toLocaleDateString() };
return;
}
});
});
return output || { success: false, message: "I'm sorry, please enter a date at least an hour out." };
} catch (error) {
return {
success: false,
message: "I'm sorry, I could not interpret that as an appropriate date. Please enter a date at least an hour out."
};
}
}
CustomPromptBot.java
private static Triple<Boolean, String, String> validateName(String input) {
String name = null;
String message = null;
if (StringUtils.isEmpty(input)) {
message = "Please enter a name that contains at least one character.";
} else {
name = input.trim();
}
return Triple.of(StringUtils.isBlank(message), name, message);
}
private static Triple<Boolean, Integer, String> ValidateAge(String input) {
int age = 0;
String message = null;
// Try to recognize the input as a number. This works for responses such as "twelve" as well as "12".
try {
// Attempt to convert the Recognizer result to an integer. This works for "a dozen", "twelve", "12", and so on.
// The recognizer returns a list of potential recognition results, if any.
List<ModelResult> results = NumberRecognizer.recognizeNumber(input, PromptCultureModels.ENGLISH_CULTURE);
for (ModelResult result : results) {
// The result resolution is a dictionary, where the "value" entry contains the processed String.
Object value = result.resolution.get("value");
if (value != null) {
age = Integer.parseInt((String) value);
if (age >= 18 && age <= 120) {
return Triple.of(true, age, "");
}
}
}
message = "Please enter an age between 18 and 120.";
}
catch (Throwable th) {
message = "I'm sorry, I could not interpret that as an age. Please enter an age between 18 and 120.";
}
return Triple.of(StringUtils.isBlank(message), age, message);
}
private static Triple<Boolean, String, String> ValidateDate(String input) {
String date = null;
String message = null;
// Try to recognize the input as a date-time. This works for responses such as "11/14/2018", "9pm", "tomorrow", "Sunday at 5pm", and so on.
// The recognizer returns a list of potential recognition results, if any.
try {
List<ModelResult> results = DateTimeRecognizer.recognizeDateTime(input, PromptCultureModels.ENGLISH_CULTURE);
// Check whether any of the recognized date-times are appropriate,
// and if so, return the first appropriate date-time. We're checking for a value at least an hour in the future.
LocalDateTime earliest = LocalDateTime.now().plus(1, ChronoUnit.HOURS);
for (ModelResult result : results) {
// The result resolution is a dictionary, where the "values" entry contains the processed input.
List<Map<String, Object>> resolutions = (List<Map<String, Object>>) result.resolution.get("values");
for (Map<String, Object> resolution : resolutions) {
// The processed input contains a "value" entry if it is a date-time value, or "start" and
// "end" entries if it is a date-time range.
String dateString = (String) resolution.get("value");
if (StringUtils.isBlank(dateString)) {
dateString = (String) resolution.get("start");
}
if (StringUtils.isNotBlank(dateString)){
DateTimeFormatter f = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss");
LocalDateTime candidate;
try {
candidate = LocalDateTime.from(f.parse(dateString));
} catch (DateTimeParseException err) {
// If the input is a date, it will throw an exception and it will create a datetime
// with the MIN localtime
DateTimeFormatter d = DateTimeFormatter.ofPattern("yyyy-MM-dd");
candidate = LocalDateTime.of(LocalDate.parse(dateString, d), LocalDateTime.MIN.toLocalTime());
}
if (earliest.isBefore(candidate)) {
DateTimeFormatter dateformat = DateTimeFormatter.ofPattern("MM-dd-yyyy");
date = candidate.format(dateformat);
return Triple.of(true, date, message);
}
}
}
}
robotar/custom_prompt_bot.py
def _validate_name(self, user_input: str) -> ValidationResult:
if not user_input:
return ValidationResult(
is_valid=False,
message="Please enter a name that contains at least one character.",
)
return ValidationResult(is_valid=True, value=user_input)
def _validate_age(self, user_input: str) -> ValidationResult:
# Attempt to convert the Recognizer result to an integer. This works for "a dozen", "twelve", "12", and so on.
# The recognizer returns a list of potential recognition results, if any.
results = recognize_number(user_input, Culture.English)
for result in results:
if "value" in result.resolution:
age = int(result.resolution["value"])
if 18 <= age <= 120:
return ValidationResult(is_valid=True, value=age)
return ValidationResult(
is_valid=False, message="Please enter an age between 18 and 120."
)
def _validate_date(self, user_input: str) -> ValidationResult:
try:
# Try to recognize the input as a date-time. This works for responses such as "11/14/2018", "9pm",
# "tomorrow", "Sunday at 5pm", and so on. The recognizer returns a list of potential recognition results,
# if any.
results = recognize_datetime(user_input, Culture.English)
for result in results:
for resolution in result.resolution["values"]:
if "value" in resolution:
now = datetime.now()
value = resolution["value"]
if resolution["type"] == "date":
candidate = datetime.strptime(value, "%Y-%m-%d")
elif resolution["type"] == "time":
candidate = datetime.strptime(value, "%H:%M:%S")
candidate = candidate.replace(
year=now.year, month=now.month, day=now.day
)
else:
candidate = datetime.strptime(value, "%Y-%m-%d %H:%M:%S")
# user response must be more than an hour out
diff = candidate - now
if diff.total_seconds() >= 3600:
return ValidationResult(
is_valid=True,
value=candidate.strftime("%m/%d/%y"),
)
return ValidationResult(
is_valid=False,
message="I'm sorry, please enter a date at least an hour out.",
)
except ValueError:
return ValidationResult(
is_valid=False,
message="I'm sorry, I could not interpret that as an appropriate "
"date. Please enter a date at least an hour out.",
)