当我第二次尝试相同的输入时，LUIS 无法识别意图
LUIS is not recognizing the intent when I try the same input second time
我第一次在同一代码中将 LUIS 用于 Azure 搜索和 QnA 识别器。
我正在使用 intent.match 来匹配识别器。
我的问题是：
第一次，如果我问一个符合 QnA 意图的问题，它 returns 来自 QnA 库的答案。
后面是与 azuresearch 意图匹配的问题。 Azure 搜索也提供结果。
但是如果我重复必须与 QnA 匹配的问题，它会说 "no intent handler found for null"
var util = require('util');
var _ = require('lodash');
var builder = require('botbuilder');
var restify = require('restify');
var cognitiveservices = require('botbuilder-cognitiveservices');
/// <reference path="../SearchDialogLibrary/index.d.ts" />
var SearchLibrary = require('../SearchDialogLibrary');
var AzureSearch = require('../SearchProviders/azure-search');
var qintent;
// Setup Restify Server
var server = restify.createServer();
server.listen(process.env.port || process.env.PORT || 3978, function () {
console.log('%s listening to %s', server.name, server.url);
});
// Create chat bot and listen for messages
var connector = new builder.ChatConnector({
appId: process.env.MICROSOFT_APP_ID,
appPassword: process.env.MICROSOFT_APP_PASSWORD
});
server.post('/api/messages', connector.listen());
// Bot Storage: Here we register the state storage for your bot.
// Default store: volatile in-memory store - Only for prototyping!
// We provide adapters for Azure Table, CosmosDb, SQL Azure, or you can implement your own!
// For samples and documentation, see: https://github.com/Microsoft/BotBuilder-Azure
var inMemoryStorage = new builder.MemoryBotStorage();
var qnarecognizer = new cognitiveservices.QnAMakerRecognizer({
knowledgeBaseId: '6b30ac2a-5ce9-4576-a1cb-c89abfb73889',
authKey: 'd457c897-71cf-46bf-a3d9-9a1f51246fad',
endpointHostName: 'https://qnadispatchwg.azurewebsites.net/qnamaker'
});
const LuisModelUrl = 'https://westeurope.api.cognitive.microsoft.com/luis/v2.0/apps/180a9aaa-9d67-4d40-b3d3-121917f4dbb8?subscription-key=39155bb750dc4b2abd84d410d80fce21&timezoneOffset=0&q=';
var recognizer = new builder.LuisRecognizer(LuisModelUrl);
// Bot with main dialog that triggers search and display its results
var bot = new builder.UniversalBot(connector);
bot.set('storage', inMemoryStorage);
var intents = new builder.IntentDialog({ recognizers: [recognizer, qnarecognizer] });
bot.dialog('/', intents);
intents.matches('Greeting', (session) => {
session.send('You reached the Greeting intent. You said \'%s\'.', session.message.text);
session.endDialog();
});
intents.matches('qna', [
function (session, args) {
console.log("my args in qna:=========================================================================================== %o", args);
var answerEntity = builder.EntityRecognizer.findEntity(args.entities, 'answer');
session.send(answerEntity.entity);
}
]);
intents.matches('Search.Aco', [
function (session, args, next) {
console.log("my args in SearchDialog:=========================================================================================== %o", args);
var intent = args.intent;
console.log("our intent is " + intent);
var entities = builder.EntityRecognizer.findEntity(args.entities, 'businessterm');
console.log("recognnized entitiy is: "+ entities.entity);
// qintent = title;
//session.send('You reached the Search.Aco intent. You enquire for the entitiy \'%s\'.', qintent);
//console.log(" SearchDialog: before updating the session.message.text------------->" + session.message.text);
session.message.text= entities.entity;
//console.log(" SearchDialog: after updating the session.message.text------------->" + session.message.text);
SearchLibrary.begin(session);
},
function (session, args, results) {
// Process selected search results
session.send(
'Done! For future reference, you selected these properties: %s',
args.selection.map(function (i) { return i.key; }).join(', '));
}
]);
var azureSearchClient = AzureSearch.create('aco-intel2', '4105C6676D0CDD9B2E7891952B9E9E00', 'azureblob-index');
var jobsResultsMapper = SearchLibrary.defaultResultsMapper(jobToSearchHit);
// Register Search Dialogs Library with bot
bot.library(SearchLibrary.create({
multipleSelection: true,
search: function (query) { return azureSearchClient.search(query).then(jobsResultsMapper); },
refiners: ['people', 'content', 'location']
}));
// Maps the AzureSearch Job Document into a SearchHit that the Search Library can use
function jobToSearchHit(acosearch) {
console.log("inside jobToSearchHit");
console.log("inside acosearch.DocUrl" + acosearch.DocUrl + "-------" + acosearch.metadata_storage_name);
return {
key: acosearch.id,
title: acosearch.metadata_storage_name,
description: acosearch.content.substring(0, 100)+"...",
documenturl:acosearch.DocUrl,
imageUrl: acosearch.imageurl
};
}
module.exports = { qintent: "qintent"};
第二次，如果我正在混合
这是它的显示方式：
Emulator output
你能帮我理解 intent.match 和对话匹配之间的区别吗？我也尝试了以下方式，但它无法识别应答实体。如何从以下代码调用 QnA？
var util = require('util');
var _ = require('lodash');
var builder = require('botbuilder');
var restify = require('restify');
var cognitiveservices = require('botbuilder-cognitiveservices');
/// <reference path="../SearchDialogLibrary/index.d.ts" />
var SearchLibrary = require('../SearchDialogLibrary');
var AzureSearch = require('../SearchProviders/azure-search');
var qintent;
// Setup Restify Server
var server = restify.createServer();
server.listen(process.env.port || process.env.PORT || 3978, function () {
console.log('%s listening to %s', server.name, server.url);
});
// Create chat bot and listen for messages
var connector = new builder.ChatConnector({
appId: process.env.MICROSOFT_APP_ID,
appPassword: process.env.MICROSOFT_APP_PASSWORD
});
server.post('/api/messages', connector.listen());
// Bot Storage: Here we register the state storage for your bot.
// Default store: volatile in-memory store - Only for prototyping!
// We provide adapters for Azure Table, CosmosDb, SQL Azure, or you can implement your own!
// For samples and documentation, see: https://github.com/Microsoft/BotBuilder-Azure
var inMemoryStorage = new builder.MemoryBotStorage();
var qnarecognizer = new cognitiveservices.QnAMakerRecognizer({
knowledgeBaseId: '6b30ac2a-5ce9-4576-a1cb-c89abfb73889',
authKey: 'd457c897-71cf-46bf-a3d9-9a1f51246fad',
endpointHostName: 'https://qnadispatchwg.azurewebsites.net/qnamaker'
});
const LuisModelUrl = 'https://westeurope.api.cognitive.microsoft.com/luis/v2.0/apps/180a9aaa-9d67-4d40-b3d3-121917f4dbb8?subscription-key=39155bb750dc4b2abd84d410d80fce21&timezoneOffset=0&q=';
var recognizer = new builder.LuisRecognizer(LuisModelUrl);
// Bot with main dialog that triggers search and display its results
var bot = new builder.UniversalBot(connector, function (session, args) {
session.send('You reached the default message handler. You said \'%s\'.', session.message.text);
}).set('storage', inMemoryStorage);
bot.recognizer(recognizer, qnarecognizer);
bot.dialog('GreetingDialog',
(session) => {
session.send('You reached the Greeting intent. You said \'%s\'.', session.message.text);
session.endDialog();
}
).triggerAction({
matches: 'Greeting'
})
bot.dialog('HelpDialog',
(session) => {
session.send('You reached the Help intent. You said \'%s\'.', session.message.text);
session.endDialog();
}
).triggerAction({
matches: 'Help'
})
bot.dialog('CancelDialog',
(session) => {
session.send('You reached the Cancel intent. You said \'%s\'.', session.message.text);
session.endDialog();
}
).triggerAction({
matches: 'Cancel'
})
bot.dialog('QnADialog',[
function (session, args, next) {
var answerEntity = builder.EntityRecognizer.findEntity(args.entities, 'answer');
console.log(answerEntity);
session.send(answerEntity.entity);
}
]).triggerAction({
matches: 'Search.QnA'
})
bot.dialog('SearchDialog', [
function (session, args) {
console.log("my args in SearchDialog:=========================================================================================== %o", args);
var intent = args.intent;
title = builder.EntityRecognizer.findEntity(intent.entities, 'businessterm');
console.log(title.entity);
qintent = title.entity;
//session.send('You reached the Search.Aco intent. You enquire for the entitiy \'%s\'.', qintent);
//console.log(" SearchDialog: before updating the session.message.text------------->" + session.message.text);
session.message.text= qintent;
//console.log(" SearchDialog: after updating the session.message.text------------->" + session.message.text);
SearchLibrary.begin(session);
},
function (session, args, results) {
// Process selected search results
session.send(
'Done! For future reference, you selected these properties: %s',
args.selection.map(function (i) { return i.key; }).join(', '));
}
]).triggerAction({
matches: 'Search.Aco'
});
var azureSearchClient = AzureSearch.create('aco-intel2', '4105C6676D0CDD9B2E7891952B9E9E00', 'azureblob-index');
var jobsResultsMapper = SearchLibrary.defaultResultsMapper(jobToSearchHit);
// Register Search Dialogs Library with bot
bot.library(SearchLibrary.create({
multipleSelection: true,
search: function (query) { return azureSearchClient.search(query).then(jobsResultsMapper); },
refiners: ['people', 'content', 'location']
}));
// Maps the AzureSearch Job Document into a SearchHit that the Search Library can use
function jobToSearchHit(acosearch) {
console.log("inside jobToSearchHit");
console.log("inside acosearch.DocUrl" + acosearch.DocUrl + "-------" + acosearch.metadata_storage_name);
return {
key: acosearch.id,
title: acosearch.metadata_storage_name,
description: acosearch.content.substring(0, 100)+"...",
documenturl:acosearch.DocUrl,
imageUrl: acosearch.imageurl
};
}
module.exports = { qintent: "qintent"};
这段代码给我的痕迹如下：
logs
请帮助我理解上面的代码有什么问题。会有很大的帮助。
此外，intent.match 和对话框匹配之间的差异。根据我的理解，bot 识别 session.message 并将其与 'match:' 参数匹配并调用对话框。所以它可以在对话框之间来回跳转。
在第一种情况下，我觉得很奇怪，因为第二次没有这样做。
提前致谢，
维维克
使用 IntentDialog class（例如 var intents = new builder.IntentDialog( ...）不允许以直接向机器人注册对话的方式进行意图中断。
给定以下示例对话框：
const bot = new UniversalBot(connector); // Assume an already created ChatConnector
bot.recognizer(new LuisRecognizer(LuisModelUrl); // LUIS model with HowAreYou and Weather intents.
bot.dialog('HowAreYou',[
function (session, args, next) {
builder.Prompts.text(session, `I\'m doing great! How are you?`);
},
function (session, args) {
var result = session.message.text;
session.send(`I\'m glad to hear you\'re doing ${result}!`);
]).triggerAction({
matches: 'HowAreYou'
});
bot.dialog('Weather', [
function (session, args) {
builder.Prompts.text(session `Which city do you want to find the weather forecast for?`);
},
function (session, args) {
// some logic to handle the response and call a weather api
}
]).triggerAction({
matches: 'Weather'
});
当用户询问 "How are you?" 时，LUIS 会检测到 'HowAreYou' 意图，并且机器人会开始相应的对话。然后机器人会提示用户 "I'm doing great! How are you?'。如果用户随后对机器人说 "Show me the weather"，该机器人将收到该消息并检测 "Weather" 意图。这样做之后，它将 "Weather" 对话框添加到对话框堆栈的顶部并开始天气对话框。
UniversalBot 不会阻止您在检测到新意图时切换对话框。在意图对话框的 code 中，它会继续您已经在的任何对话框，并且不支持切换到新的 intent/dialog。
我第一次在同一代码中将 LUIS 用于 Azure 搜索和 QnA 识别器。
我正在使用 intent.match 来匹配识别器。
我的问题是：
第一次，如果我问一个符合 QnA 意图的问题，它 returns 来自 QnA 库的答案。
后面是与 azuresearch 意图匹配的问题。 Azure 搜索也提供结果。
但是如果我重复必须与 QnA 匹配的问题，它会说 "no intent handler found for null"
var util = require('util');
var _ = require('lodash');
var builder = require('botbuilder');
var restify = require('restify');
var cognitiveservices = require('botbuilder-cognitiveservices');
/// <reference path="../SearchDialogLibrary/index.d.ts" />
var SearchLibrary = require('../SearchDialogLibrary');
var AzureSearch = require('../SearchProviders/azure-search');
var qintent;
// Setup Restify Server
var server = restify.createServer();
server.listen(process.env.port || process.env.PORT || 3978, function () {
console.log('%s listening to %s', server.name, server.url);
});
// Create chat bot and listen for messages
var connector = new builder.ChatConnector({
appId: process.env.MICROSOFT_APP_ID,
appPassword: process.env.MICROSOFT_APP_PASSWORD
});
server.post('/api/messages', connector.listen());
// Bot Storage: Here we register the state storage for your bot.
// Default store: volatile in-memory store - Only for prototyping!
// We provide adapters for Azure Table, CosmosDb, SQL Azure, or you can implement your own!
// For samples and documentation, see: https://github.com/Microsoft/BotBuilder-Azure
var inMemoryStorage = new builder.MemoryBotStorage();
var qnarecognizer = new cognitiveservices.QnAMakerRecognizer({
knowledgeBaseId: '6b30ac2a-5ce9-4576-a1cb-c89abfb73889',
authKey: 'd457c897-71cf-46bf-a3d9-9a1f51246fad',
endpointHostName: 'https://qnadispatchwg.azurewebsites.net/qnamaker'
});
const LuisModelUrl = 'https://westeurope.api.cognitive.microsoft.com/luis/v2.0/apps/180a9aaa-9d67-4d40-b3d3-121917f4dbb8?subscription-key=39155bb750dc4b2abd84d410d80fce21&timezoneOffset=0&q=';
var recognizer = new builder.LuisRecognizer(LuisModelUrl);
// Bot with main dialog that triggers search and display its results
var bot = new builder.UniversalBot(connector);
bot.set('storage', inMemoryStorage);
var intents = new builder.IntentDialog({ recognizers: [recognizer, qnarecognizer] });
bot.dialog('/', intents);
intents.matches('Greeting', (session) => {
session.send('You reached the Greeting intent. You said \'%s\'.', session.message.text);
session.endDialog();
});
intents.matches('qna', [
function (session, args) {
console.log("my args in qna:=========================================================================================== %o", args);
var answerEntity = builder.EntityRecognizer.findEntity(args.entities, 'answer');
session.send(answerEntity.entity);
}
]);
intents.matches('Search.Aco', [
function (session, args, next) {
console.log("my args in SearchDialog:=========================================================================================== %o", args);
var intent = args.intent;
console.log("our intent is " + intent);
var entities = builder.EntityRecognizer.findEntity(args.entities, 'businessterm');
console.log("recognnized entitiy is: "+ entities.entity);
// qintent = title;
//session.send('You reached the Search.Aco intent. You enquire for the entitiy \'%s\'.', qintent);
//console.log(" SearchDialog: before updating the session.message.text------------->" + session.message.text);
session.message.text= entities.entity;
//console.log(" SearchDialog: after updating the session.message.text------------->" + session.message.text);
SearchLibrary.begin(session);
},
function (session, args, results) {
// Process selected search results
session.send(
'Done! For future reference, you selected these properties: %s',
args.selection.map(function (i) { return i.key; }).join(', '));
}
]);
var azureSearchClient = AzureSearch.create('aco-intel2', '4105C6676D0CDD9B2E7891952B9E9E00', 'azureblob-index');
var jobsResultsMapper = SearchLibrary.defaultResultsMapper(jobToSearchHit);
// Register Search Dialogs Library with bot
bot.library(SearchLibrary.create({
multipleSelection: true,
search: function (query) { return azureSearchClient.search(query).then(jobsResultsMapper); },
refiners: ['people', 'content', 'location']
}));
// Maps the AzureSearch Job Document into a SearchHit that the Search Library can use
function jobToSearchHit(acosearch) {
console.log("inside jobToSearchHit");
console.log("inside acosearch.DocUrl" + acosearch.DocUrl + "-------" + acosearch.metadata_storage_name);
return {
key: acosearch.id,
title: acosearch.metadata_storage_name,
description: acosearch.content.substring(0, 100)+"...",
documenturl:acosearch.DocUrl,
imageUrl: acosearch.imageurl
};
}
module.exports = { qintent: "qintent"};
第二次，如果我正在混合 这是它的显示方式：
Emulator output
你能帮我理解 intent.match 和对话匹配之间的区别吗？我也尝试了以下方式，但它无法识别应答实体。如何从以下代码调用 QnA？
var util = require('util');
var _ = require('lodash');
var builder = require('botbuilder');
var restify = require('restify');
var cognitiveservices = require('botbuilder-cognitiveservices');
/// <reference path="../SearchDialogLibrary/index.d.ts" />
var SearchLibrary = require('../SearchDialogLibrary');
var AzureSearch = require('../SearchProviders/azure-search');
var qintent;
// Setup Restify Server
var server = restify.createServer();
server.listen(process.env.port || process.env.PORT || 3978, function () {
console.log('%s listening to %s', server.name, server.url);
});
// Create chat bot and listen for messages
var connector = new builder.ChatConnector({
appId: process.env.MICROSOFT_APP_ID,
appPassword: process.env.MICROSOFT_APP_PASSWORD
});
server.post('/api/messages', connector.listen());
// Bot Storage: Here we register the state storage for your bot.
// Default store: volatile in-memory store - Only for prototyping!
// We provide adapters for Azure Table, CosmosDb, SQL Azure, or you can implement your own!
// For samples and documentation, see: https://github.com/Microsoft/BotBuilder-Azure
var inMemoryStorage = new builder.MemoryBotStorage();
var qnarecognizer = new cognitiveservices.QnAMakerRecognizer({
knowledgeBaseId: '6b30ac2a-5ce9-4576-a1cb-c89abfb73889',
authKey: 'd457c897-71cf-46bf-a3d9-9a1f51246fad',
endpointHostName: 'https://qnadispatchwg.azurewebsites.net/qnamaker'
});
const LuisModelUrl = 'https://westeurope.api.cognitive.microsoft.com/luis/v2.0/apps/180a9aaa-9d67-4d40-b3d3-121917f4dbb8?subscription-key=39155bb750dc4b2abd84d410d80fce21&timezoneOffset=0&q=';
var recognizer = new builder.LuisRecognizer(LuisModelUrl);
// Bot with main dialog that triggers search and display its results
var bot = new builder.UniversalBot(connector, function (session, args) {
session.send('You reached the default message handler. You said \'%s\'.', session.message.text);
}).set('storage', inMemoryStorage);
bot.recognizer(recognizer, qnarecognizer);
bot.dialog('GreetingDialog',
(session) => {
session.send('You reached the Greeting intent. You said \'%s\'.', session.message.text);
session.endDialog();
}
).triggerAction({
matches: 'Greeting'
})
bot.dialog('HelpDialog',
(session) => {
session.send('You reached the Help intent. You said \'%s\'.', session.message.text);
session.endDialog();
}
).triggerAction({
matches: 'Help'
})
bot.dialog('CancelDialog',
(session) => {
session.send('You reached the Cancel intent. You said \'%s\'.', session.message.text);
session.endDialog();
}
).triggerAction({
matches: 'Cancel'
})
bot.dialog('QnADialog',[
function (session, args, next) {
var answerEntity = builder.EntityRecognizer.findEntity(args.entities, 'answer');
console.log(answerEntity);
session.send(answerEntity.entity);
}
]).triggerAction({
matches: 'Search.QnA'
})
bot.dialog('SearchDialog', [
function (session, args) {
console.log("my args in SearchDialog:=========================================================================================== %o", args);
var intent = args.intent;
title = builder.EntityRecognizer.findEntity(intent.entities, 'businessterm');
console.log(title.entity);
qintent = title.entity;
//session.send('You reached the Search.Aco intent. You enquire for the entitiy \'%s\'.', qintent);
//console.log(" SearchDialog: before updating the session.message.text------------->" + session.message.text);
session.message.text= qintent;
//console.log(" SearchDialog: after updating the session.message.text------------->" + session.message.text);
SearchLibrary.begin(session);
},
function (session, args, results) {
// Process selected search results
session.send(
'Done! For future reference, you selected these properties: %s',
args.selection.map(function (i) { return i.key; }).join(', '));
}
]).triggerAction({
matches: 'Search.Aco'
});
var azureSearchClient = AzureSearch.create('aco-intel2', '4105C6676D0CDD9B2E7891952B9E9E00', 'azureblob-index');
var jobsResultsMapper = SearchLibrary.defaultResultsMapper(jobToSearchHit);
// Register Search Dialogs Library with bot
bot.library(SearchLibrary.create({
multipleSelection: true,
search: function (query) { return azureSearchClient.search(query).then(jobsResultsMapper); },
refiners: ['people', 'content', 'location']
}));
// Maps the AzureSearch Job Document into a SearchHit that the Search Library can use
function jobToSearchHit(acosearch) {
console.log("inside jobToSearchHit");
console.log("inside acosearch.DocUrl" + acosearch.DocUrl + "-------" + acosearch.metadata_storage_name);
return {
key: acosearch.id,
title: acosearch.metadata_storage_name,
description: acosearch.content.substring(0, 100)+"...",
documenturl:acosearch.DocUrl,
imageUrl: acosearch.imageurl
};
}
module.exports = { qintent: "qintent"};
这段代码给我的痕迹如下： logs
请帮助我理解上面的代码有什么问题。会有很大的帮助。 此外，intent.match 和对话框匹配之间的差异。根据我的理解，bot 识别 session.message 并将其与 'match:' 参数匹配并调用对话框。所以它可以在对话框之间来回跳转。
在第一种情况下，我觉得很奇怪，因为第二次没有这样做。
提前致谢， 维维克
使用 IntentDialog class（例如 var intents = new builder.IntentDialog( ...）不允许以直接向机器人注册对话的方式进行意图中断。
给定以下示例对话框：
const bot = new UniversalBot(connector); // Assume an already created ChatConnector
bot.recognizer(new LuisRecognizer(LuisModelUrl); // LUIS model with HowAreYou and Weather intents.
bot.dialog('HowAreYou',[
function (session, args, next) {
builder.Prompts.text(session, `I\'m doing great! How are you?`);
},
function (session, args) {
var result = session.message.text;
session.send(`I\'m glad to hear you\'re doing ${result}!`);
]).triggerAction({
matches: 'HowAreYou'
});
bot.dialog('Weather', [
function (session, args) {
builder.Prompts.text(session `Which city do you want to find the weather forecast for?`);
},
function (session, args) {
// some logic to handle the response and call a weather api
}
]).triggerAction({
matches: 'Weather'
});
当用户询问 "How are you?" 时，LUIS 会检测到 'HowAreYou' 意图，并且机器人会开始相应的对话。然后机器人会提示用户 "I'm doing great! How are you?'。如果用户随后对机器人说 "Show me the weather"，该机器人将收到该消息并检测 "Weather" 意图。这样做之后，它将 "Weather" 对话框添加到对话框堆栈的顶部并开始天气对话框。
UniversalBot 不会阻止您在检测到新意图时切换对话框。在意图对话框的 code 中，它会继续您已经在的任何对话框，并且不支持切换到新的 intent/dialog。