I am developping a bot using the LUIS API by Microsoft. This bot must understand queries related to shopping like "I want potatoes".
The only thing my application is struggling with is detecting intents from composite terms:
For the query "I want chopped steak", LUIS will detect chopped as an intent but not "chopped steak". I tried creating a productName phrase list feature and setting different composite terms including "chopped steak" but this doesn't seem to work.
What could I do to achieve that purpose ?
Related
I am developing chatbot using Rasa for a Contract Manager Organisation. I am facing few issues and after reading a lot on the forums and Rasa blog, I am unable to conclude to a solution for this. I have several similar intents with similar examples like -
“inform_supplier_start_date” and “inform_contract_start_date”.
“inform_supplier_email” and “inform_customer_email” and “inform_reviewer_email”
Now the issue is, for both the categories of intents the example sentence in nlu.md is same. What I exactly mean is-
##intent:inform_suppler_start_date
-what is the supplier [Microsoft] (supplier_name) start date
-[EON Digital] (supplier_name) start date
##intent:inform_contract_start
1) start-date of [O2 Mobile phones] (contract_name)
2) [O2 Mobile phones] (contract_name) start date
The model isnt able to differentiate and identify the correct intent. It is getting confused and identifying the wrong intent, since the words in these intents are similar.
I need correct intents to be recognised ,so that accordingly, In custom action i can query the Database and get the corresponding result for supplier and contract.
I have many fields like this for which the example data and user queries will be same. For Example-
customer_email & supplier_email & reviewer_email
total_spend_contract & total_spend_supplier & total_spend_customer
contract_number_for_supplier & contract_number_of_contract & contract_number_organisation
What exactly I should be doing to get correct classification. One solution i am thinking of is merging the intents like “supplier_start_date” and "contract_start_date" as one “start_date” and check for the extracted entity inside custom actions in both supplier and contract database. But I dont think that would be proper usage of Natural Language.
Please Suggest, I shall be highly greatful for the same. Regards.
As the examples for your intents are very similar, the model will not be able to differentiate between them. Also the intent is actual the same, inform_suppler_start_date and inform_contract_start inform the bot about a start date. What kind of start date it is should be figured out via the entity recognition. So I would propose to merge the similar intents and check what the entity recognition detected as entities. Depending on whether a supplier or a contract was found, you can execute query A or B.
I have created several utterances in LUIS for an intent to create new meeting items in my application.
I have tagged the corresponding elements in the utterance to recognize the name of the invited person and the date / time of the meeting.
When I train the model and test it afterwards, date and time is recognized every time. Not so for the contactname. I have tried all possible things like adding the utterance as pattern, adding phrase lists, but no success.
What can I do, to make this work? Is there anythink I am missing?
If you're using simple entities, keep in mind that you'll need to train 10-15 utterances, and that there should be different names in all utterances. Using the same name repeatedly may cause faulty training.
Our bot has a large set of skills (LUIS and QnA Maker intents), but not all skills are useful for all users. We would like to suppress some skills depending on who the user is.
We developed some code to do this for LUIS intents, dynamically filtering intents returned from our model to only include ones appropriate for the current user.
The issue we have though, is that we also have a couple of QnA models in our array of recognizers (recognizer_array) ...
var intents = new builder.IntentDialog({ recognizers: recognizer_array,
intentThreshold: 0.85, recognizeOrder: 'series'});
bot.dialog('/mainDialogue', intents);
But not all users need these QnA models, we would like to exclude them for some users.
Is there a way to dynamically filter intents so that we could exclude these QnA intents for some users?
I am currently using MS LUIS for Chatbot.
Our country usually talks and chats using 2 languages, English and Chinese.
However, in LUIS I can only define one culture.
As a result, when my culture is set to English, and when I imports Chinese text, the confidence level is very low (e.g. English - 0.88, Chinese - 0.1). The other way round is the same.
The situation is the same even after I did tokenize the Chinese text using library like JieBa or THULAC.
Therefore when I did testing, it is usually very easy to fall into an unrelated intent.
I would like to make LUIS recognize both English AND Chinese easily. Are there any way to solve this problem?
Thank you very much for your help.
I would like to make LUIS recognize both English AND Chinese easily. Are there any way to solve this problem?
Yes, the way is to separate your LUIS apps/projects, 1 for each language, and use a language detection before calling LUIS.
That's the official approach from LUIS docs (see here):
If you need a multi-language LUIS client application such as a chat
bot, you have a few options. If LUIS supports all the languages, you
develop a LUIS app for each language. Each LUIS app has a unique app
ID, and endpoint log. If you need to provide language understanding
for a language LUIS does not support, you can use Microsoft Translator
API to translate the utterance into a supported language, submit the
utterance to the LUIS endpoint, and receive the resulting scores.
For the language detection you can use Text Analytics API from Microsoft Cognitive Services for example to get the text language, and then with this result query the right LUIS app.
How to use it?
Documentation of Language detection in Text Analytics API here
Text analytics API: here
As Nicolas mentioned above you can use Multilanguage chat application with separate LUIS apps for each culture.
In order to have single LUIS application, you could use the Translator Text API to translate all incoming messages before they're sent to LUIS. In this case you'll want to use middleware to handle the translation before your LUIS Recognizer is called. You can also use middleware to translate your bot's response so you don't have to use additional localization inside of your bot
Tokenizing in LUIS is different for each language in LUIS.
In the zh-cn culture, LUIS expects the simplified Chinese character set instead of the traditional character set.
Here is one more sample where you can select a language from the bot and continue the consversation as required.
After investigation and several testings, I guess I found a way on how to do that properly:
First of all, I am currently using MS BotFramework - NodeJS (3.14.0) version to create my Bot.
And in botbuilder class, you have a function called IntentDialog, it accepts a list of recognizers. So I wrote something like this:
In luis.js
const builder = require("botbuilder")
// Setting for LUIS.ai
// Universal API key for both apps
let luisAPIKey = process.env.LuisAPIKey;
// First assign variables for Chinese LUIS app
let luisAppId_Chi = process.env.LuisAppId_Chi;
let luisAPIHostName_Chi = process.env.LuisAPIHostName_Chi || 'westus.api.cognitive.microsoft.com';
let LuisModelUrl_Chi = 'https://' + luisAPIHostName_Chi + '/luis/v2.0/apps/' + luisAppId_Chi + '?subscription-key=' + luisAPIKey + '&verbose=true';
// Then assign variables for English LUIS app
let luisAppId_Eng = process.env.LuisAppId_Eng;
let luisAPIHostName_Eng = process.env.LuisAPIHostName_Eng || 'westus.api.cognitive.microsoft.com';
let LuisModelUrl_Eng = 'https://' + luisAPIHostName_Eng + '/luis/v2.0/apps/' + luisAppId_Eng + '?subscription-key=' + luisAPIKey + '&verbose=true';
// Return an object with 2 attributes: Chi for Chinese LUIS and Eng for English LUIS
let luis = {};
luis.chi = new builder.LuisRecognizer(LuisModelUrl_Chi);
luis.eng = new builder.LuisRecognizer(LuisModelUrl_Eng);
module.exports = luis;
In app.js
const luis = require("./luis")
builder.IntentDialog({ recognizers: [luis.chi, luis.eng] });
And when I tested in botEmulator, it seems that it will first check LUIS Chi app, and then go to LUIS Eng app.
I don't know what is the criteria/threshold that this recognizer used to controls whether jumps to another app or not. But at present it works for me to certain extend. It is not accurate by at least a good(?) start. :D
No MS Text translation API need.
By the way, the code will look nicer if I can get the topIntent and LUIS path right in session variable.
Hope it helps someone.
I have an app in LUIS with one intent "Help" (appart from None) and when I test it with utterances that my intent does not cover (e.g "Hi man"), LUIS resolves to the "Help" intent... I have no utterances in "None" intent...
What should I do? Should I add all the utterances I don't want to match "Help" intent in "None"?
Should I need to know everything a user can ask to my bot which is not related with "Help"?
For me, that's not make sense at all... and I think that is exactly how LUIS works...
Intent are the action which we define, None is predefined Intent which come along with every LUIS model that you create , coming back to your problem. You have only define one intent i.e "help" so whenever LUIS gets the any query it will show the highest scoring intent i.e. "help". whenever you create an intent make to sure to save at least 5-6 co-related utterance, so that LUIS can generate a pattern out of it 'more you define co-related utterance better accuracy of result you will get'
if you want LUIS to respond on "HI man" create a new intent 'greet' save some utterance let LUIS do the remaining task, lastly about None intent If any user input 'asdsafdasdsfdsf' string like this. Your bot should be able to handle it respond accordingly like 'this asdsafdasdsfdsf is irrelevant to me' in simple term 'any irregular action that user want bot to perform come under none intent' i hope this will help
You can check the score of the Luis intent and then accordingly send the default response from code. For the utterances which are configured will have a greater score. Also, Luis app shud be balanced in terms of utterances configured as there is not a defined way that u can point utterances to None intent. Please check this link for best practices.
https://learn.microsoft.com/en-us/azure/cognitive-services/luis/luis-concept-best-practices. Also to highlight Luis does not work in terms of keyword matching to the utterances which you have configured. It works in terms of data you add in Luis in respective intents.