I have a bot that uses .NET, MS Bot Framework and LUIS.ai for its smarts.
All's fine, except that I need to provide a way for non-technical users to train the bot and teach it new things, i.e. new intents in LUIS.ai.
In other words, suppose that right now the bot can answer messages like "hey bot where can i get coffee" and "where can I buy some clothes" with simple phrases containing directions. Non-technical users need to be able to train it to answer "where can I get some food" too.
Here's what I have considered:
Continuing to use LUIS.ai. Doesn't work because LUIS.ai doesn't have an API. The best it has is the GUI to refine existing intents, and the upload app/phrase list feature. The process can be semi-automated if the JSON file with the app can be generated by some application that I write; however, there still needs to be backend code that handles the new intents, and that has to be implemented by a C# coder.
Could it work if I switch from C# to Node.js? Then theoretically I would be able to auto-generate code files / intent handlers.
Azure Bot Service. Seems it doesn't have a non-technical interface and is just a browser-based IDE.
Ditching Bot Framework entirely and using third-party tools such as motion.ai. Doesn't work because there's no "intellect" as the one provided by LUIS.ai.
Using Form Flow that's part of Bot Framework. If my GUI bot builder application can generate JSON files, these files can be used by Bot Framework to build a bot automatically. Doesn't work because there's no intellect as in LUIS.ai.
Keep using Bot Framework, but ditch LUIS and build a separate web service based on a node.js language processing library for determining intents. May or may not work, may be less smart than LUIS, and could be an overkill.
Override the method in LuisDialog that selects the intent from the LuisResponse, in order to use the my own way to decide the intent (but how?).
At this point I'm out of ideas and any pointers will be greatly appreciated.
First of all, LUIS.ai provides an API that you can use to automatize the training. Moreover, here is Luis Trainer written entirely in Python against the API that just does that.
The easiest one, probably is the one you are describing in #1: you can automatize the training (as explaining above) but you will still have to deploy a new version of the bot if new intents are being provided. One thing is letting users to train an existing model with new utteraces and another completely and different thing is to let them create the model :)
It might be hard to skip having to write the backend code (I wouldn't automatize that at all)
Here is a potential idea (not sure if it will work though). You would need 2 Luis models.
One with your current model, that users will be able to train with new utterances.
The second model, is one exclusively intended to be "expanded" with new intents by users.
If you separate this in that way, you might be able to look into a "plugin" architecture for the second LUIS model. So, your app, somehow, loads dinamically an assembly where the second model lives.
Once you you have that in place, you can focus on writing the backend code for your second Luis Model without having to worry about the bot/first model. You should be able to replace the assembly with the second Luis Model and be able in the bot to detect if there is new version of that assembly and replace the current one in the app domain.
As I said, is just an idea as I'm brainstorming with you. Sounds a bit complex, and it's not addressing all your concerns; as you still will need to write code (which in any case, you will eventually have to do)
I am working through a challenge project (training) to automate the creation of Chat Bots specifically targeted against a Luis.ai model using plain old javascript and web services to Luis.
I looked at the Bot Framework and it's just too cumbersome to automate (I want X number of customers to create a Chat Bot without coding). I also want to add my own type of 'Cards' (html widgets) that do more and can be easily configured by someone with zero coding skills.
Calls to the Luis.ai/Cognitive Services API are made in my code behind and the json response returned to my own rules engine. On the following URL click the LUIS API link on the page to open the Luis API Console where you can test, and train your Model. All the endpoints you will need are here...
https://dev.projectoxford.ai/docs/services/
Based on the various endpoints on that page, you can use WebClient in asp.net to pull back the response. So in my testing I have buttons on a page to push utterances up to the model, pull back entities, create hierarchical entities and so on. Have a look at http://onlinebotbuilder.com to see how an intent of product dynamically inserted a shopping cart.
When your tool is built and utterances start to arrive, Luis.ai will store them and via the Suggest tab (at Luis.ai) it will ask you for guidance...Unfortunately I don't think you could give that control over to your customers, unless they are experts in your domain (they understand which utterance belongs to which intent). You don't need to take your app down, just train it periodically to improve the Model based on your customers input...soon enough you will have your model working well based on your intents.
Hope that helps.
Related
I have subscription on Azure and I dowloaded chat bot with my AppId and password. On page luis.ai I trained new model and exported it to downloaded azure project (with flight booking). I replaced their cognitive model with my model from luis.ai, but after that - azure project is always working with old data. I don´t understand why, because their model is removed from my PC. What should I do to working with my own model? Thanks.
You code is based on the core-bot sample. First of all, make sure that your LUIS configuration is set up correctly in your .env file (or in App Settings if running from Azure). The recognizer is created in index.js and passed to MainDialog.js. From the core-bot sample code, I'm actually not seeing where it is importing the local code. I think that is maybe just to give you the model to import to your own LUIS app? If you have the proper LUIS keys and app ID, it should respond to whatever you have in there. My guess is maybe that you replaced the FlightBooking.json LUIS model file, but didn't actually point the bot to your LUIS app with the new intents.
I would suggest, though, that this isn't the best sample to use if you are trying to just tweak it. There are a lot of things here that are set up specifically for booking flights that don't really make sense if that's not what your bot is doing. Personally I like the Dispatch Bot sample better as a starting point (even if you are not using Dispatch CLI tool), though it has the intent actions within the bot file instead of separate dialogs. Maybe that will give you a better starting point though?
I am creating an e-commerce API using the Django Rest Framework. The API will handle the following areas:
Databases
User Registration
Permissions
Orders/Payments
There's still one area in which I'm not quite sure how to implement in my project. It's the cart functionality. Would it be better to implement it on the client-side (ex: React/Ember) or on the server-side (i.e. API)?
One scenario that confused me is if the user is logged in in different platforms (ex: Website and mobile app). I want the user to have the same cart on mulitple platforms.
In that particular use case, if you want cart persistence then it must be backend. The reason for this is one being able to have a single source of truth. The phone app and the web app cannot talk to each other unless they have some sort of "common ground" between them.
That's where the API comes in. It will allow both ends to speak to each other by having the API as the single source of truth. See my terrible diagram for a visual.
Is there a way to extend a bot published and create similar one without much changes?
Below is a use case -
Creating bots for a multi-region site - there is a bot for the US region and for Europe I need to create the similar bot, but with some UI changes and some changes in the user/dialog flow.
I can add conditions in code and separate the logic and have both region pointing to same app. Wanted to know if there is a better way?
I am evaluating MS Health Bot service and able to create and test custom scenarios. However, I was looking at extending existing in-built scenario like "I have a headache" and customize based on my need. I could see product features say we can extend existing scenarios but I don't see any documentation on how to do it. Anyone aware of how to extend existing scenario?
Thanks
Monu
Additional Information:
Health Bot Service provided three templates in the catalog - Provider Lookup, File a claim, Handoff to a human. There are few others with Coming Soon tag.
Scenarios template catalog
However, I thought, I can use any of the already trained bot scenario to handle medical conditions like "I have a headache" as shown in the diagram below.(which shows up in empty designer page on the right chat widget)
Demo chat for "I have a headache"
So my revised question is "we will be able to extend only scenario that is part of template catalog and our own created scenario". Is that correct understanding?
Thanks in advance
You can customize pre-built scenarios in the Healthcare Bot through the Scenario Designer. In the Healthcare bot service you created, click on Manage Account. If you do not have any scenarios configured, either select a template scenario or create a new blank scenario. Otherwise, click on the name of the scenario to open the designer. From here, you can customize the scenario as needed by either adding more scenario elements from the top pane or modifying elements in the scenario.
At the moment it appears that you are only able to modify the three provided templates. You do not have access to the other scenarios like 'I have a headache' in the healthcare manager. The Healthcare Bot Service is relatively new so that might change in future updates.
I would recommend looking at the topics under Scenario Authoring in the Healthcare Bot Documentation for more details on creating and editing scenarios.
Hope this helps!
If you have used the Language Understanding Service (LUIS) which is part of Cognitive Services suite from Microsoft, you probably have come to the point where you needed to improve the performance of your models at predicting intents.
LUIS allows you to train models based on sample utterances which you supply either interactively or in batches. In addition, I would like to have the chat logs showing utterances which are wrongly classified by the model so I can use them as a basis for new training data-sets.
I would imagine that such feature would be released in future but in the meantime, does anyone have a work-around for this scenario?
I think a good way to implement this (by hand), would be to route all the messages that were wrongly classified to some kind of storage or log so you could in the future use them to retrain your LUIS model. In fact, you could use LUIS API to make calls dynamically and easily with the data in your log.
So, the flow would be something like this:
1) User send message to bot.
2) Bot logic tries to match message's intent using LUIS model.
3) An intent isn't found or the value associated to the result is really low.
4) Grab that message and store it somewhere (from a simple txt file stored in an Azure Blob Storage), or in in a Database (Table Storage, DocumentDB or SQL Server).
5) Make a simple program that for each line in your log makes you choose an intent and then it calls LUIS Api to retrain.
So, I found the closest thing to what I had in mind when I asked the question.
Right on the "MyApps" page on luis.ai there's the possibility to download the chat logs in which one can see the entire set of interactions between users and the bot. It could be a good starting point for picking out intents which were wrongly classified.
I attached a screenshot to indicate the link
The only caveat is that the log chat format is currently in .csv which isn't so readable. Hopefully LUIS supports json formatted logs soon.