Natural language processing extracts the meaning of a sentence and transforms it into structural data that can be consumed by programs. As a first step we will train an external natural language processor called Wit.ai.
- [Narrator] So far, we configured Iris to listen and reply.…Now, we want her to react to certain questions…and provide an answer to it if she has one.…Let's say someone asks, "What's the current time in Rome?"…So, we are asking for time and some place.…How can we pass it programmatically?…Sure, we could apply some sting matching…(mumbles) applying regular expressions and hope…that the user sticks to our syntax, but that's not…what people expect when we are talking about a bot.…It should be able to understand what we want…and regardless how we build a sentence.…
This is where natural language processing comes into play.…We will use a free service called Great to Achieve That.…It comes with a web interface and an API.…Let's get started with that.…I will log in with my GitHub account in this case,…so here is my account; now we want to create a new app,…so, use this plus icon here, click on it…and let's call this iris; put in some description;…A slack bot implementation.…
The language English is okay.…Let's set it to private and then click on Create App.…
Author
Daniel Khan
Released
11/4/2016After explaining some basics about Node.js and microservices, Daniel shows you how to sketch out the planned architecture for your application and get the boilerplate code, modules, and credentials in place. Next, he shows how to create a bot user in Slack, connect to Slack, and post messages. He also shows you how to get your bot to process variations in text by creating logic that delegates the processing of intent to dedicated modules. Lastly, he shows how to register additional services and he covers how to use monitoring to identify architectural or performance issues.
- Using Slack APIs
- Sketching out a Slack bot architecture
- Setting up a project and choosing modules
- Creating and naming your bot
- Connecting to Slack
- Setting up and using natural language processing
- Routing by intents
- Implementing geocoding and time calculation
- Adding and monitoring services
Skill Level Intermediate
Duration
Views
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Introduction
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Welcome29s
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1. Get Started with Microservices in Slack
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What we are going to build2m 21s
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Why use microservices?3m 46s
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2. Create Our Slack Bot
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Set up our project8m 57s
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Create our Iris bot user1m 47s
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Connect to Slack12m 32s
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Bring Iris to life5m 19s
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Use natural language processing17m 11s
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3. Add Services
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Route by intents9m 22s
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Implement geocoding6m 20s
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4. Add Resilience
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Add service registry route4m 52s
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Add service registry class11m 54s
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Add a weather service2m 54s
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Conclusion
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Next steps58s
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Video: Set up natural language processing