Building Chatbot: Guide Users

That sounds like a great project! I'd be happy to assist you with this. Let's get a clearer picture of what you want to achieve so we can start on the right foot. Here are some initial questions:

1. Do you have any specific programming languages or frameworks you would like to use for this project, or are you open to suggestions?

2. What type of courses are being offered and how are they currently categorized? Are there specific attributes or details (like difficulty level, topic, duration etc.) that the chat agent should use to recommend a course?

3. Who is the target audience for these courses? Are they beginners, intermediates, experts or a mix?

4. What are the key functionalities you want your chat agent to have? For example, should it be able to answer frequently asked questions, take payments, enroll users in a course, or simply guide users to the right course?

5. Do you have any existing infrastructure for the website (like a server, database, etc.) that we need to take into consideration?

6. Do you have a preference for hosting the chat agent? Options could include a cloud provider such as AWS, GCP, or Azure, or a server you already own.

7. Finally, what is your level of expertise in programming and web development? This will help me adjust the complexity and pace of the instruction.

That's some great information! TypeScript is a strong choice as it brings static typing to JavaScript, leading to more maintainable code.

A few more questions to make sure we're on the right track:

1. What information will the chatbot need to ask or gather from the user in order to recommend the right course? Some examples could be their role, experience with agile practices, what they hope to gain from the course, etc.

2. Do you have an existing database of your courses, with all the metadata (like target audience, difficulty level, topics covered, etc.) that the chatbot could use to recommend a course?

3. Considering that your website is based on WordPress, would you prefer to use a plugin or custom solution for the chat interface, or are you open to a third-party tool or service?

4. How do you envision the chat flow? Do you prefer a mostly automated experience, or will there be points where a human may need to step in?

5. Finally, in terms of deployment, would you prefer to use cloud platforms such as AWS, Azure, GCP, or are you comfortable with setting up and maintaining a server?

These questions will help us design the right chatbot solution for your needs.

Great! Here are a few more queries:

1. For the chat interface, there are generally two options: A) Using a WordPress plugin or third-party service which might be simpler to set up but could be less flexible or potentially incur additional costs, or B) Developing a custom chat interface which would provide the most flexibility and integration but would likely require more development and maintenance. Since you're not a beginner, a custom interface using a JavaScript or TypeScript library might be a good fit. Would this be okay with you?

2. Will the chatbot need to remember past interactions with a user, or will each chat session be independent?

3. Do you want the chatbot to be able to handle free-form input (users typing their own responses) or would you prefer a more guided approach (where the chatbot presents the user with predefined options to choose from)?

4. If we decide to use a cloud platform, Microsoft's Azure could be a good choice as it integrates nicely with Visual Studio. They offer a service called "Azure Bot Service" which we could use to host the bot, and they also provide the Bot Framework SDK that we could use to build the bot in TypeScript. Does that sound good?

5. You mentioned training the chatbot on your courses at startup. To clarify, this would be a simpler form of training where the chatbot learns to associate certain keywords or phrases with specific courses. This is different from machine learning, where the bot would learn to understand and generate human-like text from a large amount of data. For the latter, we would need much more data and computational resources. Are you okay with the simpler approach, or were you envisioning something else?

Your answers to these questions will help me guide you through building your chatbot.

Great, thank you for answering those questions! Your responses provide a clearer picture of the chatbot we're going to create. Here is a general plan we will follow:

1. We will create a chatbot using Microsoft's Bot Framework in TypeScript. This will provide the structure for our bot and will allow us to handle user messages.

2. We will create a simple interface on your WordPress site for users to interact with the bot. We will use REST APIs to communicate with the bot hosted on Azure.

3. We'll use your course web pages data at startup to map keywords or phrases to specific courses. This will be the 'knowledge' of our bot.

4. The chatbot will be hosted on Azure Bot Service, which integrates nicely with Visual Studio and supports deployment from there.

Let's start with the first step. Here's a general outline of the process:

1. First, install Node.js and npm (node package manager) if they are not already installed. You can download them from the official website. After installation, you can verify the installation by opening a terminal and running:

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node -v
npm -v

It should display the versions of Node.js and npm respectively.

2. Install Yeoman and the Bot Framework Yeoman generator. Yeoman is a tool for generating applications. The Bot Framework Yeoman generator will create a basic chatbot application structure for you.

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npm install -g yo generator-botbuilder

3. Run the generator to create a new bot application. Navigate to the directory where you want your application to live, then run:

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yo botbuilder

The generator will ask you some questions. For the programming language, choose TypeScript. For the template, choose "Echo Bot" for now - this will create a simple bot that just repeats back whatever it receives.

Let me know when you've completed these steps or if you encounter any difficulties.

Fantastic! Now, we have the basic structure for our chatbot. Let's proceed to the next steps:

1. Now that we've set up the basic bot, let's open the project in Visual Studio Code. Navigate to the root of the project and open it by typing:

   bashCopy code
   code .
   

2. In Visual Studio Code, take a look at the project structure. The primary files for the chatbot logic are in the src folder. The index.ts file is the entry point of the application, and the bot.ts file contains the main bot logic.

3. Open bot.ts. This file is where you'll add most of your code for the chatbot. Currently, as an echo bot, it merely sends back the user's input.

4. Modify the bot to say hello to the user when they first message the bot. Look for the onMessage function in bot.ts - this function is called when the bot receives a message from the user. The code inside this function currently sends back an echo message. Replace the onMessage function with the following code:

   typescriptCopy code
   this.onMessage(async (context, next) => {
       const replyText = `Echo: ${ context.activity.text }`;
       await context.sendActivity(MessageFactory.text(replyText, replyText));
       await next();
   });
   

   with:

   typescriptCopy code
   this.onMessage(async (context, next) => {
       if (context.activity.text === 'hi') {
           const replyText = `Hello! How can I assist you today?`;
           await context.sendActivity(MessageFactory.text(replyText, replyText));
       } else {
           const replyText = `Sorry, I didn't understand that.`;
           await context.sendActivity(MessageFactory.text(replyText, replyText));
       }
       await next();
   });
   

5. Now, the bot will respond with a greeting when the user says "hi", and with a message indicating confusion for any other input.

6. To test your bot locally, you can use the Bot Framework Emulator, a desktop application that you can use to test and debug your bot. You can download it from here.

7. Once you've downloaded and installed the emulator, you can run your bot locally by typing npm start in the terminal at the root of your project. The bot should start, and you should see a message with its URL (usually http://localhost:3978/api/messages).

8. Open the Bot Framework Emulator and connect to your bot by entering the bot's URL. You can now test your bot!

Let me know if you have any problems or when you're ready to move on to the next steps.

I apologize for the confusion. The code . command opens the current directory in Visual Studio Code. It works if you have added code to your PATH when you installed Visual Studio Code. If that isn't the case, you can open Visual Studio Code manually and then go to File -> Open... and navigate to the directory where your bot is located.

Alternatively, you can add code to your PATH:

1. Open Visual Studio Code.
2. Press Cmd + Shift + P to open the Command Palette.
3. Type shell command to find the Shell Command: Install 'code' command in PATH command.
4. Select the Shell Command: Install 'code' command in PATH command.
5. After that, you should be able to use the code . command in the terminal to open Visual Studio Code.

Let me know if this helps or if you need further assistance.

Great! Take your time and don't hesitate to reach out if you encounter any difficulties or have any questions. I'll be here to help. Once you've tested your bot locally and are ready, we'll move on to the next steps: customizing the bot to use course data and deploying the bot to Azure.

The error you're seeing usually means that you're not in the right directory in the terminal when you're running npm start. This command should be run from the root directory of your bot project, where the package.json file is located.

Here's what you can do:

1. Use the cd command in your terminal to navigate to the root directory of your bot project. For example, if your bot project is in a directory named my-bot-project on your desktop, you would type cd Desktop/my-bot-project.

2. Once you're in the correct directory, try running npm start again.

Let me know if that works!

It seems like there's a compatibility issue between the version of Restify (a module used by Bot Framework) and the version of Node.js that you're using.

Given that your Node.js version (19.8.1) is a newer one, it may be causing issues with the older dependencies. We can solve this by downgrading to a more stable version of Node.js.

To manage multiple versions of Node.js on your system, I would recommend using a version manager like nvm (Node Version Manager).

Here are the steps to install nvm and use it to install a more compatible version of Node.js:

1. To install nvm, you can use the curl command:

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   curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.1/install.sh | bash
   

2. Close your terminal and open a new one. Verify that nvm is installed by typing:

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   command -v nvm
   

   This should return 'nvm', indicating that nvm is installed.

3. Install Node.js version 14, which is a Long Term Support (LTS) version, by typing:

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   nvm install 14
   

4. Verify that the new version of Node.js is being used by typing:

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   node -v
   

   It should return 'v14.x.x'.

5. In your bot's project directory, delete the node_modules directory and the package-lock.json file. You can do this with the following commands:

   bashCopy code
   rm -rf node_modules
   rm package-lock.json
   

6. Reinstall the project dependencies by typing:

   bashCopy code
   npm install
   

7. Now, try running your bot again by typing:

   bashCopy code
   npm start
   

Let me know if you encounter any difficulties or when you're ready to proceed.

Great, your bot server is now running! The message restify listening to http://[::]:3978 means the bot is running and listening for incoming requests at http://localhost:3978.

Now, to interact with your bot, you'll need the Microsoft Bot Framework Emulator. If you haven't installed it yet, you can download it from here.

Once the Bot Framework Emulator is installed, follow these steps:

1. Open the Bot Framework Emulator.
2. Click on "Open Bot" on the welcome screen.
3. In the modal that appears, enter your bot's URL, http://localhost:3978/api/messages, into the "Bot URL" field.
4. Click "Connect".

You should now be able to chat with your bot in the emulator!

Just type 'hi' into the chat and the bot should respond with "Hello! How can I assist you today?". If you type something else, the bot will respond with "Sorry, I didn't understand that."

Please let me know if you encounter any difficulties or when you're ready to move on to the next steps.

Apologies for the confusion, it seems there may have been a miscommunication in the instructions provided. Please let's recheck the modifications in the bot.ts file.

Here is the correct onMessage function which responds to "hi" and default response for all other inputs:

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this.onMessage(async (context, next) => {
    if (context.activity.text.toLowerCase() === 'hi') {
        const replyText = `Hello! How can I assist you today?`;
        await context.sendActivity(MessageFactory.text(replyText, replyText));
    } else {
        const replyText = `Sorry, I didn't understand that.`;
        await context.sendActivity(MessageFactory.text(replyText, replyText));
    }
    await next();
});

Please ensure your onMessage function looks like the code above. Once you've made these changes, save the file and restart the bot server by running npm start in your terminal.

Again, apologies for the confusion and let me know if it's working correctly now or if you need further assistance.

To do a clean build, you'll want to delete the generated lib directory and then rebuild your code. Here's how you can do it:

1. First, stop the server if it's running by pressing Ctrl+C in the terminal.

2. Delete the lib directory. This directory contains the compiled JavaScript files that are generated when you run tsc or npm start. You can delete it with the following command:

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   rm -rf lib
   

3. Now rebuild your project. This will recompile your TypeScript files and regenerate the lib directory. You can rebuild the project with the following command:

   bashCopy code
   npm run build
   

4. Finally, start your server again:

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   npm start
   

Please let me know if this works or if you encounter any other issues.

Great! Now that we have a basic chatbot set up and responding as expected, the next steps are to train the bot to respond more intelligently, taking into account the user's inquiries about different courses.

One of the simplest ways to provide the bot with some level of 'intelligence' is to train it to identify keywords in user messages and respond accordingly. For instance, we could map some keywords to each course, such as 'agile', 'scrum', 'kanban', 'product owners', 'scrummasters', 'programmers', and 'management'. The bot could then recommend the appropriate course based on the keywords it identifies in a user's message.

Here's a rough example of how you might modify the onMessage function in bot.ts to implement this:

typescriptCopy code
this.onMessage(async (context, next) => {
    const text = context.activity.text.toLowerCase();

    let replyText = '';

    if (text.includes('agile')) {
        replyText = 'You might be interested in our Agile courses. Here are some options: [list of agile courses].';
    } else if (text.includes('scrum')) {
        replyText = 'You might be interested in our Scrum courses. Here are some options: [list of scrum courses].';
    } else if (text.includes('kanban')) {
        replyText = 'You might be interested in our Kanban courses. Here are some options: [list of kanban courses].';
    } else {
        replyText = 'Sorry, I didn\'t understand that. Could you please tell me more about what you\'re looking for?';
    }

    await context.sendActivity(MessageFactory.text(replyText, replyText));
    await next();
});

This is a simple example and your actual implementation would likely be more complex. For instance, you might need to use regular expressions instead of simple string comparison to identify keywords, and you'd need to replace [list of ... courses] with actual links to the relevant courses.

This approach could provide a good starting point, but keep in mind that it is very basic and might not be adequate for more complex inquiries. For instance, it doesn't handle situations where a user's message contains multiple keywords, and it doesn't understand synonyms, misspellings, or other complexities of natural language.

To handle these and other complexities, you might need to use a more advanced approach, such as using a machine learning model to classify user messages. This could involve training a model on a large dataset of example messages and responses, or using a pre-trained model from a service like Microsoft LUIS (Language Understanding Intelligent Service) or Google's Dialogflow.

Once you've got the bot responding more intelligently to user messages, the next steps would be to deploy the bot to Azure and integrate it with your WordPress site.

Before we proceed, please try to modify your bot as suggested and let me know how it goes. You can test your bot using the Bot Framework Emulator as before. If you encounter any issues, I'll be here to help.

Fantastic! Now that your bot is working locally, let's deploy it to Azure.

The steps to do this are as follows:

1. Create a Resource Group in Azure

   You need to create a new Resource Group in your Azure subscription. This is a container that holds related resources for an Azure solution.

   • Sign in to the Azure portal
   • In the left menu, click on "Resource Groups"
   • Click on the "+ Add" button to create a new Resource Group
   • Choose your subscription, give your Resource Group a name and select a region, then click "Review + Create"
   • After reviewing, click "Create"

2. Create a Web App Bot

   • In the Azure portal, click on "Create a resource" in the top left corner
   • Search for "Web App Bot", and click create
   • Fill in the form with the following settings:
     • Bot handle: Choose a unique name for your bot
     • Subscription: Choose your Azure subscription
     • Resource Group: Choose the Resource Group you just created
     • Location: Choose a location (same as your Resource Group's location)
     • Pricing tier: F0 (10K Premium Messages)
     • App name: Same as your Bot Handle
     • Bot template: Choose "Echo Bot" (we'll replace this with your own bot later)
     • Azure Storage: Create a new one with default settings
     • Application Insights: Off
     • Microsoft App ID and password: Auto create App ID and password
   • Click "Create" and wait for Azure to deploy your bot

3. Deploy your bot to Azure

   To deploy your bot, you'll need to use the Azure CLI and the az bot command. Here are the steps:

   • Install the Azure CLI from here if you haven't already

   • Open a terminal and login to your Azure account using the az login command

   • Navigate to your bot's root directory

   • Run the following command to deploy your bot:

     bashCopy code
     az bot publish --name "<Your Bot Handle>" --resource-group "<Your Resource Group Name>" --code-dir "."
     

   • Wait for the deployment to complete

After these steps, your bot should be running on Azure. To verify that it's working, you can test it in the Azure portal:

• Navigate to your bot in the Azure portal
• In the left menu, click on "Test in Web Chat"
• Try sending some messages to your bot and make sure it responds correctly

Please try these steps and let me know if you have any issues. After we've got your bot running on Azure, the next step will be to integrate it with your WordPress site.

Yes, I apologize for the confusion. Microsoft has changed some names and concepts in the Azure Portal since my training cut-off in September 2021. The "Web App Bot" is now referred to as "Azure Bot".

Please proceed with creating an "Azure Bot". The setup process should be similar to the steps outlined before. Let me know if you need any additional guidance during the process.

I apologize for the confusion earlier. It seems like Azure CLI's az bot publish command is deprecated for v4 bots and Microsoft recommends using az webapp instead. This changes our deployment process a bit. Here's the revised step-by-step guide to deploy your bot to Azure using Azure CLI and Azure Web Apps:

Prerequisites:

• You need to have Node.js and npm (which comes with Node.js) installed on your machine.
• Install Azure CLI from here if you haven't already.

1. Login to Azure CLI

   Open your terminal and use the following command to log in. A browser window will open for you to complete the authentication.

   bashCopy code
   az login
   

2. Create a Web App

   Use the following command to create a web app in Azure. Replace <app-name> with a unique name for your web app (this will be part of the URL for your web app) and <resource-group> with the name of your Resource Group:

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   az webapp create --name <app-name> --resource-group <resource-group> --plan <resource-group>_plan --runtime "NODE|14-lts"
   

3. Enable Web Sockets

   The Bot Framework SDK uses Web Sockets to communicate with the bot, so you need to enable Web Sockets for your web app:

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   az webapp config set --name <app-name> --resource-group <resource-group> --web-sockets-enabled true
   

4. Deploy your bot to Azure

   • Navigate to your bot's root directory and install the required npm packages by running:

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     npm install
     

   • Add a .deployment file to the root of your project with the following content:

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     [config]
     command = npm install && npm run build && npm start
     

   • Add the following scripts to your package.json:

     jsonCopy code
     "scripts": {
       "start": "node ./lib/index.js",
       "build": "tsc --build",
       "postinstall": "npm run build"
     },
     

   • Commit your changes if your code is in a git repository. If not, initialize a git repository in your project folder with the following commands:

     bashCopy code
     git init
     git add .
     git commit -m "Initial commit"
     

   • Use the following command to deploy your bot from your local git repository to Azure. Replace <app-name> with your app name and <resource-group> with your resource group name:

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     az webapp deployment source config-local-git --name <app-name> --resource-group <resource-group>
     

   • This will return a git URL in the "url" field of the output. Use this URL to push your local git repository to Azure:

     bashCopy code
     git push <git-url> master
     

5. Configure the Messaging Endpoint

   • In the Azure portal, navigate to your Azure Bot resource.
   • In the left menu, click on "Channels".
   • In the "Bot Service" section, click on "Edit" next to "Web Chat".
   • In the "Messaging Endpoint" field, enter the URL of your web app (which is https://<app-name>.azurewebsites.net/api/messages), and then click "Save".

Please follow these steps to deploy