In this module, you set up your development environment to create and build Blazor web apps. You then:
Congratulations on building your first Blazor web app!
In this module, you created an ASP.NET Core web API running on .NET. The web API creates, reads, updates, and deletes pizzas from an in-memory cache.
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You learned that creating a web API with ASP.NET Core entails:
ControllerBase class and that contain methods that respond to HTTP requests.Because this pattern allows you to focus on a single controller action at a time, you can create functional web APIs fairly quickly with a little practice.
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In this module, you used an in-memory cache. This approach helped you to focus on learning web API concepts, but it has some obvious limitations for real-world applications. If the application stops, all your changes are lost!
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This module uses the .NET 8.0 SDK. Ensure that you have .NET 8.0 installed by running the following command in your preferred command terminal:
.NET CLI
dotnet --list-sdks
Output similar to the following example appears:
Console
6.0.317 [C:\Program Files\dotnet\sdk]
7.0.401 [C:\Program Files\dotnet\sdk]
8.0.100 [C:\Program Files\dotnet\sdk]
Ensure that a version that starts with 8 is listed. If none is listed or the command isn’t found, install the most recent .NET 8.0 SDK.
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To set up a .NET project to work with the web API, we use Visual Studio Code. Visual Studio Code includes an integrated terminal that makes creating a new project easy. If you don’t want to use a code editor, you can run the commands in this module in a terminal.
dotnet new webapi -controllers -f net8.0 This command creates the files for a basic web API project that uses controllers, along with a C# project file named ContosoPizza.csproj that returns a list of weather forecasts. If you get an error, ensure that you have the .NET 8 SDK installed. ImportantWeb API projects are secured with https by default. If you have problems, configure the ASP.NET Core HTTPS development certificate.You might receive a prompt from Visual Studio Code to add assets to debug the project. Select Yes in the dialog.The command uses an ASP.NET Core project template aliased as webapi to scaffold a C#-based web API project. A ContosoPizza directory is created. This directory contains an ASP.NET Core project running on .NET. The project name matches the ContosoPizza directory name.You should now have access to these files and directories:Bash-| Controllers -| obj -| Properties -| appsettings.Development.json -| appsettings.json -| ContosoPizza.csproj -| ContosoPizza.http -| Program.cs -| WeatherForecast.csdynamics 365 finance training courses malaysia
dotnet run The preceding command:localhost URL that begins with https.You should get output similar to the following, indicating that your app is running:ConsoleBuilding... info: Microsoft.Hosting.Lifetime[14] Now listening on: https://localhost:7294 info: Microsoft.Hosting.Lifetime[14] Now listening on: http://localhost:5118 info: Microsoft.Hosting.Lifetime[0] Application started. Press Ctrl+C to shut down. info: Microsoft.Hosting.Lifetime[0] Hosting environment: Development If you’re running this app on your own machine, you could direct a browser to the HTTPS link displayed in the output (in the preceding case, https://localhost:7294) to view the resulting page. Remember this port, because you use it throughout the module where {PORT} is used. ImportantCheck the terminal output if you encounter any unexpected behavior. If the build fails or other errors occur, the log file’s information helps you troubleshoot. As you make changes to the code, you’ll need to stop the web API by selecting CTRL+C on the keyboard and rerunning the dotnet run command.https://localhost:{PORT}/weatherforecast You should see JSON output similar to this example:JSON[ { "date": "2021-11-09T20:36:01.4678814+00:00", "temperatureC": 33, "temperatureF": 91, "summary": "Scorching" }, { "date": "2021-11-09T20:36:01.4682337+00:00", "temperatureC": -8, "temperatureF": 18, "summary": "Cool" }, // ... ]dynamics 365 field service training courses malaysia
.http filesIncluded in the project is ContosoPizza.http, a file that is used to test API endpoints through a standard format. .http files are supported in several Integrated development environments (IDEs) including Visual Studio and inside of Visual Studio Code with the REST Client extension installed.
HTTP/1.1 200 OK Connection: close Content-Type: application/json; charset=utf-8 Date: Wed, 17 Jan 2024 16:46:40 GMT Server: Kestrel Transfer-Encoding: chunked [ { "date": "2024-01-18", "temperatureC": -2, "temperatureF": 29, "summary": "Warm" }, { "date": "2024-01-19", "temperatureC": 24, "temperatureF": 75, "summary": "Chilly" }, // .. ]dynamics 365 customer service training courses malaysia
dotnet tool install -g Microsoft.dotnet-httprepl The preceding command installs the .NET HTTP Read-Eval-Print Loop (REPL) command-line tool that you use to make HTTP requests to the web API.httprepl https://localhost:{PORT} Alternatively, run the following command at any time while HttpRepl is running:.NET CLIconnect https://localhost:{PORT} TipIf the HttpRepl tool warns Unable to find an OpenAPI description, the most likely cause is an untrusted development certificate. HttpRepl requires a trusted connection. Before you can continue, you must configure your system to trust the dev certificate with dotnet dev-certs https --trustls The preceding command detects all APIs available on the connected endpoint and lists them, as in the following output:Outputhttps://localhost:{PORT}/> ls . [] WeatherForecast [GET]WeatherForecast endpoint by running the following command:.NET CLIcd WeatherForecast The preceding command shows an output of available APIs for the WeatherForecast endpoint:Outputhttps://localhost:{PORT}/> cd WeatherForecast /WeatherForecast [GET]GET request in HttpRepl by using the following command:.NET CLIget The preceding command makes a GET request similar to going to the endpoint in the browser:OutputHTTP/1.1 200 OK Content-Type: application/json; charset=utf-8 Date: Fri, 02 Apr 2021 17:31:43 GMT Server: Kestrel Transfer-Encoding: chunked [ { "date": 4/3/2021 10:31:44 AM, "temperatureC": 13, "temperatureF": 55, "summary": "Sweltering" }, { "date": 4/4/2021 10:31:44 AM, "temperatureC": -13, "temperatureF": 9, "summary": "Warm" }, // .. ]HttpRepl session by using the following command:.NET CLIexitdotnet terminal in the drop-down list in Visual Studio Code. Shut down the web API by selecting CTRL+C on your keyboard.Now that you created the web API, we can modify it to meet the needs of the pizza web API.
In this module, you extend your agent’s capabilities in Microsoft Copilot Studio by giving it access to tools, learn the difference between the different tools, build a custom prompt, and execute an order cancellation using an agent flow.
This module explains how to:
In this module, you extend your agent’s capabilities in Microsoft Copilot Studio by giving it access to autonomous triggers, customize the agent’s triggers to perform conditionally when specific conditions are met, learn how to test and validate your trigger’s behavior, monitor the agent’s activity, and publish changes to the agent.
This module explains how to:
In this module, you build a conversational agent in Microsoft Copilot Studio, starting with the importing an agent solution, building an agent using natural language, and preparing the agent with knowledge sources to ground its answers in real-world data.
This module explains how to:
Microsoft 365 Copilot Chat makes it easy to build declarative agents that enhance productivity across your organization. In this module, you’ll explore the fundamentals of agent creation using Microsoft 365 Copilot Chat with templates and starting from scratch for a customer service declarative agent.
In this module, you begin building agents in Microsoft 365 Copilot Chat, starting with a template agent, and ending with a custom agent built for customer service scenarios.
Learn Microsoft guidelines for the development of responsible conversational AI, such as chat bots and voice-controlled systems.
In this module, you will:
Discover how to build an autonomous agent by using Microsoft Copilot Studio to transform routine tasks into intelligent, automated workflows. This module introduces the fundamental concepts of autonomous agent capabilities, explores real-world applications, and provides exercises to help you practice building and deploying an agent effectively. Designed for learners with beginner to intermediate experience, this module offers a step-by-step approach to creating an autonomous agent. Throughout this module, you explore the core components of Copilot Studio, gain practical experience in building a no-code autonomous agent, and learn how to deploy and manage it in a live environment.
This module explains how to:
This module describes the setup that’s required to use Azure AI Services for Language to enhance the capabilities of a Microsoft Copilot Studio. Additionally, you’ll learn about Azure AI Services for Language and how to incorporate it into an agent.
Learning objectives
In this module, you’ll:
Explore why using more services is important for your agent functionality.
Learn about Azure AI Services for Language and its capabilities.
Review how to create an agent and prepare it for use with Azure AI Services for Language.
Learn how to call your Azure AI Services for Language service from within an agent with a Power Automate flow.