You can easily implement external authentication providers to allow the users of your Blazor application to log in with Facebook, Google, Microsoft, Twitter, and many others. Simply follow the directions here: Facebook and Google authentication in ASP.NET Core | Microsoft Docs . However, you have to write custom code to associate an external login to an existing login. The method, covered here, will ask the user to enter the password of the existing account to make the association. Note:

You can easily embed Power BI reports into a Server Side Blazor Application. This method allows you to display a Power BI report without requiring the user to have a Power BI account. Note: To move to production you'll need a capacity .   Set-Up For The Application To set up to run the sample application, we follow the directions in this article: Embed Power BI content with service principal and an application secret . The first step is to start with a Power

Local Internal AI Chat Bot is a Blazor web application designed to bring the power of AI-driven chat and knowledge retrieval to your local environment. Leveraging Ollama hosting a phi3.5 model and advanced vector search, this project enables users to interact with a chat bot that can answer questions using custom, user-provided data. Documents are chunked, embedded, and stored for fast semantic search, ensuring relevant and accurate responses. The interface, built with Radzen

In this post, we’ll explore how to build a dynamic Python execution environment using .NET MAUI, Pyodide, Monaco, and Radzen. This builds upon the concepts introduced in the article Building a Dynamic Python Execution Environment with .NET MAUI, Pyodide, Monaco, and Radzen . We’ll focus on the implementation details of the DataExample.razor and index.html files, which enable users to load data files, dynamically generate Python scripts, and execute them in a browser environment.

Introduction and Overview In this blog post, we will explore how to build a dynamic Python execution environment using .NET MAUI. This project allows users to write Python code in a Monaco Editor, execute it in the browser using Pyodide, and display the results in a Radzen DataGrid. The application is designed to provide a seamless experience for running Python scripts, with a focus on data manipulation using Pandas. Key features of this project include: A rich code editor powered