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Running a fully local AI Code Assistant with Continue–Part 6–Troubleshooting

In a previous posted I introduced you to Continue in combination with Ollama, as a way to run a fully local AI Code Assistant. Remark: This post is part of a bigger series. Here are the other related posts: Part 1 – Introduction Part 2 -  Configuration Part 3 – Editing and Actions Part 4  -  Learning from your codebase Part 5 – Read your documentation Part 6 (this post) – Troubleshooting Although Continue really looks promising, I stumbled on some hurdles along the way. Here are some tips in case you encounter issues: Tip 1 - Check the Continue logs My first tip is to always check the logs. Continue provides good logging inside the IDE, So go to the output tab and switch to the Continue source to get the generated output: Tip 2 – Check the Continue LLM logs Next to the output of Continue itself, you can find all the LLM specific logs in the Continue LLM Prompt/Conversation output. So don’t forget to check that output as well: Tip 3 – Be patient
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Running a fully local AI Code Assistant with Continue–Part 5–Read your documentation

In a previous posted I introduced you to Continue in combination with Ollama, as a way to run a fully local AI Code Assistant. Remark: This post is part of a bigger series. Here are the other related posts: Part 1 – Introduction Part 2 -  Configuration Part 3 – Editing and Actions Part 4  -  Learning from your codebase Part 5 (this post) – Read your documentation Today I want to continue by having a look at how Continue can scrape your documentation website and make the content accessible inside your IDE The @docs context provider To use this feature you need to use the @docs context provider: Once you type @docs you already get a long list of available documentation: This is because Continue offers out-of-the-box a selection of pre-indexed documentation sites. (You can find the full list here ) If you now ask a question, the indexed documentation is used to answer your question: You can see the context used by expanding the context items section: Index you

Hangfire–Change polling interval

In modern .NET applications, background processing plays a crucial role in handling tasks that don't need to be executed immediately, such as sending emails, processing large datasets, or scheduling recurring jobs. A library I like to use to manage background tasks in .NET is Hangfire , thanks to its simplicity, flexibility, and wide range of storage options. As these background tasks can be scheduled in the future, some kind of storage needs to be configured where Hangfire keeps all the information related to background job processing. Out of the box multiple storage systems are supported, one of them being SQL Server . Although using SQL Server can be a convenient option to use as the main storage for your Hangfire, it comes with one big disadvantage:  Polling is used to fetch new jobs. This has 2 consequences: It increases the load on your SQL server instance The time to pickup a new job and execute it  is signifcantly longer(here is a comparison with Redis from t

Microsoft Student Innovator Series

If you are a student and enthusiastic about AI and Cloud in general and Microsoft technologies specifically, than I would encourage you to check out the Microsoft Innovator Series . This series offers a range of events that can help you improve your technical skills and are a good headstart for the Imagine Cup , Microsoft's premier global technology startup competition for student founders. There are still some events planned between now and the end of this year, so certainly have a look!   More information Event Series | Microsoft Reactor A Journey of Innovation and Inspiration with Microsoft Imagine Cup 2025 - Microsoft Community Hub

Semantic Kernel–Plugin KeyNotFoundException

Plugins are a key element when building agents in Semantic Kernel. They allow you to extend the capabilities of your Large Language Model with extra functions. This post is not about writing your own plugin but Just as a reminder, registering a plugin can be done like this: Here is the code I used to try to invoke the TimePlugin in a prompt: However when I did this the following error was returned: System.Collections.Generic.KeyNotFoundException: 'The plugin collection does not contain a plugin and/or function with the specified names. Plugin name – 'time', function name - 'Date'.' The problem is caused because I had configured an alias name for the plugin but I was using the plugin name in the prompt. I have 2 ways to fix the issue above. Either I update the prompt to point to the configured alias: Or I remove the alias from my configuration: Hope that helps… More information Plugins in Semantic Kernel | Microsoft Learn

Web Deploy error - Source does not support parameter called 'IIS Web Application Name'.

At one of my customers, everything is still on premise hosted on multiple IIS web servers. To deploy web applications, we are using Web Deploy . This works quite nicely and allows us to deploy web application in an automated way. Last week, a colleague contacted me after configuring the deployment pipeline in Azure DevOps. When the pipeline tried to deploy the application, it failed with the following error message: "System.Exception: Error: Source does not support parameter called 'IIS Web Application Name'. Must be one of (Environment)" Here is a more complete build log to get some extra context: Starting deployment of IIS Web Deploy Package : \DevDrop\BOSS.Intern.Web.zip">\DevDrop\BOSS.Intern.Web.zip">\DevDrop\BOSS.Intern.Web.zip">\DevDrop\BOSS.Intern.Web.zip">\\<servername>\DevDrop\BOSS.Intern.Web.zip Performing deployment in parallel on all the machines. Deployment started for machine: <servername> with port

MassTransit ConsumerDefinitions vs EndpointConfiguration - Understanding the Differences

In message-driven systems, configuring consumers correctly is key to achieving maintainable, scalable, and flexible systems. In MassTransit, two common approaches to achieve this are using ConsumerDefinitions and Endpoint configuration . While both serve the purpose of defining how consumers work within the system, they differ in terms of flexibility, separation of concerns, and implementation details. In this post, we’ll explore the differences and best practices for using them. MassTransit Consumers: The Basics Before diving into the comparison, let’s briefly cover what a consumer is in MassTransit. A consumer is a class responsible for handling incoming messages in a message broker (such as RabbitMQ or Azure Service Bus). Consumers are central to the processing pipeline and play a key role in event-driven architectures. Here is a simple example: Consumer Configuration The question is now how will this consumer be wired to the underlying transport mechanism. As mentioned