2025-03 on Funky Si's Blog (Dev)

Automate social posts with AI in .NET

funkysi1701@gmail.com (funkysi1701) — Mon, 17 Mar 2025 20:00:00 +0000

Automating repetitive tasks is one of the best ways to save time and focus on what matters most. In this blog, I’ll show you how I used AI with .NET to automate the creation of social media posts for my blog. By leveraging my blog’s RSS feed, OpenAI, and Semantic Kernel, I was able to generate engaging posts effortlessly. Let’s dive in!

Let’s look at a way to use AI for a practical use. For the last few weeks I have been using AI to help me write social media posts to promote my latest blog posts, let’s look at how I might automate this using .NET code.

My blog publishes new posts to a rss feed, I can consume this from .NET code and pass it to AI, and create social media posts from them.

My blog is written in Hugo and it is already generating an rss feed, however I have made a slight tweak to it. I want the tags from the blog article to be used as hashtags in any social media posts. I am storing the tags in the rss field category.

<category term="tagname">tagname</category>

And here is the section of code that generates my rss feed, the key tags I will be using are title, link, category and description.

<item>
 <title>{{ .Title }}</title>
 <link>{{ .Permalink }}</link>
 <author>{{ with .Params.author }}{{ . }}{{ else }}{{ with $.Site.Author.name }}{{.}}{{end}}{{end}}</author>
 <pubDate>{{ .Date.Format "Mon, 02 Jan 2006 15:04:05 -0700" | safeHTML }}</pubDate>
 {{ with .Site.Author.email }}<author>{{.}}{{ with $.Site.Author.name }} ({{.}}){{end}}</author>{{end}}
 <guid>{{ .Permalink }}</guid>
 {{- range .Params.tags -}}
 <category term="{{ replace . " " "" }}">{{ replace . " " "" }}</category>
 {{ end }}
 <description>{{ .Content | html }}</description>
</item>

I am using the nuget package CodeHollow.FeedReader , this allows me to pass in a URL to my rss feed, and get an object out which contains all the items in the feed. Using a nuget package saves me doing a lot of parsing of XML. The method I am using takes an input string something like https://www.funkysi1701.com/index.xml , and gives me an object I can query and do things with.

var RSSFeed = await FeedReader.ReadAsync(FeedStringValue);

RSS feed contains the following properties I want to use: Title, Link, Categories and Description. All are strings, except Categories which is an ICollection<string> This matches what I said I wanted to use from the rss feed.

I want to pass the description to AI, and then combine the Response from AI with URL of the blog post and a comma separated list of ‘hashtags’ (the categories in my rss feed).

Initially I thought about using ollama , this is an example of a LLM (Large Language Model) that you can install on your laptop, sometimes called a Small Language Model (SLM). However, I found this to be unreliable with my laptop and caused several system wide crashes. I assume this is due to memory usage and the size of the model. LLMs or SLMs do require a lot of system resources so this is not completely surprising. I will revisit this at some point as I would like to learn more about ollama.

I already have an account on OpenAI and some credit so let’s try that instead. I have made a fair few requests using OpenAI and so far it has cost me 11p, I don’t think for my usage it is going to break the bank. If I was going to put something on the public internet I may have to reconsider but for my own personal use I think this should be fine.

Next step, how do I talk to OpenAI from .NET. I know of two approaches, Semantic Kernel and the new Microsoft.Extensions.AI libraries introduces in .NET 9 https://devblogs.microsoft.com/dotnet/introducing-microsoft-extensions-ai-preview/ . Semantic Kernel is what I am using here, however I do want to explore the newer libraries at some point.

Semantic Kernel with OpenAI needs the following Nuget package: Microsoft.SemanticKernel.Connectors.OpenAI

In my Program.cs I had the following to register and add to dependency injection.

if (builder.Configuration.GetValue<string>("OpenAI:Key") != string.Empty)
{
 builder.Services.AddOpenAIChatCompletion(
 modelId: builder.Configuration.GetValue<string>("OpenAI:Model") ?? string.Empty,
 apiKey: builder.Configuration.GetValue<string>("OpenAI:Key") ?? string.Empty
 );
}

builder.Services.AddTransient((serviceProvider) => new Kernel(serviceProvider));

OpenAI:Key is your API Key, which can be found from the OpenAI site, https://platform.openai.com/api-keys OpenAI:Model is the model I am using, in my case “gpt-4o”, I’ve added it as a config option as I may find I want to change it.

Now in the code where I want to call OpenAI I can just inject SemanticKernel and call its async methods. I am a backend developer, so I created a simple API that allows me to call it.

public class AIHandler(Kernel kernel)
{
 public async Task Handle(string request, CancellationToken cancellationToken)
 {
 var response = await kernel.InvokePromptAsync(request, cancellationToken);
 // Do something with the response...
 }
}

Now the only step I am missing is what string or prompt do I want to pass to OpenAI?

I want a social media post that will fit into a facebook/twitter/bluesky etc post, some of these services are character limited so I have included a character limit in my “prompt”, however I am being clever and counting the number of characters taken up by the URL and hashtags and subtracting that first.

string socialMediaPrompt = $"write a social media post under {240 - length} characters, excluding hash tags about {feedItem.Description}"

Now once I put is all together I have a page that loads my rss feed, and I can click a button to generate a social media post.

Conclusion

By combining .NET, Semantic Kernel, and OpenAI, I was able to automate the creation of social media posts, saving time and effort. This approach can be adapted for other use cases, such as summarizing content or generating marketing copy.

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Merge two Git projects, keep history

funkysi1701@gmail.com (funkysi1701) — Mon, 10 Mar 2025 20:00:00 +0000

I needed to merge two separate projects into one repository while keeping the full commit history from both sides. Copy-paste would have worked for the files, but history would have stayed trapped in the old remotes.

This approach adds the second repo as a remote, fetches it, and merges with --allow-unrelated-histories so Git keeps both lineages. I still refer to the repos as project1 and project2, with remotes at project1Url and project2Url.

Step 1: Clone the original repository

First, clone the repository of project1:

git clone project1Url

Step 2: Add the new repository as a remote

Next, add the repository of project2 as a remote:

git remote add project2 project2Url

Step 3: Fetch the commits from the new repository

Fetch the commits from the project2 repository:

git fetch project2

Step 4: Merge the commits from the new repository

Merge the commits from the project2 repository into project1. Point at the branch that holds the code you want (often main or develop):

git merge project2/develop --allow-unrelated-histories

Step 5: Fix merge conflicts

If there are conflicts, you will need to resolve them. In my case, this was mainly build files and scripts in the root of the repository. Most of the important code was in subfolders, so this was minimal.

Step 6: Push the changes to the original repository

Push the changes to a new branch for review before merging into the main branch:

git checkout -b feature/merge-project2-into-project1
git push origin feature/merge-project2-into-project1

Step 7: Clean up

Test your code to ensure everything builds and runs as expected now that it is all in one repository. Create a pull request and review all the changes to ensure nothing gets changed that shouldn’t be.

When you look at your PR, it will look like a lot of code has been added. However, if you look closely at the Git history of those files, you will see that the history has been preserved from the original repository. You can remove the temporary project2 remote once you no longer need it (git remote remove project2).

Conclusion

This is still one of the simplest ways to combine two codebases without throwing away history. Use it when consolidating services or folding a spike repo into the main project; open a PR so reviewers can see the merge conflicts and folder layout before it lands on the default branch.

Once the histories live in one repo, automated promotion helps: see automatic pull requests for GitHub Actions and Azure DevOps patterns, and using GitHub Actions if you are wiring CI around the merge.

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2025-03 on Funky Si's Blog (Dev)

Automate social posts with AI in .NET

Using OpenAI for Social Media Posts

Conclusion

Merge two Git projects, keep history

Step 1: Clone the original repository

Step 2: Add the new repository as a remote

Step 3: Fetch the commits from the new repository

Step 4: Merge the commits from the new repository

Step 5: Fix merge conflicts

Step 6: Push the changes to the original repository

Step 7: Clean up

Conclusion

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