OpenAI-API-dotnet VS OpenAI-DotNet

Can't say I've compared them to one another, but OpenAI by OkGoDoIt has bee pretty easy to use.

I'm keen to tinker around on the ChatGPT space, and I managed to build something pretty good in C# using this plugin. https://github.com/OkGoDoIt/OpenAI-API-dotnet It has an Angular front end on the client and allows the user to query ChatGPT. So far so good.

Are you familiar with https://github.com/OkGoDoIt/OpenAI-API-dotnet?

One such library is available on GitHub: OpenAI-API-dotnet. This package is designed to work seamlessly with .NET applications, making it easy for you to integrate Chat-GPT into your project.

I'm happy to point people in the direction of what was used, this used OpenAI GPT API using: https://github.com/OkGoDoIt/OpenAI-API-dotnet and the backend AI service is built in ASP Core and interacts with actual WoW data stored in a MySQL database to build the prompts using various bits of info about the targeted NPC and current player.

On this topic, when developing with the OpenAI API in .NET like with this library at Github, I was pleasantly surprised just how easy it is to customize a chat bot. As in... Super simple. The ChatGPT API simply takes what they call a "System" message and this sets up the personality of the bot. E.g. "You are a librarian, eager to answer any questions. You refuse to discuss topics not pertaining to literature." One can also populate it with a leading conversation to run off with.

I'm baffled, what am I doing wrong here? Shouldn't this emulate similar results to ChatGPT? I am using the following NuGet for OpenAI access: https://github.com/OkGoDoIt/OpenAI-API-dotnet

In Visual Studio you can install a NuGet package which allows you to connect with OpenAI it is documented here https://github.com/OkGoDoIt/OpenAI-API-dotnet the caveat is that you need to write your app using C#, there are many places you can convert vb.net to C# until you get the hang of C#, you'll get it in no time, I am sure.

Okay, now we've confirmed the API endpoint is working, let's connect it to OpenAI first, install the OpenAI package, navigate to the route directory, and run the command below in our terminal

You can obtain an OpenAI API key by visiting the OpenAI website.

OpenAI Account: Register for an OpenAI account to utilize AI-powered features in your ToolJet applications. Sign up here.

KodiBot is a desktop app that enables users to run their own AI chat assistants locally and offline on Windows, Mac, and Linux operating systems. KodiBot is a standalone app and does not require an internet connection or additional dependencies to run local chat assistants. It supports both Llama.cpp compatible models and OpenAI API.

At this point, probably everyone has heard about OpenAI, GPT-4, Claude or any of the popular Large Language Models (LLMs). However, using these LLMs in a production environment can be expensive or nondeterministic regarding its results. I guess that is the downside of being good at everything; you could be better at performing one specific task. This is where HuggingFace can utilized. HuggingFace provides open-source AI and machine learning models that can easily be deployed on HuggingFace itself or third-party systems such as Amazon SageMaker or Azure ML.  You can interface with these deployments through an API and control the scaling of these models, which makes them perfectly suited for production environments. These models range in size but are generally small AI models that are good at doing one specific task. With capabilities to fine-tune these models, or use the pre-trained model for specific tasks, embedding them into various applications becomes more efficient, enhancing automation and performance. Combining these models can create new and intricate AI applications. In this case, by utilizing HuggingFace models, you wouldn’t have to depend on a production application on a third-party provider such as OpenAI or Google, ensuring a more targeted and customizable approach to deploying deep learning solutions in your operations.