Could we make a framework for using the MS server 2022 AI components to run LLMs in an IIS publishing instance of an AI?

Yes, it is possible to build a framework for running Large Language Models (LLMs) using Microsoft Server 2022 AI components within an IIS (Internet Information Services) instance. Here’s a structured approach to making it work:

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framework for Running LLMs on MS Server 2022 with IIS

1. System Requirements

Before setting up, ensure your server has:

• Windows Server 2022 with IIS installed.
• (such as ONNX Runtime, Windows ML, or DirectML for acceleration).
• A GPU (optional but recommended) if leveraging CUDA, DirectML, or ONNX acceleration.
• .NET Core 6/7+ or Python for hosting AI inference.
• LLM Model Files (e.g., GPT-2, GPT-3, Llama, or a smaller ONNX-converted model).

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2. Setting Up IIS for AI Model Hosting

IIS (Internet Information Services) can serve an AI inference API by hosting an application (asp.net Core, FastAPI via IIS, or Flask with WSGI).

Steps to configure IIS for LLM API hosting:

1. Enable IIS on Windows Server 2022:

   Install-WindowsFeature -name Web-Server -IncludeManagementTools
   

2. Ensure IIS supports .NET and python apps:
   • Install the .NET Core Hosting Bundle if using asp.net.
   • Install WSGI or FastCGI for python-based LLM services.

4. Deploy an AI Web Service in IIS:

6. • Deploy an asp.net API (C#) or Flask/FastAPI (python) for model inference.Ensure the AI model is preloaded on the backend.The AI API should expose endpoints such as:
     

     POST /predict   → Takes input text, returns LLM-generated response
     

   




7. Set IIS Application Pool to Use the Right python or .NET Runtime

   • If running python, set IIS to use FastCGI or WSGI.
   
   
   • If using .NET, ensure the AI module is inside an asp.net Core application.

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