# Set up your Environment

## In this learning path

- [Introduction](https://learn.arm.com/learning-paths/laptops-and-desktops/win_on_arm_build_onnxruntime/)
- [Set up your Environment](https://learn.arm.com/learning-paths/laptops-and-desktops/win_on_arm_build_onnxruntime/1-dev-env-setup/)
- [Build ONNX Runtime](https://learn.arm.com/learning-paths/laptops-and-desktops/win_on_arm_build_onnxruntime/2-build-onnxruntime/)
- [Build ONNX Runtime Generate() API](https://learn.arm.com/learning-paths/laptops-and-desktops/win_on_arm_build_onnxruntime/3-build-onnxruntime-generate-api/)
- [Run Phi3 Model](https://learn.arm.com/learning-paths/laptops-and-desktops/win_on_arm_build_onnxruntime/4-run-benchmark-on-woa/)
- [Next Steps](https://learn.arm.com/learning-paths/laptops-and-desktops/win_on_arm_build_onnxruntime/_next-steps/)

## Overview
In this Learning Path, you’ll learn how to build and deploy a large language model (LLM) on a Windows on Arm (WoA) machine using ONNX Runtime for inference.

Specifically, you’ll learn how to:
- Build ONNX Runtime and the Generate() API library.
- Download the Phi-3 model and run inference.
- Run the short-context (4K) Mini (3.3B) variant of Phi 3 model.

> **Note**  
> The short-context version accepts shorter (4K) prompts and generates shorter outputs than the long-context (128K) version. It also consumes less memory.

## Set up your development environment
Your first task is to prepare a development environment with the required software.

Start by installing the required tools:
- Visual Studio 2022 (the latest version available is recommended).
- Python 3.10 or higher.
- CMake 3.28 or higher.

> **Note**  
> These instructions were tested on a 64-bit WoA machine with at least 16GB of RAM.

## Install and Configure Visual Studio 2022
Now, to install and configure Visual Studio, follow these steps:

1. Download the latest [Visual Studio IDE](https://visualstudio.microsoft.com/downloads/).
2. Select the **Community** edition. This downloads an installer called `VisualStudioSetup.exe`.
3. Run `VisualStudioSetup.exe` from your **Downloads** folder.
4. Follow the prompts and accept the License Terms and Privacy Statement.
5. When prompted to select workloads, select **Desktop Development with C++**. This installs the **Microsoft Visual Studio Compiler** (**MSVC**).

Refer to [Visual Studio for Windows on Arm](https://learn.arm.com/install-guides/vs-woa/) for more details.

## Install Python
Download and install [Python for Windows on Arm](https://learn.arm.com/install-guides/py-woa/).

> **Note**  
> You’ll need Python version 3.10 or higher. This Learning Path was tested with version 3.11.9.

## Install CMake
CMake is an open-source tool that automates the build process and generates platform-specific build configurations.

Download and install [CMake for Windows on Arm](https://learn.arm.com/install-guides/cmake/).

> **Note**  
> The instructions were tested with version 3.30.5.

You’re now ready to build ONNX Runtime and run inference using the Phi-3 model.