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Co-authored-by: manugaursharma <[email protected]>

Author: maryamziaa

com.unity.ml-agents/Documentation~/Installation.md

@@ -1,53 +1,69 @@
 # Installation
-To install and use the ML-Agents Toolkit, follow the steps below. Detailed instructions for each step are provided later on this page.
+Set up your system to use the ML-Agents Toolkit to train and evaluate machine-learning agents in Unity projects.
 
-1. Install Unity (6000.0 or later)
-2. Install Python using conda (>= 3.10.1, <=3.10.12) - we recommend using 3.10.12
-3. Install ML-Agents using one of the following methods:
+This process includes installing Unity, configuring Python, and installing the ML-Agents packages. Follow the steps in order to ensure compatibility between Unity and the ML-Agents components.
 
-   3.1 Package installation
 
-   3.2 Advanced installation
 
-## 1. Install **Unity 6000.0** or Later
+##  Install Unity
 
-[Download](https://unity3d.com/get-unity/download) and install Unity. We strongly recommend that you install Unity through the Unity Hub as it will enable you to manage multiple Unity versions.
+Install Unity 6000.0 or later to use the ML-Agents Toolkit.
 
-## 2. Install **Python 3.10.12** using Conda
+To install Unity, follow these steps:
 
-We recommend using [conda](https://docs.conda.io/en/latest/) or [mamba](https://github.com/mamba-org/mamba) to install and manage Python environments.
+1. [Download Unity](https://unity3d.com/get-unity/download).
+2. Use the Unity Hub to manage installations and versions.
+   Unity Hub makes it easier to manage multiple Unity versions and associated projects.
+4. Verify that the Unity Editor version is 6000.0 or later.
 
-Once conda has been installed on your system, open a terminal and execute the following commands to set up a Python 3.10.12 virtual environment and activate it:
+## Install Python 3.10.12 using Conda
 
-```shell
-conda create -n mlagents python=3.10.12 && conda activate mlagents
-```
+Use Conda or Mamba to install and manage your Python environment. This ensures that ML-Agents dependencies are isolated and version-controlled.
 
-On Windows, you'll have to install the PyTorch package separately prior to installing ML-Agents in order to make sure the cuda-enabled version is used, rather than the CPU-only version. Activate your virtual environment and run from the command line:
+To install Python, follow these steps:
 
-```sh
-pip3 install torch~=2.2.1 --index-url https://download.pytorch.org/whl/cu121
-```
+1. Install [Conda](https://docs.conda.io/en/latest/) or [Mamba](https://github.com/mamba-org/mamba).
+2. Open a terminal and create a new Conda environment with Python 3.10.12:
+   
+   ```shell
+   conda create -n mlagents python=3.10.12 && conda activate mlagents
+
+
+
+
+## Install ML-Agents
+You can install ML-Agents in two ways:
+
+* Package installation: Recommended for most users who want to use ML-Agents without modifying the source code.
+* Advanced installation: For contributors, developers extending ML-Agents, or users who want access to the example environments.
+
+### Install ML-Agents (Package installation)
+
+Use this method if you don’t plan to modify the toolkit or need the example environments.
+
+#### Install the Unity package
+
+To install the package, follow these steps:
+
+1. In Unity, open **Window** > **Package Manager**.
+2. Select **+** > **Add package by name**.
+3. Enter `com.unity.ml-agents`.
+4. Enable **Preview Packages** under the **Advanced** drop-down list if the package doesn’t appear.
 
-Note that on Windows, you may also need Microsoft's Visual C++ Redistributable if you don't have it already. See the [PyTorch installation guide](https://pytorch.org/get-started/locally/) for more installation options and versions.
+If the package isn’t listed, follow the [Advanced Installation](#32-install-ml-agents---advanced-installation) method instead.
 
 
-## 3.1 Install ML-Agents - Package Installation
-Use this installation method if you do not plan to modify or extend the ML-Agents Toolkit for your purposes and you don't need access to our example environments.
 
-### 3.1.1 Install the `com.unity.ml-agents` Unity package
+### Install the Python package
 
-The Unity ML-Agents C# SDK is a Unity Package. You can install the `com.unity.ml-agents` package [directly from the Package Manager registry](https://docs.unity3d.com/Manual/upm-ui-install.html). Please make sure you enable 'Preview Packages' in the 'Advanced' dropdown in order to find the latest Preview release of the package.
+Install the ML-Agents Python package to enable communication between Unity and your machine learning training environment.
 
-**NOTE:** If you do not see the ML-Agents package listed in the Package Manager please follow the [Advanced Installation](#32-install-ml-agents---advanced-installation) instructions at the bottom of this page.
+Using a Python virtual environment helps isolate project dependencies and prevent version conflicts across your system. Virtual environments are supported on macOS, Windows, and Linux. For more information, refer to [Using Virtual Environments](https://github.com/Unity-Technologies/ml-agents/pull/6242/files/Using-Virtual-Environment.md).
 
-### 3.1.2 Install Python package
+1. Before installing ML-Agents, activate the Conda environment you created:
 
-Installing the `mlagents` Python package involves installing other Python packages that `mlagents` depends on. So you may run into installation issues if your machine has older versions of any of those dependencies already installed. Consequently, our supported path for installing `mlagents` is to leverage Python Virtual Environments. Virtual Environments provide a mechanism for isolating the dependencies for each project and are supported on Mac / Windows / Linux. We offer a dedicated [guide on Virtual Environments](Using-Virtual-Environment.md).
 
-You can install the ML-Agents Python package directly from PyPi.
 
-**Important:** Ensure you install a Python package version that matches your Unity package version. Check the [release history](https://github.com/Unity-Technologies/ml-agents/releases) to find compatible versions.
 
 To install, activate your virtual environment and run the following command:
 
@@ -61,43 +77,54 @@ which will install the latest version of ML-Agents Python packages and associate
 conda install "grpcio=1.48.2" -c conda-forge
 ```
 
-When you install the Python package, the dependencies listed in the [setup.py file](https://github.com/Unity-Technologies/ml-agents/blob/release/4.0.0/ml-agents/setup.py) are also installed. These include [PyTorch](Background-PyTorch.md).
 
 
-## 3.2 Install ML-Agents - Advanced Installation
+### Install ML-Agents (Advanced Installation)
+
+Use the advanced installation method if you plan to modify or extend the ML-Agents Toolkit, or if you want to download and use the example environments included in the repository.
+
+#### Clone the ML-Agents repository
+
+Clone the ML-Agents repository to access the source code, sample environments, and development branches.
+
+To clone the latest stable release, run:
 
-You will need to clone the repository if you plan to modify or extend the ML-Agents Toolkit for your purposes, or if you'd like to download our example environments. Some of our tutorials / guides assume you have access to our example environments.
 
 Use the command below to clone the repository:
 
 ```sh
 git clone --branch release_23 https://github.com/Unity-Technologies/ml-agents.git
 ```
 
-The `--branch release_23` option will switch to the tag of the latest stable release. Omitting that will get the `develop` branch which is potentially unstable. However, if you find that a release branch does not work, the recommendation is to use the `develop` branch as it may have potential fixes for bugs and dependency issues.
 
-To get the bleeding-edge development version (optional):
 
-```sh
-git clone https://github.com/Unity-Technologies/ml-agents.git
-```
 
-If you plan to contribute those changes back, make sure to clone the `develop` branch (by omitting `--branch release_23` from the command above). See our [Contributions Guidelines](CONTRIBUTING.md) for more information on contributing to the ML-Agents Toolkit.
+#### Add the ML-Agents Unity package
+
+After cloning the repository, add the `com.unity.ml-agents` Unity package to your project.
 
-### 3.2.1 Add the `com.unity.ml-agents` Unity package
-You can [add the local](https://docs.unity3d.com/Manual/upm-ui-local.html) `com.unity.ml-agents` package (from the repository that you just cloned) to your project by:
+To add the local package, follow these steps:
 
-1. Navigating to the menu `Window` -> `Package Manager`.
-2. In the package manager window, click on the `+` button on the top left of the packages list.
-3. Select `Add package from disk...`
-4. Navigate into the `com.unity.ml-agents` folder.
+1. In the Unity Editor, go to **Window** > **Package Manager**.
+2. In the **Package Manager** window, select **+**.
+3. Select **Add package from disk**.
+4. Navigate to the cloned repository and open the `com.unity.ml-agents` folder.
 5. Select the `package.json` file.
 
+Unity adds the ML-Agents package to your project.
+
+If you plan to use the example environments provided in the repository, open the **Project** folder in Unity to explore and experiment with them.
+
+
 <p align="center"> <img src="images/unity_package_manager_window.png" alt="Unity Package Manager Window" height="150" border="10" /> <img src="images/unity_package_json.png" alt="package.json" height="150" border="10" /> </p>
 
-If you are going to follow the examples from our documentation, you can open the `Project` folder in Unity and start tinkering immediately.
 
-### 3.2.2 Install Python package
+#### Install the ML-Agents Python package
+
+Install the Python packages from the cloned repository to enable training and environment communication.
+
+1. From the root of the cloned repository, activate your virtual environment and run:
+
 
 To install the `mlagents` Python package, activate your virtual environment and run from the command line: