UPDATE: updated the readme for users

README.md

@@ -4,7 +4,7 @@
 🌲 TTool-AI is developed at the [**Laboratory for Timber Construction**](https://www.epfl.ch/labs/ibois/) (director: Prof.Yves Weinand) with the support of the [**EPFL Center for Imaging**](https://imaging.epfl.ch/), at [**EPFL**](https://www.epfl.ch/en/), Lausanne, Switzerland. The project is part of the [**Augmented Carpentry Research**](https://www.epfl.ch/labs/ibois/augmented-carpentry/).
 
 
-🤖 TTool-AI automates the integration of new tools into AC (Augmented Carpentry), enhancing efficiency and simplifying the process. It is developed in Python and relies on the [**FastAPI**](https://fastapi.tiangolo.com/) framework. The project is containerized with [**Docker**](https://www.docker.com/) and [**Docker Compose**](https://docs.docker.com/compose/). The Training Service is based on [**PyTorch**](https://pytorch.org/). The project is developed and tested on Linux (Ubuntu 22.04) with NVIDIA GPUs.
+🤖 TTool-AI automates the integration of new tools into AC (Augmented Carpentry), enhancing efficiency and simplifying the process. It is developed in Python and relies on the [**FastAPI**](https://fastapi.tiangolo.com/) framework. The project is containerized with [**Docker**](https://www.docker.com/) and [**Docker Compose**](https://docs.docker.com/compose/). The Training Service is based on [**PyTorch**](https://pytorch.org/). The project is developed and tested on Linux (Ubuntu 20.04) with NVIDIA GPUs.
 
 
 🚀 For a quick hands-on start or more details, check out our [Wiki](https://github.com/ibois-epfl/TTool-ai/wiki).
@@ -13,45 +13,46 @@
 
 1. **Install Docker and Docker Compose**:
 
-    Ensure you have Docker and Docker Compose installed on your system with NVIDIA Runtime support for the Training Service.
+    Ensure you have Docker and Docker Compose installed on your system with **NVIDIA Runtime support** for the Training Service.
 
 2. **Environment Variables**:
-    TTool-AI relies on environment variables defined in a .env file. 
+    TTool-AI relies on environment variables defined in a **.env file**. 
     Make sure to set up this file as per the project's requirements.
 
 
 ## Getting Started
 
-### Clone the repository:
+## For Users:
+### 1. Go to the specified URL:
+
+Visit the EPFL server at: http://128.178.91.106:16666/docs
+
+### 2. Follow the instructions:
+
+Check out our [Wiki](https://github.com/ibois-epfl/TTool-ai/wiki) for more details.
+
+
+## For Developers:
+
+### 1. Make sure you have the system dependencies installed.
+### 2. Clone the repository:
 
 ```bash
 git clone [email protected]:ibois-epfl/TTool-ai.git
 ```
 
-### Run the project:
-
+### 3. Run the project:
 Navigate to the project's root directory and run the following command:
 ```bash
 cd TTool-ai/
 ```
-Run Docker Compose to build the project in the background:
-```bash
-docker compose up -d
-```
 Run Docker Compose to build the project in the foreground:
 ```bash
 docker compose up
 ```
-
-### Check the status of the containers:
 
-```bash
-docker compose ps -a
-```
-### Access the Service:
+### 4. Access the Service:
 Once everything is up and running, you can access the FastAPI interface at:
-```bash
-http://localhost:16666/docs
-```
-
+- If built on localhost: http://localhost:16666/docs
+- If built on a remote server: Use the appropriate IP address.