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UPDATE: added the env file information to the readme
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sushidelivery committed Jan 22, 2024
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🚀 For a quick hands-on start or more details, check out our [Wiki](https://github.com/ibois-epfl/TTool-ai/wiki).

## System dependencies

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.

2. **Environment Variables**:
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

### For Users:
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### For Developers:

1. **Make sure you have the system dependencies installed**
2. **Clone the repository**:
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.

2. **Environment Variables**:
TTool-AI relies on environment variables defined in a **.env file**.
Make sure to set up this file as per the project's requirements.

**Important**: The .env file that is included in the repository is tailored for the EPFL server. You might have to modify the values for **${DATA_DIR}**, **${VIDEO_DIR}** and **${POSTGRES_DIR}** to match your system's directory structure.

3. **Clone the repository**:

```bash
git clone [email protected]:ibois-epfl/TTool-ai.git
```

3. **Run the project**:
4. **Run the project**:
Navigate to the project's root directory and run the following command:
```bash
cd TTool-ai/
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docker compose up
```
4. **Access the Service**:
5. **Access the Service**:
Once everything is up and running, you can access the FastAPI interface at:
- If built on localhost: http://localhost:16666/docs
- If built on a remote server: Use the appropriate IP address.
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