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Prepare v1.0.0 release as acsm-fairifier

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@ -113,16 +113,16 @@ Open **Git Bash** and run:
```bash
cd Gitea
git clone --recurse-submodules https://gitea.psi.ch/apog/acsmnode.git
cd acsmnode
git clone --recurse-submodules https://gitea.psi.ch/apog/acsm-fairifier.git
cd acsm-fairifier
```
## Run the ACSM FAIRifier Toolkit
This toolkit includes a containerized JupyterLab environment for executing the data processing pipeline, plus an optional dashboard for manual flagging.
1. Open **PowerShell as Administrator** and navigate to the `acsmnode` repository.
2. Create a `.env` file in the root of `acsmnode/`.
1. Open **PowerShell as Administrator** and navigate to the `acsm-fairifier` repository.
2. Create a `.env` file in the root of `acsm-fairifier/`.
3. **Securely store your network drive access credentials** in the `.env` file by adding the following lines:
```plaintext
CIFS_USER=<your-username>
@ -175,13 +175,9 @@ We recommend using Miniforge to manage your conda environments. Miniforge ensure
2. Create the Environment from `environment.yml`
After installing Miniforge, open **Miniforge Prompt** or a terminal with access to conda and run:
```bash
cd path/to/Gitea/acsmnode
cd path/to/Gitea/acsm-fairifier
conda env create --file environment.yml
```
3. Activate the Environment
```bash
conda activate acsmnode_env
```
### Working with Jupyter Notebooks
We now make the previously installed Python environment `acsmnode_env` selectable as a kernel in Jupyter's interface.