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url: /elements-details-right.md
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# Details Elements

This area of the *Designer* allows you to view information and modify the configuration parameters of the elements that make up the *Workflow*, including the *Service* ports.

If no element is clicked or if a blank area of the canvas is clicked, the information for the *Workflow* will be accessed:

* **Name**: The name of the *Workflow*
* **Description**: An optional text description
* **Tags**: Keywords useful for categorization
* **Notes**: Generic and structured annotations
* **Access Level**: The visibility level (e.g., Private, Team or Public)

![workflow-details-form-in-designer](/images/workflow-details-form-in-designer.png)
*Selected element details*

This information can be modified and saved by clicking on **Create/Edit Workflow**.

Clicking on one of the elements on the canvas, the *Details Elements* panel will load the specific information for the selected block (and dependent on its type).

Let's go into detail with some examples.

## Dataset

![../images/image.png](/images/image%2029.png)
*Selected dataset details*

Clicking on a Dataset on the canvas, the *Details Elements* panel will show its related **structural and functional details**. This allows you to immediately understand the content and type of data available.

The panel shows the following information:

* **Dataset Name:** Displayed at the top in bold, for example: `IRIS`
* **Type:** Indicates the type of asset, in this case **Type: table**
* **Data Source:** Indicates the data source to which the dataset refers. In our example, **public** means that the dataset resides in a public data source, accessible to all *authenticated* users of ALIDA. Clicking on the Datasource name, you will be redirected to the Datasource detail page.
* **Dataset Columns:** In the case of a tabular dataset, it shows the list of dataset columns with their respective data types:
  * **Name**: Column name
  * **Type**: Data type (e.g. `Number`, `String`, etc.)

Finally, through the **Show Preview** button, it is possible to view a preview of the dataset:

![../images/image.png](/images/image%2031.png)
*Dataset preview*

## Service

Clicking on a *Service* on the canvas (remembering that it is orange), the *Details Elements* panel will load its related configuration information.

![../images/image.png](/images/image%2035.png)
*Selected service details and parameter configuration*

Through this view, the user can customize the execution of the service and understand how it works.

* **Advanced configuration panel on the right:** When you select a **block** (in this case a service `SKLEARN-MODEL`), the right-hand sidebar **does not only show general information**, but allows you to **configure the internal parameters** of the service.

➔ You see, for example:

* The name of the classification label (`LabelColumn`).
* The chosen algorithm (`RandomForestClassifier`).
* The algorithm parameters (`algorithm_params`) such as the number of trees, maximum depth, etc.
* The dataset split parameters (`train_test_split_args`).

### General Features

* **Parameters with flexible types:** The parameters of the services can be of various types (strings, numbers, JSON, etc.) defined by the service creator, and are **modifiable directly in the interface** without the need to write external code.
* **Mandatory and optional parameters:** The service developer can specify which parameters are requirements (mandatory) and which are optional, thus guiding the user in the correct configuration.
* **Point editing for each service:** The Designer allows you to **customize each individual block** with very specific parameters **without leaving** the drawing canvas.
* **Immediate visual feedback:** As soon as you click on a node, **you immediately see its details and can modify them**. No reloads or external window openings are needed.

::: info Note
The configurable parameters specific to the *Service* are divided into two tabs. The values belonging to the *Application* tab will be passed to the Service through *args*, while those belonging to the *Static* tab will be passed as *global variables*. The choice of how to divide the parameters depends on the considerations of those who developed and registered the *Service*.
:::

## Model

Clicking on one of the models on the canvas (remembering that it is blue), the *Details Elements* panel will load its related information. This will help the user understand the origin of the model, the data on which it was built, and the application context.

![../images/image.png](/images/image%2032.png)
*Selected model details*

Here are the fields visible in the panel:

* **Model Name:** Displayed at the top in bold (e.g. `MODEL CREATED BY AMT – AUTONOMY FORECASTING ANALYTICS`). It is accompanied by a brief explanatory description about the origin of the model, useful for the context.
* **Algorithm:** Indicates the Machine Learning algorithm used to train the model.
* **Input Columns:** List of columns of the dataset given as input to the model.
* **Dataset:** Shows the name of the origin dataset used for training the model. **Note:** Clicking on it, you will be redirected to the related detail page.
  ![../images/image.png](/images/image%2033.png)
  *Dataset detail page*
* **Workflow**: ID of the original *Workflow* in which the model was created; clickable to access the *Workflow* detail page
  ![../images/image.png](/images/image%2034.png)
  *Workflow detail page*
* **Data Source:** Indicates the visibility of the data source hosting the model.