# Managing pipelines > Create and run pipeline runs in AI Center by selecting a package, dataset, and pipeline type from the Pipelines page. ## Creating pipelines 1. In the **Pipelines** page, select the **Create new** button. The **Create new pipeline run** page is displayed. Alternatively, in the **ML Package Details** of a specific package, select the **Pipeline Runs**, and then select the **Create new** button. The **Create new pipeline run** page is displayed. 2. In the **Create new pipeline run** page, select the type of the pipeline run. The available options are **Training run**,**Evaluation run**, and **Full pipeline run**. 3. Add a display name for the pipeline run. 4. Select the package for the pipeline run. 5. Select the package's major and minor versions. 6. Select datasets. According to the selected pipeline type, the following datasets must be specified: * For **training pipeline**, specify the **input dataset**. * For **evaluation pipeline**, specify the **evaluation dataset**. * For **full pipeline run**, specify the **input dataset** and the **evaluation dataset**. 7. **Optional:** Enter parameters for the pipeline runs. Select **Add new** to display the parameters section, then enter the environment variable and its corresponding value. Multiple parameters are accepted. 8. Select whether the pipeline requires a **GPU**, by default it is set to **No**. :::note If you are using the **AI Units** licensing model, the hourly cost of **AI Units** is displayed under the **Enable GPU** toggle button. Depending on whether you choose to use GPU or not, the hourly cost changes. ::: 9. Select when the pipeline should run. The possible options are: * **Run now** - the pipeline starts running immediately after its creation. * **Time based** - the pipeline starts running at the date and time you specify in the **Date** and **Time** fields. * **Recurring** - the pipeline starts running according to the recurring schedule you set up in the **Set Recurring Schedule** window. You can set it up to run on specific weekdays at a certain time, or you can use cron expressions. 10. Select **Create** to create the pipeline or **Cancel** to abort the process. The **Create new pipeline run** page is closed. ![Screenshot including the Create new pipeline run menu in UiPath AI Center.](https://dev-assets.cms.uipath.com/assets/images/ai-center/ai-center-screenshot-including-the-create-new-pipeline-run-menu-in-uipath-ai-center-271052-f846c1d1-3ca975d2.webp) The pipeline is created and displayed along with its details in the **Pipelines** page and in the selected package's **ML Package Details** page's **Pipeline Runs** tab. The pipeline runs according to the timeframe you chose while creating it. :::note We made optimizations to node availability for skill deployments. Starting with [October](https://docs.uipath.com/ai-center/automation-cloud/latest/user-guide/october-2023), time taken for skill deployments is reduced. ::: ### Scheduling pipelines During creation, any pipeline type can be either scheduled at a single future date and time, or with a recurring schedule. For example, a schedule may be set for a pipeline to execute on Sunday nights at 1am. This allows for models to be continuously updated as data is sent back from Human-In-the-Loop tasks and additionally allows for more efficient usage of AI Units licenses. ⏲ To create a pipeline to be scheduled at a single future date, select the **Time based** option in the **Create new pipeline run** page. 📅 To create a pipeline with a recurring schedule, select the **Recurring** option in the **Create new pipeline run** page. ⚙ A more complex schedule than daily at some time can be set by selecting the **Advanced** tab in the **Set Recurring Schedule** window and entering a cron expression. There are many free online tools to easily generate cron expressions. ## Editing scheduled pipelines You can only edit pipelines that haven't run yet. 1. Go to the **Pipeline Details** page. * In the **Pipelines** page, select the three-dot **⁝** button next to a scheduled pipeline and select **Details**. * In the **ML Package Details** of a specific package, select the **Pipeline Runs** tab, select the three-dot **⁝** button next to a scheduled pipeline and select **Details**. The **Pipeline Details** page is displayed. 2. Select **Edit pipeline**. The **Edit pipeline run** page is displayed. 3. You can change the data directory of the scheduled pipeline, as well as the recurring schedule. 4. Select **Submit** to save the changes. The scheduled pipeline is displayed in the **Pipelines** page with its updated information. ## Removing pipelines 1. Remove a pipeline. * In the **Pipelines** page, select the three-dot **⁝** button next to a pipeline and select **Remove**. * In the **ML Package Details** of a specific package, select the **Pipeline Runs** tab, select the three-dot **⁝** button next to a pipeline and select **Remove**. A confirmation dialog is displayed. 2. Select **OK** to delete the pipeline. :::note Removing a Packaging, Waiting for resources or Running pipeline first stops it and then removes it. If you just want to stop a Packaging, Waiting for resources or Running pipeline and look at its logs, select the three-dot **⁝** button next to it and select the **Details** option to navigate its corresponding **Pipeline Details** page. You can stop the pipeline from there. ::: ## Viewing pipeline details You can consult more information about a specific pipeline or perform other actions. * In the **Pipelines** page, select the three-dot **⁝** button next to a scheduled pipeline and select **Details**. * In the **ML Package Details** of a specific package, select the **Pipeline Runs** tab, select the three-dot **⁝** button next to a scheduled pipeline and select **Details**. The **Pipeline Details** page is displayed. * Or, if an ML Package is generated by a pipeline, you can access all information related to the pipeline directly from the **ML Package** window by clicking on the three-dot **⁝** menu and **Pipeline Details**. This is only available for new pipelines. The information displayed and the actions you can perform here depend on the [pipeline status](https://docs.uipath.com/ai-center/automation-cloud/latest/user-guide/about-pipelines#pipeline-status). ### Scheduled pipeline details The **Pipeline Details** page for Scheduled pipelines shows an information tab. You can perform the following actions: **Delete** the pipeline. **Edit** the pipeline. In the displayed **Edit pipeline run** page, any fields can be updated. Selecting **Run Now** does not create a new pipeline, instead, it executes this pipeline immediately, thus removing it from the list of scheduled pipelines. ### Packaging pipeline details The **Pipeline Details** page for Packaging pipelines shows an information tab. You can perform the following action: **Kill** the pipeline. This stop the execution of the pipeline, so it won't run and it won't consume AI Units. Its status changes to Killed. ### Waiting for resources pipeline details The **Pipeline Details** page for Waiting for resources pipelines shows an information tab. You can perform the following action: **Kill** the pipeline. This removes the pipeline from the queue, so it won't be executed and it won't consume AI Units. Its status changes to Killed. ### Running pipeline details The **Pipeline Details** page for Running pipelines shows an information tab and real-time logs. You can perform the following action: **Kill** the pipeline. This immediately stops the pipeline and changes its status to Killed. The logs show the snapshot at the time the kill action was executed. ### Failed pipeline details The **Pipeline Details** page for Failed pipelines shows an information tab and logs. Depending on the stage at which this pipeline failed, (partial) pipeline outputs are displayed. You can perform the following action: **Restart** the pipeline. This adds a new pipeline to the queue, with the exact same parameters with which it was created. If the queue is empty, the pipeline immediately starts executing. ### Killed pipeline details The **Pipeline Details** page for Killed pipelines shows an information tab. In addition, depending on the point at which this pipeline was killed, the pipeline details page may also include logs. You can perform the following actions: **Restart** the pipeline. **Remove** the pipeline. ### Successful pipeline details The **Pipeline Details** page for Successful pipelines shows an information tab, logs and pipeline outputs. You can perform the following actions: **Delete** the pipeline. **Remove** the pipeline. **Restart** the pipeline. ## Logs You can download a report of the pipeline run from the **Logs** section. To do so, select the **Download Pipeline Report** button. We recommend attaching this report when submitting an issue for faster troubleshooting. This report gathers all the necessary information required to debug an issue, including account ID, tenant ID, AI Units, and the respective package and pipeline information. The following screenshot is an example for a pipeline run report: ![Example of a pipeline run report.](https://dev-assets.cms.uipath.com/assets/images/ai-center/ai-center-example-of-a-pipeline-run-report-303070-3bd26740-f0fba045.webp)