Command Execution and Conditional Judgment Workflow

This workflow automatically triggers and monitors the execution of specified DAGs by calling the REST API of Apache Airflow, allowing real-time retrieval of task execution results. It has built-in status checks and timeout mechanisms to intelligently handle different states, ensuring the stability and controllability of the workflow. It is suitable for scenarios that require remote triggering and monitoring of data pipeline tasks, improving work efficiency, reducing human intervention, and ensuring the smooth progress of task processes.

This workflow provides a complete set of API backend solutions specifically designed for managing and controlling Docker-based container instances, catering to the integration needs of WHMCS/WISECP modules. Its functionalities include operations such as deploying, starting, stopping containers, mounting disks, managing permissions, and viewing logs. It supports receiving commands through a Webhook API and implements dynamic configuration and access control. Additionally, it integrates an error handling mechanism to ensure efficient and secure operations, providing convenient automated management tools for cloud service providers and IT operations teams.

This workflow is designed to automate the handling of issues and comments in GitHub repositories. It intelligently determines whether a responsible person needs to be assigned and automatically assigns unassigned issues to appropriate users. It can recognize requests from users who proactively claim tasks, avoiding duplicate assignments and significantly enhancing project management efficiency. Whether in open-source projects or internal enterprise development, this workflow helps accelerate response times, reduce the burden on maintainers, and achieve more efficient team collaboration.

This workflow implements automated deployment functionality by monitoring a specific folder in Google Drive, automatically downloading and processing JSON files of n8n workflows. After formatting and cleaning, it uses an API to import the workflows into a designated instance and automatically sets tags. Finally, the deployed files are archived into another folder. The entire process requires no manual intervention, significantly enhancing the efficiency of workflow management and deployment, making it suitable for teams that need to manage and update workflows in bulk.

This workflow automates the processing of GitLab merge requests, intelligently receiving and reviewing code changes. It leverages advanced language model technology to analyze code differences and provide professional review suggestions, generating scores and decisions of "accept" or "reject." The review results are automatically published to the discussion area of GitLab, helping development teams quickly address issues, improve code quality and collaboration efficiency, alleviate the burden of manual reviews, and standardize review criteria. It is applicable in scenarios such as software development, continuous integration, and open-source project maintenance.

This workflow creates a simple API endpoint through a Webhook node, capable of receiving HTTP requests with a name parameter and dynamically generating Google search links as a response. It requires no coding, allowing for the quick setup of a custom query interface, simplifying the complex processes of traditional API development. It is suitable for automation enthusiasts, developers, and educational training scenarios, making it an ideal choice for generating dynamic links.

This workflow automates the scheduled sending of fun messages and images to a designated Discord channel. It is set to trigger at various frequencies, including every Friday and Saturday at 9 AM, as well as every 30 minutes. This approach effectively enhances community engagement and interaction, reduces the hassle of manual operations, ensures the delivery of interesting content at specific times, boosts user participation, and fosters a positive community atmosphere. It is suitable for community management and teams looking to automate message delivery.

This workflow automates the management of tags in the Docker image repository by regularly scanning and deleting expired or redundant tags, while retaining only the latest few and the "latest" tag, thereby keeping the repository tidy. After the cleanup, garbage collection is performed, and the operations team is notified of the results via email, with support for failure alerts. This enhances operational efficiency and space utilization, addressing issues of wasted storage resources and management chaos.