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n8napi-check-workflow-which-model-is-using

This workflow automatically detects and summarizes the AI model information used by all workflows in the current instance. It extracts the model IDs and names associated with each node and exports the results to Google Sheets. Through batch processing, users can quickly understand the model invocation status in a multi-workflow environment, avoiding the tediousness of manual checks and enhancing project management transparency and operational efficiency. It is suitable for automation engineers, team managers, and data analysts.

Workflow Diagram
n8napi-check-workflow-which-model-is-using Workflow diagram

Workflow Name

n8napi-check-workflow-which-model-is-using

Key Features and Highlights

This workflow automatically detects and aggregates AI model usage information across all workflows within the current n8n instance. It accurately extracts the model IDs and names associated with each node and exports the results to a Google Sheets spreadsheet for easy management and analysis. Supporting batch processing, it ensures data clarity and organization.

Core Problem Addressed

In multi-workflow environments, developers and automation administrators often struggle to quickly identify which workflows invoke which AI models. This workflow automates scanning and filtering to help users rapidly locate and consolidate AI model usage within workflows, eliminating the complexity and potential omissions of manual inspection.

Use Cases

  • AI-driven automation project management
  • Monitoring model usage across multiple workflows
  • Automated operations and model compliance auditing
  • Providing a unified view of model usage for team collaboration

Main Process Steps

  1. Manual Trigger: Initiate the detection process via the “Test workflow” node.
  2. Retrieve All Workflows: Call the n8n API to fetch all workflow data from the current instance.
  3. Filter Workflows Containing Model IDs: Select workflows that include nodes invoking AI models, excluding the detection workflow itself.
  4. Batch Iterate Through Workflow Nodes: Split the filtered workflows into batches and decompose their node lists one by one.
  5. Filter Nodes with Model IDs: Identify nodes that actually call AI models.
  6. Organize Field Data: Extract and uniformly format node name, model ID, model name, workflow name, workflow ID, and jump URL.
  7. Clear Google Sheets Data: Clean the target Google Sheets to ensure complete data refresh.
  8. Save Aggregated Data to Google Sheets: Append the organized data to Google Sheets, generating a real-time usage report.

Involved Systems or Services

  • n8n API: Used to retrieve workflow lists and detailed node information.
  • Google Sheets: Serves as the data storage and visualization platform for managing workflow and model usage.
  • Manual Trigger Node: Controls the initiation of the process.

Target Users and Value

  • Automation engineers and developers: Quickly grasp AI model invocation across projects to support optimization and maintenance.
  • Team managers and operations personnel: Facilitate unified monitoring of model usage compliance and resource allocation.
  • Data analysts and product managers: Leverage clear data to support decision-making and resource planning.

This workflow significantly simplifies the management of AI model usage in multi-workflow environments, enhancing transparency and operational efficiency in automation projects.