This n8n workflow automates the process of receiving video and thumbnail data via a webhook, validating the data, and then storing the information in Airtable. The workflow is designed for seamless integration of AI-generated media content into a database for easy management and tracking.
Here’s a step-by-step explanation:
1. Webhook Trigger: The workflow begins with a webhook node listening for POST requests at the specified endpoint ‘luma-ai-response’. It captures incoming JSON data.
2. Data Preparation: The ‘Video JSON’ set node processes and assigns relevant data fields such as the entire JSON payload, video URL, thumbnail URL, and an ID from the webhook payload.
3. Validation: An ‘If’ node checks if the video URL exists in the incoming data to ensure the payload is valid and contains video assets.
4. Airtable Update: If the validation passes, the data is sent to Airtable. A dedicated node updates a record in a specified Airtable table, adding the video URL, thumbnail URL, generation ID, and status information.
5. Practical Use Case: This workflow is perfect for scenarios where AI-generated videos need to be automatically collected, validated, and cataloged in an Airtable base, such as in content creation pipelines, social media automation, or digital media management.
Overall, this setup streamlines workflow automation, reduces manual data entry, and ensures that media assets are systematically stored for further use.
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