Workflow in n8n for video generation via API
It is necessary to create a workflow in n8n that implements a small self-improving system.
In the database, we store (or will store) the following data:
- Completed video
- Image that was the first frame of generation
- Prompt used for video generation
- Generation model
It might also be worth adding:
- Image description
- Location name
- Character names
- Some useful tags
In the workflow, we need to write the perfect prompt for the model (chosen) to generate the video based on data from the database and the system prompt.
Start generation using the Klng API.
The generated video is placed into the Airtable table, which contains the Director's Comment cell, a Start button for generating a new prompt or re-generating based on the director's comments, and a cell for a new prompt.
Versions of prompts and images that were not approved are stored in Airtable and versioned.
After achieving a good result, it is added to our database, thereby increasing the number of high-quality results in our database.
How do you see the process of extracting data from the database, comparing, selecting relevant entries, the quantity, and other nuances?
What database do you suggest to use besides Airtable?
What would you suggest to improve in this workflow?
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