Workflow to automatically create videos with AI

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Workflow to Create Videos Automatically with AI

What is the error message (if any)?

Please share your workflow

(Select the nodes on your canvas and use the keyboard shortcuts CMD+C/CTRL+C and CMD+V/CTRL+V to copy and paste the workflow.)

Share the output returned by the last node

Information on your n8n setup

  • n8n version:
  • Database (default: SQLite):
  • n8n EXECUTIONS_PROCESS setting (default: own, main):
  • Running n8n via (Docker, npm, n8n cloud, desktop app):
  • Operating system:
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Hey @Samuel_Bebecito_troj, while you wait for a response, here are some things that might help:

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@Parintele_Damaskin, @azizaavon - you’ve helped with similar issues before, can you take a look?

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@Samuel_Bebecito_troj I’ll make you some JSON, one moment!

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i will make it

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Hi Samuel — for the editing part (joining clips, rotating to 9:16 vertical, subtitles, music) the usual blocker is that n8n Cloud doesn’t have FFmpeg and in n8n 2.0 the Execute Command node comes disabled. What works without installing anything: calling a video API with HTTP Request and waiting for the result with a Wait → If loop.

I’m leaving you an importable workflow that does exactly that (video URL → vertical 9:16 with blurred background → download URL), using only native nodes: https://kinopipe.com/workflows/kinopipe-vertical-tiktok-n8n.json — you change the endpoint URL for trim, merge, subtitles, etc. (catalog: Prebuilt Video & Audio API Tools — KinoPipe).

For the script and generated images/videos use the OpenAI/Gemini/Kling nodes you already have; the API only handles the final render. Full transparency: the API is mine (KinoPipe), it has 100 free credits with no card required to try it out. If you share what exact steps you want (image + audio → video, join 5 clips, etc.) I’ll send you the JSON for each one.

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Re: Can n8n Automate Video Processing for a YouTube-Like App?

Great question — and yes, it’s definitely possible, but the approach matters a lot here.

The key thing to understand first:

n8n is an orchestration tool, not a media engine. The default n8n environment doesn’t ship with FFmpeg, yt-dlp, or any video tooling. So if you’ve been trying to run video commands directly inside n8n and hitting errors, that’s expected — the binaries simply aren’t there.

A cleaner way to think about it:

Split the work into two layers.

1. n8n as the orchestrator
Let n8n handle what it’s genuinely good at:

  • Receiving the upload or video URL via webhook
  • Validating and queuing the job
  • Tracking status
  • Updating your database
  • Sending notifications back to the user

2. A dedicated processing service
Let something purpose-built handle the actual video work — transcoding, thumbnails, format conversion. This can be:

  • A small container running FFmpeg
  • A serverless function
  • A managed transcoding service (Mux, Cloudflare Stream, Coconut, AWS Elemental — all solid options)

How the flow would look:

  • A webhook in n8n receives the video or URL
  • n8n pushes the job into a queue (Redis, RabbitMQ, or SQS work well)
  • Your worker picks it up and processes the video
  • When finished, the worker calls back into n8n
  • n8n then uploads the output to storage, writes metadata, and notifies the user

A few things worth planning for:

  • Memory: video files are large, and n8n holds binary data in memory by default. A big file can crash the instance. Better to pass references (URLs, storage paths) through n8n rather than the file itself.
  • Timeouts: transcoding takes time. Long-running steps inside n8n will time out, which is another reason to keep the heavy work outside it.
  • Concurrency: multiple uploads at once need a queue, otherwise jobs collide.
  • Retries: jobs will fail sometimes. Plan for retries without duplicating output.

In short:

Don’t route the video through n8n — route references to it. Let n8n handle the workflow logic and let a dedicated service handle the processing. That gives you something reliable and scalable without fighting the platform.

If it’s just a small hobby project with short clips, you can make it work inside n8n with a custom image, but for anything user-facing, delegating the processing is the smoother path.

Happy to help sketch out the queue and worker setup if you share your expected scale.

Regards,

Ryan | AccuWeb.Cloud

Cloud and Infrastructure Support

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Hey Samuel! For all these cases, I at least started using a tool (API) that allows me to use FFmpeg by making requests and in response I get the video already edited with what I needed. I think they’re in a Beta version but it’s worked perfectly and their free account has a lot of capacity since it’s in the testing period. I’m leaving you the link in case it’s useful:

Cheers!