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Turn any Youtube video into VIRAL shorts

NasserNasser
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2/3/2026
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For Who?

  • Content Creators
  • Youtube Automation
  • Marketing Team

How it works?

1 - Enter the video ID (in Edit Field Node) you want to use as a base to create Short Form videos 2 - Use yt-transcript-api (self-hosted on docker) to retrieve the transcript of the video 3 - Format the transcript to be usable by an LLM 4 - LLM select clips based on specific rules (prompt customizable) 5 - Split out the selected Clips and perform a loop for each Clip 6 - Use yt-clip-api (self-hosted on docker) to edit the video in ready-to-use Short Form videos

What you get?

🧩 Copy-Paste Setup – You’ll get a straightforward, easy-to-follow system with clear instructions, even with minimal technical skills.

🎛️ Built-in Customization Guide – The documentation includes a dedicated section to help you easily adjust the system to your own channel, video style, or workflow needs.

💬 Full Personalized Support – I’ll personally help you until the workflow is fully running on your side.

++System Cost to run++: $0

++Time to Setup++: 20-40min (depending on your experience)

⚠️ PRE-REQUISITES

Before purchasing, please make sure you meet the following requirements:

  • The YouTube channel you want to clip includes face-cam + screen recording (like on my videos).
  • You have basic knowledge of code (enough to follow simple setup instructions). You can also use AI to help you 😉

👨‍💻 More Workflows : https://n8n.io/creators/nasser/

n8n YouTube Video to Viral Shorts Workflow

This n8n workflow is designed to help you transform any YouTube video into engaging, viral short-form content. It leverages AI to analyze video transcripts, extract key moments, and generate compelling titles and descriptions suitable for platforms like YouTube Shorts, TikTok, or Instagram Reels.

What it does

This workflow automates the following steps:

  1. Manual Trigger: Initiates the workflow upon a manual click, allowing you to process videos on demand.
  2. HTTP Request: This node is currently configured as a placeholder or a starting point for potential API calls. In its current state, it does not perform any specific action related to YouTube video processing but can be extended to fetch video data, transcripts, or interact with other services.
  3. No Operation, do nothing: A placeholder node that passes data through without modification. It can be used for debugging or as a point to insert future logic.
  4. Edit Fields (Set): This node allows you to define or modify specific fields within the workflow's data. It can be used to prepare data for subsequent AI processing.
  5. Loop Over Items (Split in Batches): This node is designed to process items in batches, which is useful for handling multiple video segments or processing large amounts of text data efficiently.
  6. Wait: A node that pauses the workflow for a specified duration. This can be useful for respecting API rate limits or introducing delays between processing steps.
  7. Sticky Note: A visual aid within the workflow, used for adding comments or notes to explain parts of the logic.
  8. Code: This node allows custom JavaScript code execution. It's a powerful tool for complex data manipulation, custom logic, or integrating with services not directly supported by n8n nodes.
  9. Basic LLM Chain: Utilizes a Language Model (LLM) chain from LangChain to perform a sequence of operations, likely involving text analysis, summarization, or generation based on the video content.
  10. Structured Output Parser: Processes the output from the LLM chain, parsing it into a structured format (e.g., JSON) to make it easily usable by subsequent nodes. This is crucial for extracting titles, descriptions, and other metadata in a consistent format.
  11. Split Out: This node splits an array of items into individual items, allowing each item to be processed independently. This is useful if the AI generates multiple short ideas from a single video.
  12. Mistral Cloud Chat Model: Integrates with the Mistral Cloud Chat Model, a powerful AI language model, to generate creative text, summarize content, or refine short-form video ideas.

Prerequisites/Requirements

  • n8n Instance: A running instance of n8n.
  • Mistral Cloud Account & API Key: Required for the "Mistral Cloud Chat Model" node to interact with the Mistral AI service.
  • LangChain Integration: The workflow utilizes LangChain nodes, which might require specific n8n package installations or configurations.
  • YouTube Video Transcripts/Content: While not explicitly fetched by the current HTTP Request node, the workflow's purpose implies the need for YouTube video data (e.g., transcripts) as input for the AI processing. This would likely be fed into the "Edit Fields (Set)" or "Code" nodes.

Setup/Usage

  1. Import the workflow: Download the provided JSON and import it into your n8n instance.
  2. Configure Credentials:
    • Set up your Mistral Cloud API Key in the "Mistral Cloud Chat Model" node's credentials.
  3. Input Video Data:
    • Currently, the workflow starts with a "Manual Trigger" and an "HTTP Request" node that is a placeholder. To process a YouTube video, you would typically:
      • Modify the "HTTP Request" node to fetch the transcript or details of a YouTube video (e.g., using the YouTube API).
      • Alternatively, manually input the video's transcript or key information into the "Edit Fields (Set)" node for testing.
  4. Execute the Workflow: Click "Execute Workflow" on the "Manual Trigger" node to run the workflow.
  5. Review Output: The output of the "Structured Output Parser" and subsequent nodes will contain the generated short-form video ideas, titles, and descriptions. You can inspect the data flow in n8n to see the results at each step.

This workflow provides a robust framework for automating the creation of viral YouTube Shorts, leveraging the power of AI to streamline content generation.

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