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Narrative chaining: AI-generated video scene extensions with Veo3

DenizDeniz
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2/3/2026
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Structured Setup Guide: Narrative Chaining with N8N + AI

1. Input Setup

Use a Google Sheet as the control panel. Fields required: Video URL (starting clip, ends with .mp4) Number of clips to extend (e.g., 2 extra scenes) Aspect ratio (horizontal, vertical, etc.) Model (V3 or V3 Fast) Narrative theme (guidance for story flow) Special requests (scene-by-scene instructions) Status column (e.g., "For Production", "Done") 👉 Example scene inputs: Scene 1: Naruto walks out with ramen is his hands Scene 2: Joker joins with chips

2. Workflow in N8N

Step 1: Fetch Input Get rows in sheet → fetch the next row where status = For Production. Clear sheet 2 → reset the sheet that stores generated scenes. Edit fields (Initial Values): Video URL = starting clip Step = 1 Complete = total number of scenes requested Step 2: Looping Logic Looper Node: Runs until step = complete. Carries over current video URL → feeds into next generation. Step 3: Analyze Current Clip Send video URL to File.AI Video Understanding API. Request: Describe last frame + audio + scene details. Output: Detailed video analysis text. Step 4: Generate Prompt AI Agent creates the next scene prompt using: Context from video analysis Narrative theme (from sheet) Scene instructions (from sheet) Aspect ratio, model preference, etc. 👉 Output = video prompt for next scene Step 5: Extract Last Frame Call File.AI Extract Frame API. Parameters: Input video URL Frame = last Output = JPG image (last frame of current clip). Step 6: Generate New Scene Use Key.AI (V3 Fast) for economical video generation. POST request includes: Prompt (from AI Agent) Aspect ratio + model Image URL (last frame) → ensures seamless chaining Wait for generation to complete. 👉 Output = New clip URL (MP4) Step 7: Store & Increment Log new clip URL into Sheet 2. Increment Step by +1. Replace Video URL with the new clip. Loop back if Step < Complete.

3. Output Section

Once all clips are generated: Gather all scene URLs from Sheet 2. Use File.AI Merge Videos API to stitch clips together: Original clip + all generated scenes. Save final MP4 output. Update Sheet 1 row with: Final video URL Status = Done

4. Costs

Video analysis: ~$0.015 per 8s clip Frame extraction: ~0.002¢ (almost free) Clip merging: negligible (via ffmpeg backend) V3 Fast video generation (Key.AI): ~$0.30 per 8s clip

n8n Workflow: AI-Generated Video Scene Extensions with VEO3

This n8n workflow demonstrates a sophisticated chaining of AI agents to generate narrative scene extensions for video, leveraging a VEO3 API. It orchestrates a process where an AI agent "thinks" about a video scene, generates a narrative extension, and then potentially triggers further actions based on the generated content.

What it does

This workflow automates the following steps:

  1. Manual Trigger: The workflow is initiated manually, allowing for on-demand execution.
  2. AI Agent (Think): An AI Agent, specifically configured with a "Think" tool, processes initial input (likely a video scene description or context). This step is designed to simulate an AI "thinking" or planning its response.
  3. OpenAI Chat Model: The output from the "Think" agent is then fed into an OpenAI Chat Model. This model is responsible for generating the actual narrative extension for the video scene.
  4. Structured Output Parser: The raw text output from the OpenAI Chat Model is parsed into a structured format, ensuring consistency and usability for subsequent steps.
  5. Edit Fields (Set): The parsed data is then transformed or refined, likely mapping the AI-generated narrative elements to specific fields required for video scene extensions.
  6. If Node: A conditional check is performed on the processed data. This could be to verify the quality, length, or specific content of the generated narrative.
  7. Wait: If the condition in the "If" node is met (e.g., the narrative is valid), the workflow pauses for a specified duration. This might be to simulate processing time or to wait for an external system.
  8. HTTP Request (VEO3 API): After the wait period, an HTTP Request is made. Based on the directory name "veo3", this likely interacts with a VEO3 API to submit the AI-generated scene extension for video generation or integration.
  9. Google Sheets: The workflow concludes by writing data to Google Sheets. This could be for logging the generated scene extensions, tracking the status of video generation requests, or storing the AI's output for review.
  10. Sticky Note: A sticky note is included in the workflow, likely for documentation or internal notes about a specific part of the process.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • OpenAI API Key: For the OpenAI Chat Model.
  • Google Sheets Account: With appropriate permissions to write data to a spreadsheet.
  • VEO3 API Access: Credentials and an endpoint for the VEO3 API (implied by the directory name and HTTP Request node, though not explicitly configured in the provided JSON).
  • n8n LangChain Nodes: The @n8n/n8n-nodes-langchain package installed in your n8n instance for the AI Agent, OpenAI Chat Model, and Structured Output Parser nodes.

Setup/Usage

  1. Import the Workflow: Download the JSON content and import it into your n8n instance.
  2. Configure Credentials:
    • Set up your OpenAI API Key credential for the "OpenAI Chat Model" node.
    • Configure your Google Sheets credential for the "Google Sheets" node.
    • Configure any necessary HTTP Request credentials (e.g., API keys, tokens) for the "HTTP Request" node to interact with the VEO3 API.
  3. Customize Nodes:
    • AI Agent (Think): Adjust the agent's prompt and configuration to guide its "thinking" process for your specific video scene context.
    • OpenAI Chat Model: Fine-tune the model's parameters (e.g., model, temperature) to achieve the desired narrative style and quality.
    • Structured Output Parser: Define the expected JSON schema for the narrative output.
    • Edit Fields (Set): Map the parsed AI output to the correct fields for your VEO3 API or Google Sheet.
    • If: Modify the conditions to match your validation criteria for the generated narratives.
    • Wait: Adjust the wait duration as needed.
    • HTTP Request: Update the URL, headers, and body of the request to match your VEO3 API's specifications for scene extension submission.
    • Google Sheets: Specify the Spreadsheet ID, Sheet Name, and the data to be written.
  4. Execute: Click "Execute workflow" on the "Manual Trigger" node to run the workflow.

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