A collection of custom code nodes for n8n to enhance video processing workflows. These nodes provide advanced video analysis, frame extraction, and metadata generation capabilities.
Extracts 5 key frames from a video and selects the best one for social media using OpenAI's GPT-4o Vision.
Features:
- Scene detection for intelligent frame selection
- Visual appeal and composition analysis
- Social media platform-specific suggestions
- Detailed metadata for each extracted frame
Files:
best-frame-extractor/best-frame-extractor.js- Main code node scriptbest-frame-extractor/configuration.md- Configuration documentation
Extracts comprehensive context from videos including transcripts, visual analysis, and topic segmentation.
Features:
- Word-level timestamp transcription using Whisper API
- Visual frame analysis with GPT-4o Vision
- Automatic topic segmentation with timestamps
- Combined transcript and visual context
Files:
video-context-extractor/video-context-extractor.js- Main code node scriptvideo-context-extractor/configuration.md- Configuration documentation
Docker setup for n8n with ffmpeg and other required dependencies pre-installed.
Files:
docker-config/docker-compose.yml- Docker Compose configurationdocker-config/n8n.Dockerfile- Custom Dockerfile for n8n with ffmpeg
- n8n v1.91.1 or later
- Docker and Docker Compose
- FFmpeg installed in the container
- OpenAI API key
- Clone this repository
- Navigate to the repository directory
- Start the Docker container:
cd docker-config docker-compose up -d - Access n8n at http://localhost:5678
- Create a new workflow and add a "Code" node
- Copy the content of the desired script into the Code node
- Configure the workflow as described in the configuration documentation
The following environment variables are recommended for optimal performance:
N8N_DEFAULT_BINARY_DATA_MODE=filesystem
N8N_BINARY_DATA_STORAGE_PATH=/tmp/n8n-binary-data
N8N_PAYLOAD_SIZE_MAX=1024
MIT
Created for video processing workflows in n8n.