Automated Image Analysis and Embedding for Search
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This workflow analyzes an image by extracting color information and generating descriptive keywords using OpenAI. It then prepares this data for embedding into a vector store, enabling semantic search capabilities. The Google Drive and Edit Image nodes are central to image retrieval and processing.
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About This Workflow
Overview
This n8n workflow automates the process of analyzing an image to prepare it for semantic search. It begins by retrieving an image from Google Drive. The Google Drive node fetches the image file. Subsequently, the Get Color Information and Resize Image nodes (from the Edit Image node) are used to extract color channel data and ensure the image is in a suitable format (512x512 pixels) for AI analysis, as recommended for OpenAI models.
Following image processing, a Document for Embedding node crafts a structured document containing the extracted color information and generated keywords (from an assumed upstream process or other nodes not fully detailed here, but implied by the Sticky Note1). This document, along with metadata such as the image's original filename and format, is then passed to the Default Data Loader and Recursive Character Text Splitter nodes. These nodes prepare the content for ingestion into a vector database. Finally, the Embeddings OpenAI node converts this textual representation into embeddings, ready to be stored in a vector store for efficient similarity searches.
Key Features
- Retrieves images from Google Drive.
- Extracts color channel information from images.
- Resizes images to optimize for AI analysis (512x512).
- Compiles image data and metadata into a structured document for embedding.
- Prepares text content for vector store ingestion.
- Generates embeddings using OpenAI.
How To Use
- Ensure you have a Google Drive account and have connected it to n8n via credentials.
- Replace the
fileIdin theGoogle Drivenode with the ID of the image you wish to analyze. - Configure the
Edit Imagenodes for color information extraction and resizing as needed. - Adjust the
Document for Embeddingnode to correctly capture any upstream keyword generation if applicable. - Set up your OpenAI credentials and ensure the
Embeddings OpenAInode is configured with your desired model. - Connect the output of the
Embeddings OpenAInode to your chosen vector store node (e.g.,VectorStoreInMemory) for storage and retrieval.
Apps Used
Workflow JSON
{
"id": "f5cb6730-472d-4ffa-a825-7087e07c10a5",
"name": "Automated Image Analysis and Embedding for Search",
"nodes": 0,
"category": "AI and Machine Learning",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: f5cb6730-472d...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
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