ManualTrigger Automate

For ManualTrigger Automate, this workflow automates image processing by downloading an image from Google Drive, extracting color information, generating semantic keywords using OpenAI, and creating an embedding document for vector search. It simplifies image analysis and enhances searchability, making it easier to retrieve relevant images based on content and context.

7/8/2025
22 nodes
Complex
manualcomplexgoogle driveeditimagelangchainsticky noteadvanced
Categories:
Complex WorkflowManual TriggeredCreative Design Automation
Integrations:
Google DriveEditImageLangChainSticky Note

Target Audience

This workflow is designed for:
- Digital Marketers looking to analyze visual content for SEO and keyword optimization.
- Graphic Designers who want to automate image processing and gain insights from their designs.
- Researchers in fields like computer vision or data science needing to extract and analyze image features.
- Developers integrating image processing capabilities into applications using n8n automation.

Problem Solved

This workflow addresses the challenge of efficiently extracting valuable insights from images, such as:
- Automating Image Downloads from Google Drive.
- Extracting Color Information to understand the visual characteristics of images.
- Generating Keywords that describe the image semantically, enhancing searchability and categorization.
- Creating an Embedding Document for images, facilitating advanced search capabilities using vector stores.

Workflow Steps

  • Manual Trigger: The workflow starts when the user clicks the "Test workflow" button.
    2. Download Image: The image is fetched from Google Drive using a specified file ID.
    3. Get Color Information: The workflow extracts color channel statistics from the downloaded image.
    4. Resize Image: The image is resized to 512x512 pixels, ensuring compatibility with OpenAI models.
    5. Generate Keywords: The workflow uses OpenAI's capabilities to extract a comprehensive list of semantic keywords related to the image.
    6. Combine Analysis: Color information and generated keywords are merged to create a comprehensive analysis output.
    7. Document for Embedding: This step prepares the data for embedding by defining metadata such as source and format.
    8. Store in Vector Store: The embedding document is inserted into an in-memory vector store for future retrieval.
    9. Search for Image: Users can perform searches against the vector store using prompts, allowing for efficient image retrieval based on semantic content.

    • Customization Guide

    To customize this workflow:
    - Change Image Source: Update the Google Drive file ID in the Google Drive node to fetch a different image.
    - Adjust Image Processing: Modify the parameters in the Resize Image or Get Color Information nodes to change how the image is processed.
    - Alter Keyword Extraction: Adjust the text in the Get Image Keywords node to refine the type of keywords generated based on your needs.
    - Expand Metadata: Customize the metadata in the Document for Embedding node to include additional relevant information.
    - Integrate Additional Nodes: Add more processing or analysis nodes as needed to enhance the workflow's capabilities.