Generate searchable embeddings from image text summaries
Workflow Description
Automation that retrieves images from Google Drive, extracts and summarizes their text using OpenAI, then converts summaries into numerical embeddings stored in vector memory for intelligent semantic search and retrieval.
How it works
- 1.Manually trigger workflow to select images from Google Drive
- 2.Extract text content from images using document loader
- 3.Split extracted text into manageable chunks
- 4.Summarize text chunks using OpenAI language model
- 5.Convert summaries into vector embeddings with OpenAI
- 6.Store embeddings in memory for semantic search queries
Use cases
- Index and organize large image archives by content automatically
- Enable natural language search across image document collections
- Automate extraction and categorization of scanned documents
Requirements
- Active Google Drive account with image files
- Valid OpenAI API key with embedding model access
- Understanding of prompt engineering for text summarization
Service Value
Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.
Apps Used
Details
How to Use
- 1.Click "Download Template"
- 2.Open your n8n dashboard
- 3.Go to Workflows > Import from File
- 4.Select downloaded file and configure credentials
Nodes Used (22)
When clicking "Test workflow"
Manual Trigger
Google Drive
Google Drive
Get Color Information
Edit Image
Resize Image
Edit Image
Default Data Loader
Document Default Data Loader
Recursive Character Text Splitter
Text Splitter Recursive Character Text Splitter
Sticky Note
Sticky Note
Sticky Note1
Sticky Note
Sticky Note2
Sticky Note
Combine Image Analysis
Merge
Document for Embedding
Set
Sticky Note3
Sticky Note
Sticky Note4
Sticky Note
Sticky Note5
Sticky Note
Sticky Note6
Sticky Note
Embeddings OpenAI1
OpenAI
Sticky Note7
Sticky Note
Sticky Note8
Sticky Note
Get Image Keywords
OpenAI
In-Memory Vector Store
Vector Store In Memory
Embeddings OpenAI
OpenAI
Search for Image
Vector Store In Memory