Extract and intelligently search Google Drive documents with AI
Workflow Description
Automation that retrieves files from Google Drive, splits document content into manageable text chunks, converts them into vector embeddings using OpenAI, and stores them in memory for semantic search and intelligent document retrieval.
How it works
- 1.Start automation manually with user input or trigger
- 2.Fetch files and folders from Google Drive storage
- 3.Split document content into smaller text segments for processing
- 4.Generate vector embeddings for each segment using OpenAI models
- 5.Store embeddings in memory-based vector store for fast retrieval
- 6.Query documents semantically and return relevant results
Use cases
- Semantic search across enterprise document archives and repositories
- Analyze stored documents and generate intelligent summaries on demand
Requirements
- Active Google account with full access permissions to Google Drive
- Valid OpenAI API key configured for embedding generation
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
In-Memory Vector Store
Vector Store In Memory
Embeddings OpenAI
OpenAI
Search for Image
Vector Store In Memory
Get Image Keywords
OpenAI