Build a Google Drive document similarity database with Ollama and Postgres
Ready for 3.0What this workflow does
This AI workflow has 56 nodes and runs when a chat message arrives. Along the way it connects Google Drive, Postgres, Postgres PGVector Store and Embeddings Ollama.
How it runs
Trigger: When a chat message arrives.
- Prompt Main Action (Chat): send and wait for a reply
- Route Operations Mode (Switch): routes items into 2 branches
- Prompt Operational Rules (Chat): send and wait for a reply
- Confirm Pipeline Launch (Chat): send and wait for a reply
- Verify Rules Selection (If): checks a condition and branches into true / false
- Validate Launch Parameters (Code): runs custom JavaScript code
- Clear Vector Table (Postgres): delete table
- Broadcast Error Alert (Chat): uses Chat
- Evaluate Validation Results (If): checks a condition and branches into true / false
- Clear Scraped Pages Table (Postgres): delete table
…plus 39 more steps. See the full node list below.
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (17)
- Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches - Google Drive
n8n-nodes-base.googleDrive - HTML
n8n-nodes-base.html - Postgres
n8n-nodes-base.postgres - Postgres PGVector Store
@n8n/n8n-nodes-langchain.vectorStorePGVector - Embeddings Ollama
@n8n/n8n-nodes-langchain.embeddingsOllama - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - Remove Duplicates
n8n-nodes-base.removeDuplicates - Filter
n8n-nodes-base.filter - Convert to File
n8n-nodes-base.convertToFile - Edit Fields (Set)
n8n-nodes-base.set - Code
n8n-nodes-base.code - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - Chat
@n8n/n8n-nodes-langchain.chat - Switch
n8n-nodes-base.switch - If
n8n-nodes-base.if
From the author
Quick overview Builds a searchable semantic similarity database from Google Drive documents using PostgreSQL, PGVector, and Ollama embeddings, then analyzes document similarity and provides interactive internal linking recommendations through chunk-level and…