AI Agents
Automate Google Sheets with an AI Agent
11 nodes
311
153
Webhook
Workflow Description
A workflow that routes webhook requests to an AI agent, splits text into chunks, generates embeddings using Hugging Face, stores them in Supabase vector store, maintains conversation memory, processes queries through an intelligent agent, and automatically writes results and responses back to Google Sheets.
How it works
- 1.Receive requests via webhook and route to the AI agent
- 2.Split text content and compute embeddings for semantic search
- 3.Store embeddings and queries in Supabase vector database
- 4.Maintain conversation context using a sliding memory window
- 5.Generate intelligent responses via Hugging Face language model
- 6.Write results, queries, and agent responses to Google Sheets
Use cases
- Build a searchable knowledge base in Google Sheets with AI-powered queries
- Automate data entry and analysis based on natural language questions
- Log and audit all AI agent interactions directly in spreadsheets
- Streamline data workflows with low-code AI intelligence
Requirements
- Hugging Face API key and Supabase project credentials
- Webhook URL to trigger the automation
- Write access to your Google Sheets document
Service Value
Ready-made workflow template for automation delivery and service execution.
Apps Used
Text Splitter
Embeddings
Vector Store
Memory
Lm Chat Hf
AI Agent
Google Sheets
Details
Trigger
Webhook
Nodes
11
Apps
7
Views
311
Downloads
153
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 (11)
/
Sticky
Sticky Note
Webhook
Webhook
Splitter
Text Splitter Character Text Splitter
Embeddings
Embeddings Hugging Face
Insert
Vector Store Supabase
Query
Vector Store Supabase
Tool
Tool Vector Store
Memory
Memory Buffer Window
Chat
Lm Chat Hf
Agent
Agent
Sheet
Google Sheets