Track study weaknesses from LINE images with Google Gemini and Google Sheets
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 11 nodes and runs when an HTTP POST request hits its webhook URL. Along the way it connects Google Sheets and Google Gemini Chat Model. It also calls api.line.me over HTTP.
How it runs
Trigger: When an HTTP POST request hits its webhook URL.
- Filter: keeps only the items that match a condition
- Fetch LINE Image Data (HTTP Request): calls an HTTP API
- Study Result Analysis Agent (AI Agent): runs an AI agent, with model: Gemini Study Result Model
- Append Study Record to Sheets (Google Sheets): append
- Retrieve Study History from Sheets (Google Sheets): uses Google Sheets
- Compile Study History (Aggregate): combines items into one
- Learning Trends Analysis Agent (AI Agent): runs an AI agent, with model: Gemini Learning Trend Model
- Post Feedback to LINE API (HTTP Request): calls api.line.me (POST)
Services it uses
HTTP calls to: api.line.me
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 (7)
- Webhook
n8n-nodes-base.webhook - HTTP Request
n8n-nodes-base.httpRequest - AI Agent
@n8n/n8n-nodes-langchain.agent - Google Sheets
n8n-nodes-base.googleSheets - Aggregate
n8n-nodes-base.aggregate - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Filter
n8n-nodes-base.filter
From the author
Quick overview This workflow receives study result images from LINE, uses Google Gemini to extract key details and store them in Google Sheets, then analyzes the student’s history to identify weaknesses, generate review questions, and replies with feedback in…