Log food calories from images to Google Sheets using LINE and OpenAI Vision

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

This workflow allows a LINE user to send either text or an image of food to a connected LINE bot. If text is sent, the AI agent responds directly via LINE. If an image is sent, the workflow downloa...

Best for

Personal Productivity automation workflows
Multimodal AI automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.switch, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.openai, n8n-nodes-base.set, @n8n/n8n-nodes-langchain.memorybufferwindow, n8n-nodes-base.code, n8n-nodes-base.googlesheets

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by kote2.

Original n8n.io source

1.1 Workflow description

Title: Log food calories from images to Google Sheets using LINE and OpenAI Vision
Workflow name: Log food calories from images to Google Sheets using LINE and OpenAI Vision

This workflow allows a LINE user to send either text or an image of food to a connected LINE bot.

If text is sent, the AI agent responds directly via LINE.

If an image is sent, the workflow downloads it from LINE’s API, analyzes it using OpenAI’s Vision model, estimates calories (only if the image contains food), and formats the result into JSON.

Detected dishes and calories are appended to a Google Sheet, and a confirmation message is sent back to the user via LINE.

Key Features:

Integrates LINE Messaging API webhook with n8n

Uses OpenAI Vision to detect food and estimate calories

Automatically logs results into Google Sheets

Sends real-time feedback to the LINE user

How to use:

Set up a LINE Messaging API channel and get your channel access token.

Add your OpenAI API credentials in n8n.

Replace placeholders for {channel access token}, {your id}, and Google Sheet IDs with your own.

Activate the workflow and send a food image or text message to your LINE bot.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Switch

Type / Role: n8n-nodes-base.switch - switch
Config choices: Version 3.2

Block 2 - AI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 2.1

Block 3 - OpenAI Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

Block 4 - Analyze image

Type / Role: @n8n/n8n-nodes-langchain.openAi - openAi
Config choices: Version 1.8

Block 5 - Edit Fields1

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 6 - Simple Memory

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1.3

Block 7 - Code

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 8 - Append row in sheet

Type / Role: n8n-nodes-base.googleSheets - googleSheets
Config choices: Version 4.6

Block 9 - Code1

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 10 - LINE webhook

Type / Role: n8n-nodes-base.webhook - webhook
Config choices: Version 2

Block 11 - user verification

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.2

Block 12 - images download

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 13 - only message

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 14 - send LINE

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.2

Block 15 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 16 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 17 - Sticky Note2

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

3. Summary Table

Workflow	Log food calories from images to Google Sheets using LINE and OpenAI Vision
Complexity	advanced
Nodes	17
Categories	Personal Productivity, Multimodal AI
Author	kote2
Published	11 Aug 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/7228/7228.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Personal Productivity workflows Multimodal AI workflows

Frequently asked questions

What does Log food calories from images to Google Sheets using LINE and OpenAI Vision do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Personal Productivity, Multimodal AI use case.

kote2

3 workflows

Nodes

n8n-nodes-base.switch @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.lmchatopenai @n8n/n8n-nodes-langchain.openai n8n-nodes-base.set @n8n/n8n-nodes-langchain.memorybufferwindow n8n-nodes-base.code n8n-nodes-base.googlesheets

Complexity

advanced

Published 11 Aug 2025

Likes 0

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Install path: /data/workflows/7228/7228.json

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Log food calories from images to Google Sheets using LINE and OpenAI Vision

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Switch

Block 2 - AI Agent

Block 3 - OpenAI Chat Model

Block 4 - Analyze image

Block 5 - Edit Fields1

Block 6 - Simple Memory

Block 7 - Code

Block 8 - Append row in sheet

Block 9 - Code1

Block 10 - LINE webhook

Block 11 - user verification

Block 12 - images download

Block 13 - only message

Block 14 - send LINE

Block 15 - Sticky Note

Block 16 - Sticky Note1

Block 17 - Sticky Note2

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions