WhatsApp dietitian AI chatbot workflow

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Important notice

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

1. Workflow Overview

WhatsApp Dietitian AI Chatbot Workflow Transform your WhatsApp into a professional nutrition consultant with this comprehensive AI powered dietitian assistant. Built using n8n automation and Google...

Best for

Support Chatbot automation workflows
AI Chatbot automation workflows
advanced n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.lmchatgooglegemini, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.whatsapptrigger, n8n-nodes-base.whatsapp, n8n-nodes-base.httprequest, @n8n/n8n-nodes-langchain.chainllm, n8n-nodes-base.switch, n8n-nodes-base.stickynote

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title: WhatsApp dietitian AI chatbot workflow
Workflow name: WhatsApp dietitian AI chatbot workflow

WhatsApp Dietitian AI Chatbot Workflow

Transform your WhatsApp into a professional nutrition consultant with this comprehensive AI-powered dietitian assistant. Built using n8n automation and Google Gemini AI, this workflow provides instant, intelligent nutrition advice to your clients 24/7.

🍽️ What It Does

Meal Analysis: Users can send photos of their meals with captions like "analyze this meal" and receive detailed nutritional breakdowns including calories, macronutrients, and personalized recommendations.

Nutrition Guidance: Answers questions about general nutrition, dietary restrictions, meal planning, and healthy eating habits with evidence-based information.

Meal Recommendations: Suggests customized meals based on specific criteria like calorie targets, dietary preferences (vegan, keto, etc.), or available ingredients.

🚀 Key Features

Dual Input Processing: Handles both text questions and image analysis seamlessly
Professional AI Responses: Uses Google Gemini 2.0 Flash for accurate, contextual nutrition advice
WhatsApp Optimized: Responses formatted specifically for mobile messaging with emojis and clear structure
Smart Routing: Automatically detects message type (text vs image) and processes accordingly
Structured Output: Consistent, professional formatting for all responses
Scope Management: Stays within nutrition expertise and includes appropriate medical disclaimers

🛠️ Technical Stack

Platform: n8n workflow automation
AI Model: Google Gemini 2.0 Flash
Integration: WhatsApp Business API
Message Types: Text messages, images with captions
Output: Structured, conversational responses

📱 Perfect For

Nutritionists and dietitians offering remote consultations
Health coaches providing 24/7 client support
Fitness professionals adding nutrition guidance
Wellness businesses expanding their service offerings
Anyone wanting to monetize nutrition expertise

🎯 Ready to Deploy

This workflow comes with comprehensive documentation, clear setup instructions, and professional prompt engineering. Simply configure your WhatsApp Business API and Google Gemini credentials to start serving clients immediately.

Transform your nutrition expertise into an automated, scalable WhatsApp service that works around the clock!

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 - Google Gemini Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatGoogleGemini - lmChatGoogleGemini
Config choices: Version 1

Block 2 - Structured Output Parser

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

Block 3 - WhatsApp Message Received

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

Block 4 - Get whatsapp image

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

Block 5 - Download Image

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

Block 6 - Send Response to client

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

Block 7 - Generate Response from text

Type / Role: @n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices: Version 1.6

Block 8 - Generate Response from Image and caption

Type / Role: @n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices: Version 1.6

Block 9 - Check if message contains image

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

Block 10 - Sticky Note

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

Block 11 - Sticky Note1

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

Block 12 - Sticky Note2

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

Block 13 - Sticky Note3

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

Block 14 - Sticky Note4

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

Block 15 - Sticky Note5

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

Block 16 - Sticky Note6

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

Block 17 - Sticky Note7

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

3. Summary Table

Workflow	WhatsApp dietitian AI chatbot workflow
Complexity	advanced
Nodes	17
Categories	Support Chatbot, AI Chatbot
Author	Tamer
Published	10 Jun 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/4858/4858.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 Support Chatbot workflows AI Chatbot workflows

Frequently asked questions

What does WhatsApp dietitian AI chatbot workflow 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 Support Chatbot, AI Chatbot use case.

Tamer

6 workflows

Nodes

@n8n/n8n-nodes-langchain.lmchatgooglegemini @n8n/n8n-nodes-langchain.outputparserstructured n8n-nodes-base.whatsapptrigger n8n-nodes-base.whatsapp n8n-nodes-base.httprequest @n8n/n8n-nodes-langchain.chainllm n8n-nodes-base.switch n8n-nodes-base.stickynote

Complexity

advanced

Published 10 Jun 2025

Likes 0

View on n8n.io Download Workflow

Install path: /data/workflows/4858/4858.json

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WhatsApp dietitian AI chatbot workflow

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

WhatsApp Dietitian AI Chatbot Workflow

🍽️ What It Does

🚀 Key Features

🛠️ Technical Stack

📱 Perfect For

🎯 Ready to Deploy

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Google Gemini Chat Model

Block 2 - Structured Output Parser

Block 3 - WhatsApp Message Received

Block 4 - Get whatsapp image

Block 5 - Download Image

Block 6 - Send Response to client

Block 7 - Generate Response from text

Block 8 - Generate Response from Image and caption

Block 9 - Check if message contains image

Block 10 - Sticky Note

Block 11 - Sticky Note1

Block 12 - Sticky Note2

Block 13 - Sticky Note3

Block 14 - Sticky Note4

Block 15 - Sticky Note5

Block 16 - Sticky Note6

Block 17 - Sticky Note7

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