Multi-LLM customer support chatbot for WordPress & webhook integrations

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Important notice

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

1. Workflow Overview

AI Chat Bot workflow for WordPress & Webhook Live Chats This workflow powers a versatile AI chatbot that can be integrated into any live chat interface, such as our free Forerunner AI Chat Bot for...

Best for

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

Tools used

@n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.stickynote, n8n-nodes-base.set, n8n-nodes-base.webhook, n8n-nodes-base.if, n8n-nodes-base.respondtowebhook, @n8n/n8n-nodes-langchain.toolthink, @n8n/n8n-nodes-langchain.memorybufferwindow

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title: Multi-LLM customer support chatbot for WordPress & webhook integrations
Workflow name: Multi-LLM customer support chatbot for WordPress & webhook integrations

AI Chat Bot workflow for WordPress & Webhook Live Chats

This workflow powers a versatile AI chatbot that can be integrated into any live chat interface, such as our free Forerunner™ AI Chat Bot for WordPress. It's designed to automate customer support and lead generation by handling a variety of user queries independently.

The setup process is straightforward and typically takes less than five minutes. This involves connecting your preferred Large Language Model (LLM) and a live chat platform to the workflow via webhooks.

How the Workflow Works The core of this workflow is an AI Agent that acts as the brain of the chatbot. It processes user input and generates responses based on predefined rules and your chosen language model.

User Input: When a user sends a message through your live chat, it's sent to the workflow via a webhook. This message is then passed to the AI Agent for processing.

AI Response Generation: The AI Agent analyzes the message, retrieves relevant conversational history from the Simple Memory node to maintain context, and uses the selected Large Language Model (e.g., OpenAI, Gemini, or Claude) to formulate a response.

Conditional Logic: After the response is generated, the workflow uses an If node to check if the conversation should end. If the response contains the specific tag [END_OF_CONVERSATION], the workflow prepares to end the chat. Otherwise, the conversation continues.

Send to Client: The final response is then sent back to the live chat interface, where it is displayed to the user. This completes the loop, allowing the chatbot to engage in a continuous conversation until the task is complete.

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 - OpenAI Chat Model

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

Block 2 - Sticky Note

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

Block 3 - Convert Chat Text

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

Block 4 - Website Chat Messages

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

Block 5 - End Conversation?

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

Block 6 - Yes - End

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

Block 7 - No - Continue

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

Block 8 - Send Chat to Client

Type / Role: n8n-nodes-base.respondToWebhook - respondToWebhook
Config choices: Version 1.2

Block 9 - Think

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

Block 10 - Simple Memory

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

Block 11 - Google Gemini Chat Model

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

Block 12 - Forerunner™ AI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.9

Block 13 - Anthropic Chat Model

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

Block 14 - OpenRouter Chat Model

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

Block 15 - xAI Grok Chat Model

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

3. Summary Table

Workflow	Multi-LLM customer support chatbot for WordPress & webhook integrations
Complexity	advanced
Nodes	15
Categories	Support Chatbot, AI Chatbot
Author	Design for Online
Published	30 Aug 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/8062/8062.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 Multi-LLM customer support chatbot for WordPress & webhook integrations do?

AI Chat Bot workflow for WordPress & Webhook Live Chats This workflow powers a versatile AI chatbot that can be integrated into any live chat interface, such as our free Forerunner AI Chat Bot for...

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.

Design for Online

1 workflow

Nodes

@n8n/n8n-nodes-langchain.lmchatopenai n8n-nodes-base.stickynote n8n-nodes-base.set n8n-nodes-base.webhook n8n-nodes-base.if n8n-nodes-base.respondtowebhook @n8n/n8n-nodes-langchain.toolthink @n8n/n8n-nodes-langchain.memorybufferwindow

Complexity

advanced

Published 30 Aug 2025

Likes 0

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Install path: /data/workflows/8062/8062.json

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Multi-LLM customer support chatbot for WordPress & webhook integrations

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

AI Chat Bot workflow for WordPress & Webhook Live Chats

This workflow powers a versatile AI chatbot that can be integrated into any live chat interface, such as our free Forerunner™ AI Chat Bot for WordPress. It's designed to automate customer support and lead generation by handling a variety of user queries independently.

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - OpenAI Chat Model

Block 2 - Sticky Note

Block 3 - Convert Chat Text

Block 4 - Website Chat Messages

Block 5 - End Conversation?

Block 6 - Yes - End

Block 7 - No - Continue

Block 8 - Send Chat to Client

Block 9 - Think

Block 10 - Simple Memory

Block 11 - Google Gemini Chat Model

Block 12 - Forerunner™ AI Agent

Block 13 - Anthropic Chat Model

Block 14 - OpenRouter Chat Model

Block 15 - xAI Grok Chat Model

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