How I Built a Multi-Platform AI Chatbot with n8n and LangBot

Connecting n8n's visual workflow automation with LangBot's multi-platform bot framework creates a powerful, code-free way to deploy AI chatbots across QQ, WeChat, Discord, Telegram, Slack, and more. This tutorial shows you how to integrate these tools in minutes.

What You'll Need

• Python 3.8+ installed
• Node.js 18+ installed
• npm or npx available
• 15 minutes of your time

Deploy LangBot in 3 Commands

LangBot is a production-ready bot framework that connects to multiple messaging platforms and AI services including Dify, FastGPT, Coze, OpenAI, Claude, and Gemini. Deploy it instantly:

cd your-workspace
mkdir -p langbot-instance && cd langbot-instance
uvx langbot@latest

On first launch, LangBot initializes automatically. Open http://127.0.0.1:5300 in your browser.

Register your admin account when prompted. You'll land on the dashboard where you can manage bots, models, pipelines, and integrations.

Set Up n8n Workflow Automation

n8n is an open-source automation platform with 400+ integrations and powerful AI capabilities. Launch it locally:

cd your-workspace
mkdir -p n8n-data
export N8N_USER_FOLDER=$(pwd)/n8n-data
npx n8n

Visit http://127.0.0.1:5678 and create your owner account.

Build Your AI Workflow

Create a new workflow in n8n. You'll need two essential nodes:

Add the Webhook Trigger

Click "+" on the canvas and add a Webhook node. Configure it:

• HTTP Method: POST
• Response Mode: Streaming (enables real-time chat responses)
• Authentication: None (adjust for production)

Add the AI Agent

Press Tab, navigate to the "AI" category, and select AI Agent.

Configure the Chat Model: Click "Chat Model" and choose "OpenAI Chat Model". Add your credentials:

• API Key: Your OpenAI API key (or compatible service key)
• Base URL: For OpenAI alternatives like Claude, Gemini, or local models, update to your provider's endpoint

Critical Step - Fix the Prompt Source: By default, the AI Agent expects a Chat Trigger node, which won't work with webhooks. Here's how to fix it:

1. Find "Source for Prompt (User Message)" in the AI Agent settings
2. Change from "Connected Chat Trigger Node" to "Define below"
3. Switch to "Expression" mode
4. Enter: {{ $json.body }}

This expression pulls the user's message from the webhook request body.

Activate and Get Your Webhook URL

Save the workflow and toggle the activation switch (top-right). Switch to the "Production URL" tab and copy the webhook URL:

http://localhost:5678/webhook/{your-webhook-id}

Connect LangBot to n8n

Back in the LangBot dashboard, navigate to Pipelines and click the default "ChatPipeline".

Switch to the AI tab and select "n8n Workflow API" from the Runner dropdown. Configure:

• Webhook URL: Paste your n8n production webhook URL
• Authentication Type: None (match your n8n webhook settings)
• Timeout: 120 seconds
• Output Key: response

Click Save.

Test It Out

In the Pipeline editor, click "Debug Chat" on the left sidebar. Send a test message like "What is LangBot?"

If everything works, you'll see LangBot send the message to n8n, where the AI Agent processes it and streams back a response.

Troubleshooting

Error: "Expected to find the prompt in an input field called 'chatInput'"

This means the AI Agent is still configured for a Chat Trigger node. Fix it:

1. Open the AI Agent configuration
2. Set "Source for Prompt (User Message)" to "Define below"
3. Switch to Expression mode
4. Enter: {{ $json.body }}

Test Your Webhook Directly

Verify the webhook works with curl:

curl -X POST http://localhost:5678/webhook/your-webhook-id \
  -H "Content-Type: application/json" \
  -d '{"body": "Hello, can you introduce yourself?"}'

You should receive streaming JSON with the AI's response.

How the Integration Works

Here's the complete flow:

1. User sends a message via QQ, WeChat, Discord, Telegram, Slack, LINE, or any LangBot-supported platform
2. LangBot's Pipeline receives the message and calls the n8n Workflow API
3. n8n's Webhook node captures the request and passes it to the AI Agent
4. The AI Agent uses OpenAI, Claude, Gemini, or your configured LLM to generate a response
5. n8n streams the response back to LangBot
6. LangBot delivers the response to the user on their original platform

Why This Combination Works

LangBot + n8n unlocks powerful capabilities:

1. No-Code AI Logic: Design conversation flows visually in n8n without touching code
2. Multi-Platform Reach: Deploy the same AI across QQ, WeChat, Discord, Telegram, Slack, LINE, DingTalk, and Lark simultaneously
3. Flexible AI Models: Swap between OpenAI GPT, Anthropic Claude, Google Gemini, Coze, Dify, local models, and more
4. Rich Integrations: Connect n8n's 400+ integrations - databases, APIs, Notion, Airtable, Google Sheets, Slack, and beyond
5. Tool-Calling Agents: AI Agent can trigger n8n tools like database queries, API calls, or custom functions
6. Workflow Extensions: Add preprocessing, content moderation, logging, or custom business logic

Perfect For:

• Enterprise customer support bots
• Knowledge base Q&A systems
• Multi-platform community management
• Task automation assistants
• Unified chat interfaces for teams

Next Steps

Extend your bot further:

• Integrate Dify or FastGPT for advanced RAG (retrieval-augmented generation)
• Add vector database nodes (Pinecone, Qdrant, Weaviate) for knowledge retrieval
• Connect business APIs for real-time data
• Implement conversation memory and context tracking
• Add content filtering and moderation workflows
• Use Langflow or Coze for additional AI orchestration

This integration gives you the flexibility of code-based AI frameworks like LangChain with the simplicity of visual workflow builders - all while reaching users across every major messaging platform.

Ready to deploy your multi-platform AI assistant? Start with LangBot and n8n today.