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Create a branded AI chatbot for websites with Flowise multi-agent chatflows

DavideDavide
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2/3/2026
email-notificationgoogle-sheetsdata-exportapi-integrationdaily-automation
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This workflow integrates Flowise Multi-Agent Chatflows into a custom-branded n8n chatbot, enabling real-time interaction between users and AI agents powered by large language models (LLMs).

Key Advantages:

✅ Easy Integration with Flowise:

  • Uses a low-code HTTP node to send user questions to Flowise's API (/api/v1/prediction/FLOWISE_ID) and receive intelligent responses.
  • Supports multi-agent chatflows, allowing for complex, dynamic interactions.

🎨 Customizable Chatbot UI:

  • Includes pre-built JavaScript for embedding the n8n chatbot into any website.
  • Provides customization options such as welcome messages, branding, placeholder text, chat modes (e.g., popup or embedded), and language support.

🔐 Secure & Configurable:

  • Authorization via Bearer token headers for Flowise API access.
  • Clearly marked notes in the workflow for setting environment variables like FLOWISE_URL and FLOW_ID.

How It Works

  1. Chat Trigger: The workflow starts with the When chat message received node, which acts as a webhook to receive incoming chat messages from users.
  2. HTTP Request to Flowise: The received message is forwarded to the Flowise node, which sends a POST request to a Flowise API endpoint (https://FLOWISEURL/api/v1/prediction/FLOWISE_ID). The request includes the user's input as a JSON payload ({"question": "{{ $json.chatInput }}"}) and uses HTTP header authentication (e.g., Authorization: Bearer FLOWSIE_API).
  3. Response Handling: The response from Flowise is passed to the Edit Fields node, which maps the output ($json.text) for further processing or display.

Set Up Steps

  1. Configure Flowise Integration:

    • Replace FLOWISEURL and FLOWISE_ID in the HTTP Request node with your Flowise instance URL and flow ID.
    • Ensure the Authorization header is set correctly in the credentials (e.g., Bearer FLOWSIE_API).

  2. Embed n8n Chatbot:

    • Use the provided JavaScript snippet in the sticky notes to embed the n8n chatbot on your website. Replace YOUR_PRODUCTION_WEBHOOK_URL with the webhook URL generated by the When chat message received node.
    • Customize the chatbot's appearance and behavior (e.g., welcome messages, language, UI elements) using the createChat configuration options.

  3. Optional Branding:

    • Adjust the sticky note examples to include branding details, such as custom messages, colors, or metadata for the chatbot.

  4. Activate Workflow:

    • Toggle the workflow to "Active" in n8n and test the chat functionality end-to-end.

Ideal Use Cases:

  • Embedding branded AI assistants into websites.
  • Connecting Flowise-powered agents with customer support chatbots.
  • Creating dynamic, smart conversational flows with LLMs via n8n automation.

Need help customizing?

Contact me for consulting and support or add me on Linkedin.

n8n Chatbot Integration with Flowise

This n8n workflow demonstrates a basic integration pattern for receiving chat messages and preparing them for further processing, likely with an external AI chatbot platform like Flowise. It acts as an initial listener and data transformer for incoming chat interactions.

What it does

This workflow simplifies the initial handling of chat messages by:

  1. Listening for Chat Messages: It actively waits for and captures incoming chat messages from a configured source.
  2. Preparing Data: It takes the received chat message and transforms it into a structured format, setting a new field called chatMessage with the content of the incoming message.
  3. Making an HTTP Request: It includes an HTTP Request node, which is typically used to send the processed chat message to an external API (e.g., a Flowise instance or another AI service) for generating a response.

Prerequisites/Requirements

  • n8n Instance: A running instance of n8n.
  • Chat Trigger Configuration: The "Chat Trigger" node needs to be configured to listen to your desired chat platform (e.g., Slack, Telegram, Discord, etc.). This usually involves setting up webhooks or API keys on the respective platform and in n8n.
  • Flowise (or other AI Chatbot Platform): An active Flowise instance or another AI chatbot API endpoint to which the HTTP Request node will send the chat message for processing.
  • API Endpoint for AI Service: The URL and any necessary authentication details for your AI chatbot's API.

Setup/Usage

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Chat Trigger:
    • Open the "When chat message received" node.
    • Select or create the appropriate credential for your chat platform (e.g., Slack API, Telegram Bot API).
    • Follow the instructions to set up the webhook or bot on your chosen chat platform to send messages to this n8n workflow.
  3. Configure Edit Fields (Set):
    • This node is pre-configured to extract the chat message. Review it to ensure it correctly maps to the incoming data structure from your chat trigger.
  4. Configure HTTP Request:
    • Open the "HTTP Request" node.
    • Set the URL to your Flowise (or other AI chatbot) API endpoint.
    • Configure the Method (likely POST).
    • Set the Body Parameters to send the chatMessage data. You might need to adjust the JSON structure based on your AI service's API documentation.
    • Add any necessary Headers for authentication (e.g., Authorization header with an API key).
  5. Activate the Workflow: Once configured, activate the workflow to start listening for chat messages.

You can then send a message to your configured chat platform, and the workflow will trigger, process the message, and send it to your AI chatbot. The response from the AI chatbot would typically be handled in subsequent nodes (not included in this basic template) to send back to the original chat platform.

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