Handle LINE chat messages with an AI that replies in a supportive tone. Incoming texts get fast, helpful answers, while images or other types receive a clear notice. It suits clinics, wellness brands, and support teams that chat with users on LINE.

An incoming message hits a webhook and starts a loading indicator so the user sees activity. A check splits the path by message type. Non text messages get a polite reply that the format is not supported. Text messages go to an AI agent that uses an Azure OpenAI chat model. A format step turns the AI result into a clean output field. The system then sends a reply on LINE using the reply token, which avoids using broadcast quota. This flow keeps users informed and keeps costs under control.

Set up a LINE Messaging API channel and add the webhook URL from n8n in the LINE console. Create an Azure OpenAI deployment and connect it as the chat model. Expect faster replies, fewer missed chats, and steady quality across hours. Helpful for mental health check ins, guided self help, and general customer questions on LINE.

• LINE webhook receives messages and passes user data to the flow
• Loading indicator call shows the user that a response is in progress
• Message type check routes text and non text content differently
• AI agent uses a clear system prompt to guide supportive responses
• Azure OpenAI chat model powers the conversation with adjustable settings
• Set node formats the AI result into a single output field for sending
• Reply message call returns the answer using the LINE reply token
• Separate path sends a friendly notice when images or other types arrive

• Cut average reply time from minutes to seconds
• Automate up to 90% of common chat questions
• Handle 10x more conversations without extra staff
• Reduce message errors by sending one clean formatted reply
• Lower messaging costs by using the reply token instead of broadcast

1. Import the template into n8n: Create a new workflow in n8n > Click the three dots menu > Select 'Import from File' > Choose the downloaded JSON file.
2. You'll need accounts with LINE Messaging API and Azure OpenAI. See the Tools Required section above for links to create accounts with these services.
3. In the LINE Developers Console create a Messaging API channel. Enable the webhook, copy the Channel access token, and keep the Channel secret ready.
4. Open the Line Chatbot node in n8n and copy the webhook URL. Paste it into the LINE Developers Console as the webhook URL. Remove any test path before moving to production.
5. In the n8n credentials manager create an HTTP Header credential for LINE. Add header name Authorization and value Bearer your LINE channel access token. Assign this credential to the Loading Animation and Reply Message nodes.
6. Open the Loading Animation node and verify the POST URL and JSON body fields. Confirm chatId uses the userId from the incoming event and loadingSeconds is set to your preferred value.
7. Open the Check Message Type IsText node and make sure it checks that the incoming message type equals text. The false path should go to the not supported reply.
8. In Azure create an Azure OpenAI resource and a chat model deployment. Note the endpoint, API key, and deployment name.
9. In n8n create Azure OpenAI credentials. Double click the Azure OpenAI Chat Model node, choose Create new credential, and follow the on screen steps. Enter your endpoint, API key, and deployment details.
10. Open the AI Agent node. Set the system prompt and link it to the Azure OpenAI Chat Model node. Adjust temperature for more creative or more stable replies.
11. Open the Format Reply node and ensure the output field maps to the AI answer. Keep the text within LINE message limits to avoid errors.
12. Test the flow. Send a text to your LINE bot and look for the loading indicator followed by the AI reply. Send an image and confirm you receive the not supported notice. If you see 401 errors check the Authorization header. If replies fail, confirm the reply token mapping and that the webhook is enabled in LINE.