How can I update chat window status messages during an n8n workflow?

Below is an explanation of why you’re having trouble and some workarounds you might consider:

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Why Intermediate Status Updates Aren’t Natively Supported

The Chat Trigger node in n8n is designed so that when a user sends a message (or starts a conversation) the entire workflow is executed and—using the node’s response mode—it sends a single final reply back to the chat window. Every message triggers a new workflow execution, and the node isn’t built to “push” updates during a long-running process like status messages in Ansible or shell scripts.

Webhooks in this context are used to initiate the overall execution rather than to update the chat window mid-execution. This design means that although you can pass data (including metadata) with the initial call, you don’t have a built‐in mechanism for sending multiple incremental responses within one execution.

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Potential Workarounds

1. Splitting the Workflow into Multiple Executions
   One approach is to separate your long-running task into several smaller workflows. Each stage can trigger a new execution that sends a status update back to the chat window. For example, you could:

   • Use the first workflow (with the Chat Trigger) to start the process.
   • At key stages, call a secondary workflow via an HTTP Request node (or an internally exposed webhook) that sends a status update as its output.
   • The chat interface could be built to append new messages as they’re received (this may involve custom front-end logic if using the embedded chat option).

2. Using External Messaging or Real-Time Techniques
   If immediate in-execution updates are critical, you might consider:

   • Implementing a separate service (for example, a small web server with WebSocket support) that your workflow communicates with.
   • The external service then sends real-time updates to your chat window.
     This approach is more advanced and would require building a custom integration between n8n and your chat client.

3. Manually Setting the Chat Response
   While the Chat Trigger node typically takes the output from the last node as its reply, you can also build logic within your workflow to compute a custom response. However, this still results in one final message per execution.
   To do this, make sure you structure your output as a simple string (using a field named text or output), so the chat interface displays exactly what you want.

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Conclusion

There isn’t a native “status update” mechanism built into the Chat Trigger node that works within a single workflow execution. The design of n8n means each conversation message leads to one workflow run with one final reply. If you need periodic updates, you’ll need to architect your solution either by splitting the workflow into multiple status-update triggers or by adding an external real-time communication mechanism.

For further details on configuring the Chat Trigger node and passing additional data (such as metadata), you can refer to the documentation sections on setting the chat response manually and on node options for hosted or embedded chat.

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I hope this helps clarify the limitations and possible approaches for your use case!