How can I enhance the conversational quality of n8n’s AI agent to match Dify’s output?

Based on the n8n documentation, it’s not that the underlying LLM is inherently limited when used within n8n—it’s more about how the prompt and the surrounding agent configuration are set up. The built-in Conversational Agent node is designed with specific patterns (via default human and system messages) which may be more formal than what you’re used to with Dify.

Here are a few pointers to help you tailor the responses:

1. Customize the Human Message:
   By editing the Human Message node option, you can provide more context and tone guidelines. You can include informal language or even specify that the agent should include emojis and use a step-by-step approach. For example, you could adjust the text to instruct the agent to respond in a friendlier, more conversational tone.

2. Tweak the System Message:
   The System Message can set the overall behavior of the node. If you want responses that are less formal or more dynamic, make sure this message reflects that. This might involve reducing any overly strict instructions that force the agent to follow a more rigid, formal style.

3. Define Your Prompt Explicitly:
   If you switch from “Take from previous node automatically” to “Define below”, you can manually craft a prompt that includes your preferred tone. This way, you have full control over the initial conditions the LLM sees before generating a reply.

4. Review the Pre-Defined Templates:
   The built-in agent comes with default templates and expressions (like {tools}, {format_instructions}, and {{input}}) which are intended to structure tool calls and output format. Altering these (or the surrounding text) slightly might help influence a less “machine-like” output.

5. Experiment with Additional Node Options:
   Although temperature and top P are already set to desired values, changing fields such as “Prefix Prompt” or “Suffix Prompt” might allow you to inject further stylistic guidance. For instance, you might include language like “speak informally” or “add emojis where appropriate.”

In summary, there isn’t a hard limitation with using the Conversational Agent node; it’s more about adjusting the prompt and configuration within n8n to match the conversational style you’re aiming for. This may require some experimentation with the human/system messages and the prompt itself until you achieve responses that mirror the quality you see with Dify.