Structured output
Structured output enforces a defined schema for AI agent responses, such as JSON, instead of free-form text.
Why use structured output
- Predictable responses that can be processed by other systems
- Easier automation and system integration
- Reduced ambiguity in free-form responses
Use cases
-
Hybrid chatbots: Detect when to transition from AI agent to chatbot control. Use parameters such as response (message to end user) and isLeaving: true/false.
-
Multimodal responses: Send more than plain text, such as lists, buttons, images, or locations.
Structured output supports these message formats by separating the text message (response) from the format (next_answer_type) and the extra content (suggested_answers).
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Escalation management: Use the escalate_to_human: true parameter to route to live agents.
Example schema
{
"response": "string - Message to display",
"sentiment": "positive|neutral|negative",
"escalate_to_human": "boolean",
"next_answer_type": "text|list|buttons|image",
"suggested_answers": ["array", "of", "options"]
}Using structured output in Answers
When you use structured output, the AI agent returns a JSON object instead of plain text.
To use structured output in Answers, do the following:
- In the Agent connector element, extract the full response by using the JSON path
$.content. - Use a Code element to parse the JSON and extract individual fields into separate attributes.
- Use the extracted values to do the following:
- Display the response text to the end user
- Route based on
escalate_to_humanorisLeavingflags - Determine message format using
next_answer_type - Populate buttons or lists with
suggested_answers
For detailed configuration of the Agent connector element, refer to Use AI agents in Answers.
For agent configuration steps, refer to Configure your agent.