LLM: generate text

The LLM: generate text Point template asks a Claude model for a short piece of text and saves it as a traveler attribute, so a later step can drop it into a push, an email, or an SMS.

This point authenticates with its own Anthropic API key — it doesn’t use any account-level integration configured elsewhere in Settings.

Configure the point

1. Drag LLM: generate text from the Integrations section of the left panel onto the canvas.
2. Double-click the point and enter a Step Name.
3. In Anthropic API key, enter your Anthropic API key. It’s stored masked, like a webhook secret header.
4. In Model, choose claude-haiku-4-5, claude-sonnet-5, or claude-opus-5. Defaults to claude-haiku-4-5. Haiku answers fastest. Opus is slower but still finishes within the point’s 10-second timeout. Every call bills your own Anthropic key for every traveler who reaches this step, and Opus costs more per token than Sonnet or Haiku.
5. In Prompt, write what you want the model to generate. It takes the same macros as any Webhook body, for example {{device:hwid}}.
6. Click Save.

Responses are capped at about 300 tokens (roughly a short paragraph) to keep the request inside the Webhook timeout. Ask for something that short. A longer or more detailed prompt doesn’t get more room to answer.

Response

After the step runs, the generated text is available in later steps as attribute llm_text — use it the same way you’d use a Webhook response attribute, for example with Dynamic Content in a later message. Attributes llm_input_tokens and llm_output_tokens carry the token counts for that request.

A failed request drops the traveler from the journey — see Errors and failed requests. A response that comes back but isn’t what you expected doesn’t drop the traveler: if the model’s answer runs into the 300-token cap, llm_text holds the truncated text. If the model declines to answer, llm_text holds whatever it replied with instead. Either way, the journey continues with that value.