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The chat window is the fastest way to use a prompt in your library. You pick a prompt, pick a model, fill in any variables, and run it — all from the same conversation. Switching models is a one-click operation, so you can compare how the same prompt behaves on different providers without copying anything around.

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Opening a prompt in chat

There are two entry points:
  1. From the Prompt Library — open a prompt and click Run in chat. A new chat tab opens with the prompt preloaded.
  2. From inside chat — click the library icon in the chat composer and pick a prompt. The prompt body is inserted into the composer with variable placeholders highlighted.

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Filling in variables

If the prompt uses {{variable_name}} placeholders, Blueprint shows an inputs panel above the composer. Each variable becomes a labeled field. Fill them in, then click Run — Blueprint substitutes the values into the prompt body before sending it to the model.

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Choosing a model

The chat window has a model picker in the top-right of every tab. Click it to see every model your workspace has access to, grouped by provider:
  • OpenAI
  • Anthropic
  • Google
  • Meta
  • Mistral, Cohere, DeepSeek, AWS
  • Any custom model you have added via AI providers, including self-hosted models behind an OpenAI-compatible endpoint
The picker shows the per-1K-token price and context window next to each model so you can pick deliberately.

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Switching mid-conversation

You can change the model at any point in a chat. Click the picker, choose a new model, and the next message uses the new model. Earlier messages keep the model they were originally generated with — the chat transcript shows a small badge next to each assistant message identifying which model produced it.

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Re-running against a different model

Hover over any assistant response and click Re-run with… to regenerate that same message against a different model. The new response appears as a sibling to the original, and you can flip between them with the arrow controls. This is the fastest way to compare how, say, Claude and GPT-4o handle the same prompt.

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Saving a chat run back to the library

If you tweaked the prompt body inline before running, click Save changes to library on the prompt header. Blueprint creates a new version on the source prompt with your edits — see Prompt collaboration for how versions work. If you want to keep the tweak as a separate prompt instead, click Save as new prompt and pick a scope.

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Running prompts programmatically

The chat experience is convenient for iteration, but the same library prompts are available from Blueprints and the API:
  • In a Blueprint — add a prompt node and select From library. Reference the prompt by ID; updates to the library prompt flow through automatically.
  • From the API — call POST /v1/prompts/{id}/run with a model parameter and a variables object. See the API reference for the full schema.

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Limitations

  • The chat window streams responses for any model that supports streaming. For models that do not, the full response appears at once when generation finishes.
  • Vision and tool-use features depend on the selected model — the input area will hide the Attach image button on text-only models.
  • Re-running an old message against a new model does not replay any tool calls that happened in the original run.