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Unlike standard LLM responses, which are plain text or markdown, a C1 Response is a string that is structured payload to contain rich content. It uses an XML-like structure to package multiple types of content into a single string. It is generally stored as assistant message content in the database. 
<!-- A C1 Response can contain multiple content types -->
<thinking>...</thinking><content>...</content><artifact>...</artifact>

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Node.js SDK (@thesysai/genui-sdk/server)

This SDK provides a function to create a Response Builder object that manages the creation and streaming of the C1 Response. 
import { makeC1Response } from "@thesysai/genui-sdk/server";
import { transformStream } from "@crayonai/stream";

export async function POST(req: NextRequest) {
  const c1Response = makeC1Response();
  // ... use c1Response methods ...
  return new NextResponse(c1Response.responseStream, {
    headers: { "Content-Type": "text/event-stream" },
  });
}

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Main Function

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makeC1Response()
C1ResponseBuilder
Creates and returns an instance of the Response Builder object.

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Response Builder Methods

The object returned by makeC1Response() has the following methods and properties:
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writeContent
(content: string) => void
Pipes the raw string response from a C1 API call (e.g., from the Generative UI or Artifacts endpoint) into the response stream.
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writeCustomMarkdown
(markdown: string) => void
Adds a custom markdown response to the stream. This will be wrapped in <custom_markdown> tags.
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writeThinkItem
(item: ThinkItem) => void
Adds a thinking state entry to the <thinking> part of the response stream.
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end
() => void
Signals that the stream is complete and closes it. This should be called in the onEnd callback of your stream processing.
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responseStream
ReadableStream
The ReadableStream object that should be returned from your API route.

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Python SDK (thesys_genui_sdk)

The thesys_genui_sdk package provides the C1Response class, which acts as the Response Builder. Please refer to the Python SDK Reference for more details.

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A Practical Example: Adding Thinking States

A common use case for the Response Builder is to add real-time thinking state indicators to the stream before the main content from the LLM arrives. This significantly improves the user’s perception of responsiveness. For a complete, step-by-step example of how to use these helpers, see the Thinking States guide.