makeReal.tsx

import { Editor, TLShapeId, createShapeId } from '@tldraw/tldraw'
import { ResponseShape } from './ResponseShape/ResponseShape'
import { getSelectionAsImageDataUrl } from './lib/getSelectionAsImageDataUrl'
import {
	GPT4VCompletionResponse,
	GPT4VMessage,
	MessageContent,
	fetchFromOpenAi,
} from './lib/fetchFromOpenAi'

// the system prompt explains to gpt-4 what we want it to do and how it should behave.
const systemPrompt = `You are an expert web developer who specializes in tailwind css.
A user will provide you with a low-fidelity wireframe of an application. 
You will return a single html file that uses HTML, tailwind css, and JavaScript to create a high fidelity website.
Include any extra CSS and JavaScript in the html file.
If you have any images, load them from Unsplash or use solid colored rectangles.
The user will provide you with notes in blue or red text, arrows, or drawings.
The user may also include images of other websites as style references. Transfer the styles as best as you can, matching fonts / colors / layouts.
They may also provide you with the html of a previous design that they want you to iterate from.
Carry out any changes they request from you.
In the wireframe, the previous design's html will appear as a white rectangle.
For your reference, all text from the image will also be provided to you as a list of strings, separated by newlines. Use them as a reference if any text is hard to read.
Use creative license to make the application more fleshed out.
Use JavaScript modules and unpkg to import any necessary dependencies.

Respond ONLY with the contents of the html file.`

export async function makeReal(editor: Editor) {
	// we can't make anything real if there's nothing selected
	const selectedShapes = editor.getSelectedShapes()
	if (selectedShapes.length === 0) {
		throw new Error('First select something to make real.')
	}

	// first, we build the prompt that we'll send to openai.
	const prompt = await buildPromptForOpenAi(editor)

	// then, we create an empty response shape. we'll put the response from openai in here, but for
	// now it'll just show a spinner so the user knows we're working on it.
	const responseShapeId = makeEmptyResponseShape(editor)

	try {
		// If you're using the API key input, we preference the key from there.
		// It's okay if this is undefined—it will just mean that we'll use the
		// one in the .env file instead.
		const apiKeyFromDangerousApiKeyInput = (
			document.body.querySelector('#openai_key_risky_but_cool') as HTMLInputElement
		)?.value

		// make a request to openai. `fetchFromOpenAi` is a next.js server action,
		// so our api key is hidden.
		const openAiResponse = await fetchFromOpenAi(apiKeyFromDangerousApiKeyInput, {
			model: 'gpt-4-vision-preview',
			max_tokens: 4096,
			temperature: 0,
			messages: prompt,
		})

		// populate the response shape with the html we got back from openai.
		populateResponseShape(editor, responseShapeId, openAiResponse)
	} catch (e) {
		// if something went wrong, get rid of the unnecessary response shape
		editor.deleteShape(responseShapeId)
		throw e
	}
}

async function buildPromptForOpenAi(editor: Editor): Promise<GPT4VMessage[]> {
	// the user messages describe what the user has done and what they want to do next. they'll get
	// combined with the system prompt to tell gpt-4 what we'd like it to do.
	const userMessages: MessageContent = [
		{
			type: 'image_url',
			image_url: {
				// send an image of the current selection to gpt-4 so it can see what we're working with
				url: await getSelectionAsImageDataUrl(editor),
				detail: 'high',
			},
		},
		{
			type: 'text',
			text: 'Turn this into a single html file using tailwind.',
		},
		{
			// send the text of all selected shapes, so that GPT can use it as a reference (if anything is hard to see)
			type: 'text',
			text: getSelectionAsText(editor),
		},
	]

	// if the user has selected a previous response from gpt-4, include that too. hopefully gpt-4 will
	// modify it with any other feedback or annotations the user has left.
	const previousResponseContent = getContentOfPreviousResponse(editor)
	if (previousResponseContent) {
		userMessages.push({
			type: 'text',
			text: previousResponseContent,
		})
	}

	// combine the user prompt with the system prompt
	return [
		{ role: 'system', content: systemPrompt },
		{ role: 'user', content: userMessages },
	]
}

function populateResponseShape(
	editor: Editor,
	responseShapeId: TLShapeId,
	openAiResponse: GPT4VCompletionResponse
) {
	if (openAiResponse.error) {
		throw new Error(openAiResponse.error.message)
	}

	// extract the html from the response
	const message = openAiResponse.choices[0].message.content
	const start = message.indexOf('<!DOCTYPE html>')
	const end = message.indexOf('</html>')
	const html = message.slice(start, end + '</html>'.length)

	// update the response shape we created earlier with the content
	editor.updateShape<ResponseShape>({
		id: responseShapeId,
		type: 'response',
		props: { html },
	})
}

function makeEmptyResponseShape(editor: Editor) {
	const selectionBounds = editor.getSelectionPageBounds()
	if (!selectionBounds) throw new Error('No selection bounds')

	const newShapeId = createShapeId()
	editor.createShape<ResponseShape>({
		id: newShapeId,
		type: 'response',
		x: selectionBounds.maxX + 60,
		y: selectionBounds.y,
	})

	return newShapeId
}

function getContentOfPreviousResponse(editor: Editor) {
	const previousResponses = editor
		.getSelectedShapes()
		.filter((shape): shape is ResponseShape => shape.type === 'response')

	if (previousResponses.length === 0) {
		return null
	}

	if (previousResponses.length > 1) {
		throw new Error('You can only have one previous response selected')
	}

	return previousResponses[0].props.html
}

function getSelectionAsText(editor: Editor) {
	const selectedShapeIds = editor.getSelectedShapeIds()
	const selectedShapeDescendantIds = editor.getShapeAndDescendantIds(selectedShapeIds)

	const texts = Array.from(selectedShapeDescendantIds)
		.map((id) => {
			const shape = editor.getShape(id)
			if (!shape) return null
			if (
				shape.type === 'text' ||
				shape.type === 'geo' ||
				shape.type === 'arrow' ||
				shape.type === 'note'
			) {
				// @ts-expect-error
				return shape.props.text
			}
			return null
		})
		.filter((v) => v !== null && v !== '')

	return texts.join('\n')
}