67 lines
2.4 KiB
TypeScript
67 lines
2.4 KiB
TypeScript
// ./app/api/chat/route.js
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import OpenAI from 'openai'
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import { OpenAIStream, StreamingTextResponse } from 'ai'
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const USER_PROMPT = 'Generate code a web page that looks exactly like this'
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const SYSTEM_PROMPT= `You are an expert Tailwind developer
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You take screenshots of a reference web page from the user, and then build single page apps
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using Tailwind, HTML and JS.
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You might also be given a screenshot(The second image) of a web page that you have already built, and asked to
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update it to look more like the reference image(The first image).
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- Make sure the app looks exactly like the screenshot.
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- Pay close attention to background color, text color, font size, font family,
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padding, margin, border, etc. Match the colors and sizes exactly.
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- Use the exact text from the screenshot.
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- Do not add comments in the code such as "<!-- Add other navigation links as needed -->" and "<!-- ... other news items ... -->" in place of writing the full code. WRITE THE FULL CODE.
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- Repeat elements as needed to match the screenshot. For example, if there are 15 items, the code should have 15 items. DO NOT LEAVE comments like "<!-- Repeat for each news item -->" or bad things will happen.
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- For images, use placeholder images from https://placehold.co and include a detailed description of the image in the alt text so that an image generation AI can generate the image later.
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In terms of libraries,
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- Use this script to include Tailwind: <script src="https://cdn.tailwindcss.com"></script>
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- You can use Google Fonts
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- Font Awesome for icons: <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.15.3/css/all.min.css"></link>
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Return only the full code in <html></html> tags.
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Do not include markdown "\`\`\`" or "\`\`\`html" at the start or end.`
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const openai = new OpenAI({
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apiKey: process.env.OPENAI_API_KEY,
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})
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export const runtime = 'edge' //vs cloud. Edge is faster but more expensive
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export async function POST(req: Request) {
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const { url } = await req.json()
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const response = await openai.chat.completions.create({
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model: 'gpt-4-vision-preview',
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stream: true,
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max_tokens: 4096,
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messages: [
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{
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role: 'system',
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content: SYSTEM_PROMPT,
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},
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{
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role: 'user',
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content: [
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{
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type: 'text',
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text: USER_PROMPT,
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},
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{
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type: 'image_url',
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image_url: url
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},
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],
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}
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],
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});
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const stream = OpenAIStream(response)
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return new StreamingTextResponse(stream)
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}
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