index.js

const os = require('os')
const bytes = require('bytes')
const sharp = require('sharp')
const morgan = require('morgan')
const express = require('express')
const PDFDocument = require('pdfkit')
const axios = require("axios")
const FormData = require("form-data")
const tfjs = require('@tensorflow/tfjs-node')
const nsfwjs = require('nsfwjs')
const jpegjs = require('jpeg-js')
const fileType = require("file-type")
//const { BingChat } = (await import("bing-chat")).default

const { sss_instagram, gramvio } = require("./lib/instagram.js")
const { allToJpg } = require("./lib/convertFormat.js")
const apikey = "@SadTeam77"

const app = express()
app.set('json spaces', 4)
app.use(morgan('dev'))
app.use(express.json({ limit: "500mb" }))
app.use(express.urlencoded({ limit: '500mb', extended: true }))
app.use((req, res, next) => {
  load_model(),
  next()
})

app.all('/', (req, res) => {
	const status = {}
	const used = process.memoryUsage()
	for (let key in used) status[key] = formatSize(used[key])
	
	const totalmem = os.totalmem()
	const freemem = os.freemem()
	status.memoryUsage = `${formatSize(totalmem - freemem)} / ${formatSize(totalmem)}`
	
	res.json({
		creator: "@SadTeams",
		message: 'Hello World!!',
		uptime: new Date(process.uptime() * 1000).toUTCString().split(' ')[4],
		status
	})
})

app.post('/imagetopdf', async (req, res) => {
	try {
		console.log(req.body)
		const { images } = req.body
		if (!images) return res.json({ success: false, message: 'Required an array image url' })
		
		const buffer = await toPDF(images)
		res.setHeader('Content-Disposition', `attachment; filename=${Math.random().toString(36).slice(2)}.pdf`)
		res.setHeader('Content-Type', 'application/pdf')
		res.setHeader('Content-Length', buffer.byteLength)
		res.send(buffer)
	} catch (e) {
		console.log(e)
		e = String(e)
		res.json({ error: true, message: e === '[object Object]' ? 'Internal Server Error' : e })
	}
})

app.post('/api/chatgpt', async (req, res) => {
	try {
		console.log(req.body)
		const { prompt, model, status } = req.body
		if (!prompt) return res.json({ success: false, message: 'Required an prompt text!' })
        if (!model) return res.json({ success: false, message: 'Required an model version!' })
        if (!status) return res.json({ success: false, message: 'Required an prompt text!' })

        if(status !== apikey) return res.json({ success: false, message: 'Invalid status!' })
		const response = await acytoo(prompt, model)
        res.json({
          status: "ok",
          result: response
        })
	} catch (e) {
		console.log(e)
		e = String(e)
		res.json({ error: true, message: e === '[object Object]' ? 'Internal Server Error' : e })
	}
})
app.post('/api/chatgpt2', async (req, res) => {
	try {
		console.log(req.body)
		const { data, prompt, status } = req.body
        if (!data) return res.json({ success: false, message: 'Required an data text!' })
		if (!prompt) return res.json({ success: false, message: 'Required an prompt text!' })
        if (!status) return res.json({ success: false, message: 'Required an status text!' })

        if(status !== apikey) return res.json({ success: false, message: 'Invalid status!' })
		const response = await axios.request({
          method: "GET",
          url: `https://aemt.me/prompt/gpt?prompt=${data}&text=${prompt}`
        })
        res.json({
          status: "ok",
          result: response.data.result
        })
	} catch (e) {
		console.log(e)
		e = String(e)
		res.json({ error: true, message: e === '[object Object]' ? 'Internal Server Error' : e })
	}
})
app.post('/api/toanime', async (req, res) => {
	try {
		console.log(req.body)
		const { url, status } = req.body
        if (!url) return res.json({ success: false, message: 'Required an url!' })
        if (!status) return res.json({ success: false, message: 'Required an status text!' })

        if(status !== apikey) return res.json({ success: false, message: 'Invalid status!' })
		const response = await axios.request({
          method: "GET",
          url: `https://aemt.me/toanime?url=${url}`
        })
        const image = await axios.request({
          method: "GET", 
          url: response.data.url.img_crop_single,
          responseType: "arraybuffer" 
        })
        res.setHeader('Content-Type', 'image/jpeg')
        res.send(image.data)
	} catch (e) {
		console.log(e)
		e = String(e)
		res.json({ error: true, message: e === '[object Object]' ? 'Internal Server Error' : e })
	}
})
app.post('/api/waifu2x', async (req, res) => {
	try {
		console.log(req.body)
		const { images, format, status } = req.body
        if (!images) return res.json({ success: false, message: 'Required an images!' })
        if (!format) return res.json({ success: false, message: 'Required an format size!' })
        if (!status) return res.json({ success: false, message: 'Required an status text!' })

        if(status !== apikey) return res.json({ success: false, message: 'Invalid status!' })
        if (/^(https?|http):\/\//i.test(images)) {
          const data_img = await axios.request({
            method: "GET",
            url: images,
            responseType: "arraybuffer"
          })
          const response = await waifu2x(data_img.data, format)
          res.setHeader('Content-Type', 'image/jpg')
          res.send(response)
        } else if (images && typeof images == 'string' && isBase64(images)) {
	   	  const response = await waifu2x(Buffer.from(images, "base64"), format)
          res.setHeader('Content-Type', 'image/jpg')
          res.send(response)
        } else {
          res.json({
            success: false, message: 'No url or base64 detected!!' 
          })
        }
	} catch (e) {
		console.log(e)
		e = String(e)
		res.json({ error: true, message: e === '[object Object]' ? 'Internal Server Error' : e })
	}
})
app.post('/api/nsfw-check', async (req, res) => {
	try {
		console.log(req.body)
		const { images, status } = req.body
        if (!images) return res.json({ success: false, message: 'Required an images!' })
        if (!status) return res.json({ success: false, message: 'Required an status text!' })

        if(status !== apikey) return res.json({ success: false, message: 'Invalid status!' })
        if (/^(https?|http):\/\//i.test(images)) {
          const data_img = await axios.request({
            method: "GET",
            url: images,
            responseType: "arraybuffer"
          })
          const response = await check_nsfw(data_img.data)
          res.json({
            status: "ok",
            result: response
          })
        } else if (images && typeof images == 'string' && isBase64(images)) {
	   	  const img = Buffer.from(images, "base64")
          const type = await fileType.fromBuffer(img)
          if (type.ext == "jpg") {
            let response = await check_nsfw(img)
            res.json({
              status: "ok",
              result: response
            })
          }
          if (type.ext == "webp") {
            let converting = await allToJpg(img)
            let response = await check_nsfw(converting)
            res.json({
              status: "ok",
              result: response
            })
          }
        } else {
          res.json({
            success: false, message: 'No url or base64 detected!!' 
          })
        }
	} catch (e) {
		console.log(e)
		e = String(e)
		res.json({ error: true, message: e === '[object Object]' ? 'Internal Server Error' : e })
	}
})
app.post('/api/instagram/stalk', async (req, res) => {
	try {
		console.log(req.body)
		const { username, status } = req.body
        if (!username) return res.json({ success: false, message: 'Required an username text!' })
        if (!status) return res.json({ success: false, message: 'Required an status text!' })

        if(status !== apikey) return res.json({ success: false, message: 'Invalid status!' })
		const response = await gramvio(username)
        res.json({
          status: "ok",
          result: response
        })
	} catch (e) {
		console.log(e)
		e = String(e)
		res.json({ error: true, message: e === '[object Object]' ? 'Internal Server Error' : e })
	}
})
app.post('/api/instagram/download', async (req, res) => {
	try {
		console.log(req.body)
		const { url, status } = req.body
        if (!url) return res.json({ success: false, message: 'Required an url!' })
        if (!status) return res.json({ success: false, message: 'Required an status text!' })

        if(status !== apikey) return res.json({ success: false, message: 'Invalid status!' })
		const response = await sss_instagram(url)
        res.json({
          status: "ok",
          result: response
        })
	} catch (e) {
		console.log(e)
		e = String(e)
		res.json({ error: true, message: e === '[object Object]' ? 'Internal Server Error' : e })
	}
})
/*app.post('/api/bingchat', async (req, res) => {
	try {
		console.log(req.body)
		const { prompt, status } = req.body
        if (!prompt) return res.json({ success: false, message: 'Required an prompt text!' })
        if (!status) return res.json({ success: false, message: 'Required an status text!' })

        if(status !== apikey) return res.json({ success: false, message: 'Invalid status!' })
		const api = new BingChat({
          cookie: process.env.BING_COOKIE
        })
        const resonse = await api.sendMessage(prompt)
        res.json({
          status: "ok",
          result: response.text
        })
	} catch (e) {
		console.log(e)
		e = String(e)
		res.json({ error: true, message: e === '[object Object]' ? 'Internal Server Error' : e })
	}
})*/

const PORT = process.env.PORT || 7860
app.listen(PORT, () => {
  console.log('App running on port', PORT)
})                         

function formatSize(num) {
	return bytes(+num || 0, { unitSeparator: ' ' })
}
function isBase64(str) {
	try {
		return btoa(atob(str)) === str
	} catch {
		return false
	}
}
function toPDF(urls) {
	return new Promise(async (resolve, reject) => {
		try {
			if (!Array.isArray(urls)) urls = [urls]
			const doc = new PDFDocument({ margin: 0, size: 'A4' })
			const buffers = []
			
			for (let i = 0; i < urls.length; i++) {
				const response = await fetch(urls[i], { headers: { referer: urls[i] }})
				if (!response.ok) continue
				
				const type = response.headers.get('content-type')
				if (!/image/.test(type)) continue
				
				let buffer = Buffer.from(await response.arrayBuffer())
				if (/gif|webp/.test(type)) buffer = await sharp(buffer).png().toBuffer()
				
				doc.image(buffer, 0, 0, { fit: [595.28, 841.89], align: 'center', valign: 'center' })
				if (urls.length !== i + 1) doc.addPage()
			}
			
			doc.on('data', (chunk) => buffers.push(chunk))
			doc.on('end', () => resolve(Buffer.concat(buffers)))
			doc.on('error', reject)
			doc.end()
		} catch (e) {
			console.log(e)
			reject(e)
		}
	})
}
async function acytoo(text, model) {
    let res = await axios.request({
        method: "POST",
        url: "https://chat.acytoo.com/api/completions",
        data: JSON.stringify({
            key: "",
            messages: [{
                role: "user", 
                content: text,
                createAt: "",
            }],
            model: model,
            password: "",
            temprature: 1
        }),
        headres: {
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36",
            "Origin": "https://chat.acytoo.com"
        }
    })
  return res.data
}
async function waifu2x(image, formats) {
    // data
  //let img = await axios.get(urls, { responseType: "arraybuffer"})
  let random_numbers = Math.floor(Math.random() * 1000)
  let format
    if(formats == "Medium") {
      format = "1"
    } else if(formats == "High") {
      format = "2"
    } else if(!formats) {
      format = "0"
    }
    // memasukan data api
    const formData = new FormData()
    formData.append("denoise", format)
    formData.append("scale", "true")
    formData.append("file", image, {
        filename: "images_" + random_numbers.toString().padStart(3, '0') + ".jpg",
        contentType: "image/jpeg"
    })

    // request ke api untuk mendapatkan hash nya
    const response = await axios.request({
        method: "POST",
        url: "https://api.alcaamado.es/api/v1/waifu2x/convert",
        data: formData,
        headers: {
            "Accept": "application/json",
            "Referer": "https://waifu2x.pro/",
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36 Edg/119.0.0.0"
        }
    })

    const ress = await axios.request({
        method: "GET",
        url: "https://api.alcaamado.es/api/v2/waifu2x/check?hash=" + response.data.hash,
        headers: {
            "Accept": "application/json",
            "Referer": "https://waifu2x.pro/",
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36 Edg/119.0.0.0"
        }
    })

    if(!ress.data.finished) return "Images Not Supported!!"

    const images = await axios.request({
          method: "GET",
          url: "https://api.alcaamado.es/api/v2/waifu2x/get?hash=" + response.data.hash + "&type=jpg",
          headers: {
            "Accept": "image/webp,image/apng,image/svg+xml,image/*,*/*;q=0.8",
            "Content-Type": "image/jpg",
            "Referer": "https://waifu2x.pro/",
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36 Edg/119.0.0.0"
          },
          responseType: "arraybuffer"
    })
    return images.data
}
async function check_nsfw(buffer) {
  let _model = await load_model()
  const convert = async (img) => {
  // Decoded image in UInt8 Byte array
    const image = await jpegjs.decode(img, { useTArray: true })

    const numChannels = 3
    const numPixels = image.width * image.height
    const values = new Int32Array(numPixels * numChannels)

    for (let i = 0; i < numPixels; i++)
      for (let c = 0; c < numChannels; ++c)
        values[i * numChannels + c] = image.data[i * 4 + c]

    return tfjs.tensor3d(values, [image.height, image.width, numChannels], 'int32')
  }
  const image = await convert(buffer)
  const predictions = await _model.classify(image)
  image.dispose();
  const results = predictions.map(v => {
    return {
      class_name: v.className,
      probability: v.probability,
      probability_percent: (v.probability * 100).toFixed(2)
    }
  })
  return results
}
async function load_model() {
  return await nsfwjs.load()
}