manage error + img ratio

app/api/collections/route.ts

@@ -15,5 +15,5 @@ export async function POST(request: Request) {
     }
   })
 
-  return Response.json({ images, status: 200, statusText: "OK" })
+  return Response.json({ images, status: 200, ok: true })
 }

app/api/pipeline.ts

@@ -1,21 +0,0 @@
-import { pipeline, env } from "@xenova/transformers";
-
-// Use the Singleton pattern to enable lazy construction of the pipeline.
-// NOTE: We wrap the class in a function to prevent code duplication (see below).
-process.env.HF_ACCESS_TOKEN = process.env.NEXT_PUBLIC_APP_HF_TOKEN
-
-const P = () => class PipelineSingleton {
-    static task = 'image-classification';
-    static model = 'enzostvs/nsfw-detector-transformersjs';
-    static instance = null;
-
-    static async getInstance(progress_callback: any = null) {
-        if (this.instance === null) {
-            this.instance = pipeline(this.task, this.model, { progress_callback }) as any;
-        }
-        return this.instance;
-    }
-}
-
-const PipelineSingleton = P();
-export default PipelineSingleton;

app/api/route.ts

@@ -1,28 +1,26 @@
 import { PrismaClient } from '@prisma/client'
 
-import PipelineSingleton from './pipeline';
-import { RawImage } from '@xenova/transformers';
-
 const prisma = new PrismaClient()
 
 export async function POST(
   request: Request,
 ) {
+  const global_headers = {
+    Authorization: `Bearer ${process.env.NEXT_PUBLIC_APP_HF_TOKEN}`,
+    'Content-Type': 'application/json',
+    ['x-use-cache']: "0"
+  }
+
   const { inputs, negative_prompt } = await request.json()  
-  const response = await fetch('https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0', {
+  const response = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/models/stabilityai/stable-diffusion-xl-base-1.0`, {
     method: 'POST',
     body: JSON.stringify({
       inputs,
       negative_prompt
     }),
-    headers: {
-      Authorization: `Bearer ${process.env.NEXT_PUBLIC_APP_HF_TOKEN}`,
-      'Content-Type': 'application/json',
-      ['x-use-cache']: "0"
-    },
+    headers: global_headers,
   })
 
-  // avoid json parse error
   const res = await response.clone().json().catch(() => ({}));
   if (res?.error) return Response.json({ status: response.status, ok: false, message: res.error });
 
@@ -30,12 +28,19 @@ export async function POST(
   const headers = new Headers();
   headers.set("Content-Type", "image/*");
 
-  // check if image is not safe for work
-  const file_url = await RawImage.fromBlob(blob)
-  const classifier: any = await PipelineSingleton.getInstance();
-  if (classifier) {
-    const results = await classifier(file_url);
-    if (results?.length && results[0]?.label === "nsfw") {
+  const response_isnsfw = await fetch(`${process.env.NEXT_PUBLIC_API_URL}/models/DamarJati/NSFW-Filterization-DecentScan`, {
+    method: 'POST',
+    headers: {
+      ...global_headers,
+      ...headers,
+    },
+    body: blob,
+  })
+  const isNSFW = await response_isnsfw.clone().json().catch(() => ({}));
+  // if (isNSFW?.error) return Response.json({ status: response.status, ok: false, message: isNSFW.error });
+  if (isNSFW?.length) {
+    const scoreNotSafe = isNSFW?.find((n: { label: string }) => n.label === "no_safe");
+    if (scoreNotSafe?.score > 0.7) {
       return Response.json({ status: 401, ok: false, message: "Image is not safe for work." });
     }
   }

components/modal/modal.tsx

@@ -58,14 +58,20 @@ export const Modal: React.FC<Props> = ({ id, onClose }) => {
     >
       <motion.div
         onClick={(e) => e.stopPropagation()}
-        className="max-w-2xl h-2/3 w-full z-[1] rounded-3xl overflow-hidden flex items-center justify-center flex-col gap-4 bg-white/30 backdrop-blur-sm p-2"
+        className="max-w-2xl h-2/3 w-full z-[1] rounded-3xl overflow-hidden flex items-center justify-center flex-col gap-4 bg-white/30 backdrop-blur-sm px-2 pb-2 pt-6"
         variants={dropIn}
         initial="hidden"
         animate="visible"
         exit="exit"
       >
         <div
-          className="bg-cover bg-center w-full h-full rounded-2xl"
+          className="bg-contain bg-center w-full h-full rounded-2xl bg-no-repeat"
+          style={{
+            backgroundImage: `url(${bufferToBase64})`,
+          }}
+        />
+        <div
+          className="bg-cover bg-center w-full h-full rounded-2xl bg-no-repeat z-[-1] absolute top-0 left-0 opacity-90 blur-xl"
           style={{
             backgroundImage: `url(${bufferToBase64})`,
           }}

package.json

@@ -11,7 +11,6 @@
   "dependencies": {
     "@prisma/client": "^5.5.2",
     "@tanstack/react-query": "^4.32.6",
-    "@xenova/transformers": "^2.7.0",
     "classnames": "^2.3.2",
     "filereader": "^0.10.3",
     "framer-motion": "^10.16.4",

prisma/schema.prisma

@@ -4,7 +4,7 @@ generator client {
 
 datasource db {
   provider = "sqlite"
-  url      = "file://data/dev.db"
+  url      = "file:../data/dev.db"
 }
 
 model Image {