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src/routes/api/aiMarkDrawing.js

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+const aiMarkDrawing = async (req, res) => {
+
+  
+  const express = require('express');
+const fetch = require('node-fetch'); // For making HTTP requests
+const path = require('path');
+const fs = require('fs');
+
+// Create an Express app
+const app = express();
+const port = 3000;
+
+// Middleware to handle JSON and URL-encoded form data
+app.use(express.json());
+app.use(express.urlencoded({ extended: true }));
+
+// Replace with your OpenAI API key
+const OPENAI_API_KEY = 'your-openai-api-key';
+
+// Route to handle image upload and forward it to OpenAI API
+app.post('/upload-image', async (req, res) => {
+    try {
+        // Check if the file is included in the request
+        if (!req.headers['content-type']?.includes('multipart/form-data')) {
+            return res.status(400).send({ message: 'No file uploaded' });
+        }
+
+        // Extract the raw body data (binary) from the request
+        let imageBuffer = Buffer.alloc(0);
+
+        // Collect the image data from the stream (raw body)
+        req.on('data', chunk => {
+            imageBuffer = Buffer.concat([imageBuffer, chunk]);
+        });
+
+        req.on('end', async () => {
+            // Forward the image to OpenAI's API for scoring
+            const score = await sendImageToOpenAI(imageBuffer);
+
+            // Respond with the score
+            res.json({ score: score });
+        });
+
+    } catch (error) {
+        console.error('Error processing the image:', error);
+        res.status(500).send({ message: 'Internal Server Error' });
+    }
+});
+
+// Function to send image to OpenAI API and get the response
+async function sendImageToOpenAI(imageBuffer) {
+    try {
+        // Convert binary image data to base64 format
+        const imageBase64 = imageBuffer.toString('base64');
+
+        // Make a request to the OpenAI API using fetch
+        const response = await fetch('https://api.openai.com/v1/chat/completions', {
+            method: 'POST',
+            headers: {
+                'Authorization': `Bearer ${OPENAI_API_KEY}`,
+                'Content-Type': 'application/json',
+            },
+            body: JSON.stringify({
+                model: "gpt-4-vision", // Use the appropriate model
+                messages: [
+                    { role: "system", content: "You are a grading assistant for 2nd grade students." },
+                    { role: "user", content: "Evaluate this student's drawing or coloring." }
+                ],
+                functions: {
+                    function_call: {
+                        name: "vision_function",
+                        args: {
+                            image: imageBase64 // Send the image in base64 format
+                        }
+                    }
+                }
+            })
+        });
+
+        // Parse the response
+        const data = await response.json();
+
+        // Extract the score or other relevant information from the response
+        const aiResponse = data.choices[0].message.content;
+
+        // You can parse this response and extract the score, for example:
+        const score = extractScoreFromResponse(aiResponse);
+        return score;
+
+    } catch (error) {
+        console.error('Error interacting with OpenAI API:', error);
+        throw error;
+    }
+}
+
+// Example function to extract a score from OpenAI's response (you need to define this based on the actual response structure)
+function extractScoreFromResponse(responseText) {
+    // You can use a regex or logic to extract the score from OpenAI's response
+    const scoreMatch = responseText.match(/score:\s*(\d+)/i);
+    if (scoreMatch) {
+        return parseInt(scoreMatch[1], 10);
+    } else {
+        // If no score is found, return a default value
+        return 0;
+    }
+}
+
+// Start the server
+app.listen(port, () => {
+    console.log(`Server running at http://localhost:${port}`);
+});
+
+
+}
+
+module.exports = aiMarkDrawing;