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// Import necessary libraries
import express from "express";
import 'dotenv/config.js'
import { createServer } from "http";
import { Server } from "socket.io";
import { client } from "@gradio/client";
import { createRequire } from 'node:module';
import fs from 'fs';
import path from 'path';
const require = createRequire(import.meta.url);
global.EventSource = require('eventsource');
// Initialize the Express app and HTTP server
const app = express();
const httpServer = createServer(app);
// Serve static files from 'public' directory
app.use(express.static('public'));
// Initialize Socket.IO for real-time web socket communication
const io = new Server(httpServer, {});
// Directory for saving inference files
const outputDir = 'inference_outputs';
if (!fs.existsSync(outputDir)){
fs.mkdirSync(outputDir);
}
// Handle new socket connection
io.on("connection", (socket) => {
console.log("πŸ”Œ New socket connection");
// Listen for 'ask_api' events from the client
socket.on("ask_api", (client_data) => {
console.log("πŸ“Έ Received data from client");
asyncAPICall(client_data, socket);
});
});
// Example function to test server communication with a Gradio API
async function test_servers(){
try{
const grapi_test = await client("https://gradio-hello-world.hf.space");
const apitest_result = await grapi_test.predict("/predict", ["John"]);
console.log(apitest_result);
}
catch(e){
console.log("❌ Error testing servers:", e);
}
}
// Function to call the Gradio API asynchronously
async function asyncAPICall(data, socket) {
const grapi = await client("fffiloni/mndrm-call");
try{
// Perform the API call with the provided image blob and question
const api_result = await grapi.predict("/infer", [data[0], data[1]]);
console.log("βœ… API Result:", api_result);
// Emit the API response back to the client
socket.emit("api_response", api_result.data);
// Save the inference input and output
saveInference(data, api_result.data);
}
catch(e){
console.log("❌ API Call Error:", e);
socket.emit("api_error", "ERROR ON API SIDE, SORRY...");
}
}
// Save the inference input (image and question) and output (API response) to files
function saveInference(data, apiResponse) {
const timestamp = new Date().toISOString().replace(/[:.]/g, '-');
const basePath = path.join(outputDir, timestamp);
// Save image
const imageData = data[0].split(',')[1]; // Assuming data[0] is a base64 image string
fs.writeFileSync(`${basePath}_image.png`, imageData, 'base64');
// Save question and API response in a text file
const textContent = `Question: ${data[1]}\nAPI Response: ${apiResponse}`;
fs.writeFileSync(`${basePath}_info.txt`, textContent);
console.log("πŸ“ Inference data saved:", basePath);
}
// Start the HTTP server
httpServer.listen(7860, () => console.log("πŸš€ App running on localhost:7860"));