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Rajdeep Singh
Rajdeep Singh

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Steps Included To Develop Spicychat.ai Platform Cloning

#clone #ai

Creating a conversational AI platform like Spicychat.Ai includes greater than only a chatbot UI - it blends devices gaining knowledge of, real-time messaging, scalability, and ethical compliance. In this novice-friendly guide, I’ll walk you via the precise method I accompanied to build a spicychat ai clone, starting from planning and tech stack selection to development and testing.

Choosed Tech Stack

Frontend: React.js + Tailwind CSS
Backend: Node.js with Express
Real-time Chat: Socket.io
AI Model: OpenAI GPT-4 (you can fine-tune or use prompt engineering)
Database: MongoDB (for users, chats, media)
Auth: Firebase or JWT
Media Storage: AWS S3
Deployment: Vercel (frontend), Render or Heroku (backend)

2.Setting Up the Project Structure

mkdir spicychat-ai-clone
cd spicychat-ai-clone
npx create-react-app frontend
mkdir backend
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_Backend folder included:
_

/routes – Auth, chats, users

/controllers – Logic for user auth, chat responses

/models – MongoDB models for User, Message

/utils – Middleware (e.g., token validation)
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3. Integrating OpenAI for Chatbot Responses

I used OpenAI’s API to simulate spicy conversations (with NSFW filters for safety).

// backend/controllers/aiController.js
const axios = require('axios');

exports.getAIResponse = async (req, res) => {
  const prompt = req.body.prompt;
  const apiKey = process.env.OPENAI_API_KEY;

  try {
    const response = await axios.post("https://api.openai.com/v1/chat/completions", {
      model: "gpt-4",
      messages: [{ role: "user", content: prompt }],
      temperature: 0.9,
    }, {
      headers: {
        Authorization: `Bearer ${apiKey}`
      }
    });

    res.json({ reply: response.data.choices[0].message.content });
  } catch (err) {
    res.status(500).send("AI Error");
  }
};
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This code powers the conversational core of the spicychat ai clone.

4. Real-time Chat with Socket.io
Enable users to chat live:

// backend/socket.js
const socketIO = require('socket.io');

function setupSocket(server) {
  const io = socketIO(server, {
    cors: {
      origin: "*"
    }
  });

  io.on("connection", socket => {
    socket.on("joinRoom", room => {
      socket.join(room);
    });

    socket.on("sendMessage", ({ room, message }) => {
      io.to(room).emit("receiveMessage", message);
    });
  });
}

module.exports = setupSocket;
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_On the frontend:
_


const socket = io("http://localhost:5000");
socket.emit("joinRoom", roomId);
socket.emit("sendMessage", { room: roomId, message });
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5. Media Sharing with AWS S3

I used the aws-sdk to allow media uploads:

// backend/utils/s3Upload.js
const AWS = require('aws-sdk');
const s3 = new AWS.S3({ /* credentials */ });

exports.uploadToS3 = async (file) => {
  const params = {
    Bucket: 'spicychat-media',
    Key: Date.now() + file.originalname,
    Body: file.buffer,
    ACL: 'public-read',
  };

  return await s3.upload(params).promise();
};
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This adds media support to the spicychat ai clone.

6. Basic Authentication (JWT)

const jwt = require("jsonwebtoken");

exports.authenticate = (req, res, next) => {
  const token = req.headers.authorization?.split(" ")[1];
  if (!token) return res.sendStatus(401);

  jwt.verify(token, process.env.JWT_SECRET, (err, user) => {
    if (err) return res.sendStatus(403);
    req.user = user;
    next();
  });
};
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JWT-based auth was sufficient for early-stage testing of the spicychat ai clone.

7. UI: React with Tailwind
For the frontend, I used:
Chat bubbles with timestamps
Input area with emoji/GIF support
Side panel for room selection, user profiles

<button onClick={handleSend} className="bg-pink-500 text-white px-4 py-2 rounded">Send</button>
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8. Testing and Deployment
Local testing with Postman and WebSocket test tools
Frontend deployed to Vercel, backend to Render
Used MongoDB Atlas for cloud DB

Finally - Understanding the Core of a Spicychat.ai Clone Development
Before jumping into code, I outlined what makes Spicychat unique:
Real-time private and public chats
AI-powered conversations (mature AI content filters)
Image/video sharing with moderation
Tiered user access (free, premium)
Anonymous chatting option
This clarity helped me define the architecture and break the platform down into manageable components for the spicychat ai clone.

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