Synthetic Data Revolution: Training Superior AI Models with Generated Data

package com.devmetrix.synthetic;

import org.springframework.ai.chat.ChatClient;
import org.springframework.stereotype.Service;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.CompletableFuture;

@Service
public class DataFactoryService {

    private final ChatClient teacherModel;
    private final ValidatorService validator;
    private final DatasetRepository repository;

    public DataFactoryService(ChatClient teacherModel, ValidatorService validator, DatasetRepository repository) {
        this.teacherModel = teacherModel;
        this.validator = validator;
        this.repository = repository;
    }

    /**
     * Generates N synthetic examples for a specific domain.
     * Uses parallel execution for speed.
     */
    public void generateDataset(String domain, int count) {
        List<CompletableFuture<Void>> futures = new ArrayList<>();

        for (int i = 0; i < count; i++) {
            futures.add(CompletableFuture.runAsync(() -> {
                generateAndPersist(domain);
            }));
        }

        CompletableFuture.allOf(futures.toArray(new CompletableFuture[0])).join();
    }

    private void generateAndPersist(String domain) {
        // 1. Generate Instruction
        String instructionPrompt = String.format(
            "Generate a complex, unique instruction related to %s. Do not answer it yet.", domain
        );
        String instruction = teacherModel.call(instructionPrompt).getResult().getOutput().getContent();

        // 2. Generate Chain-of-Thought Response
        String responsePrompt = String.format(
            "You are an expert. Answer the following instruction using Step-by-Step reasoning.\nInstruction: %s", instruction
        );
        String response = teacherModel.call(responsePrompt).getResult().getOutput().getContent();

        // 3. Quality Filter (Rejection Sampling)
        if (validator.evaluateQuality(instruction, response) > 0.8) {
            SyntheticExample example = new SyntheticExample(domain, instruction, response);
            repository.save(example);
        } else {
            System.out.println("Discarding low-quality generation.");
        }
    }
}

// Validator Service using a Judge Model approach
@Service
class ValidatorService {
    private final ChatClient judgeModel;

    public double evaluateQuality(String instruction, String response) {
        String prompt = String.format(
            "Rate the following Q&A pair on a scale of 0.0 to 1.0 for correctness and clarity.\nQ: %s\nA: %s\nReturn only the number.",
            instruction, response
        );
        String scoreStr = judgeModel.call(prompt).getResult().getOutput().getContent();
        return Double.parseDouble(scoreStr.trim());
    }
}

'use client';

import { useState } from 'react';
import { motion, AnimatePresence } from 'framer-motion';
import { Check, X, RefreshCw } from 'lucide-react';

// Mock Data
const initialData = [
  { id: 1, instruction: "Explain quantum entanglement.", response: "Quantum entanglement is..." },
  // ...
];

export default function ReviewDashboard() {
  const [queue, setQueue] = useState(initialData);
  const [current, setCurrent] = useState(queue[0]);

  const handleDecision = (approved: boolean) => {
    // API call to save/discard would go here
    const nextQueue = queue.slice(1);
    setQueue(nextQueue);
    setCurrent(nextQueue[0]);
  };

  if (!current) return <div className="text-center p-20 text-white">Queue Empty! Great job.</div>;

  return (
    <div className="max-w-2xl mx-auto mt-10">
      <div className="bg-gray-900 rounded-2xl p-8 border border-gray-700 shadow-2xl relative overflow-hidden">
        <div className="absolute top-0 left-0 w-full h-1 bg-gradient-to-r from-purple-500 to-pink-500" />

        <h3 className="text-gray-400 text-sm font-bold uppercase tracking-wider mb-2">Instruction</h3>
        <p className="text-xl text-white font-medium mb-6">{current.instruction}</p>

        <h3 className="text-gray-400 text-sm font-bold uppercase tracking-wider mb-2">Generated Response</h3>
        <div className="bg-gray-800 p-4 rounded-lg text-gray-300 text-sm leading-relaxed mb-8 max-h-60 overflow-y-auto">
          {current.response}
        </div>

        <div className="flex justify-between gap-4">
          <motion.button
            whileHover={{ scale: 1.05 }}
            whileTap={{ scale: 0.95 }}
            onClick={() => handleDecision(false)}
            className="flex-1 flex items-center justify-center gap-2 py-3 rounded-xl bg-red-500/20 text-red-400 hover:bg-red-500/30 transition-colors font-bold"
          >
            <X size={20} /> Reject
          </motion.button>

          <motion.button
            whileHover={{ scale: 1.05 }}
            whileTap={{ scale: 0.95 }}
            onClick={() => handleDecision(true)}
            className="flex-1 flex items-center justify-center gap-2 py-3 rounded-xl bg-green-500/20 text-green-400 hover:bg-green-500/30 transition-colors font-bold"
          >
            <Check size={20} /> Approve
          </motion.button>
        </div>
      </div>

      <p className="text-center text-gray-500 mt-4 text-sm">
        {queue.length} items remaining in queue
      </p>
    </div>
  );
}