import React, { useState, useEffect } from 'react';

const BenchmarkChart = () => {
  // Real data from your ASR calculations - sorted by highest achievable ASR
  const benchmarkData = [
    {
      model: "Grok 4",
      baseline: 68.67,
      methods: {
        keyword_objective_combined: 85.15
      }
    },
    {
      model: "Deepseek R1-0528",
      baseline: 68.67,
      methods: {
        keyword_objective_combined: 83.76
      }
    },
    {
      model: "Llama 3.1 405B",
      baseline: 67.00,
      methods: {
        keyword_objective_combined: 80.75
      }
    },
    {
      model: "Gemini 2.5 Pro",
      baseline: 55.67,
      methods: {
        keyword_objective_combined: 74.14,
        root_problem: 67.19
      }
    },
    {
      model: "Llama 3 8B Instruct Reference",
      baseline: 58.33,
      methods: {
        keyword_objective_combined: 68.86
      }
    },
    {
      model: "Mixtral 8x22B",
      baseline: 48.00,
      methods: {
        keyword_objective_combined: 66.82
      }
    },
    {
      model: "Llama 4 Maverick Instruct",
      baseline: 45.00,
      methods: {
        keyword_objective_combined: 56.46
      }
    },
    {
      model: "GPT o3",
      baseline: 22.00,
      methods: {
        keyword_objective_combined: 30.53
      }
    },
    {
      model: "Claude 4 Sonnet",
      baseline: 26.33,
      methods: {
        keyword_objective_combined: 28.64
      }
    },
    {
      model: "Claude Opus 4.1", 
      baseline: 20.67,
      methods: {
        keyword_objective_combined: 23.56
      }
    },
    {
      model: "GPT 5",
      baseline: 8.33,
      methods: {
        keyword_objective_combined: 11.68,
        root_problem: 12.46
      }
    },
    {
      model: "GPT 5 mini",
      baseline: 7.67,
      methods: {
        keyword_objective_combined: 11.28,
        root_problem: 10.44
      }
    }
  ];

  const [currentPhase, setCurrentPhase] = useState('baseline');
  const [currentMethodIndex, setCurrentMethodIndex] = useState(0);
  
  const synthesisMethodsOrder = ['keyword_objective_combined', 'root_problem'];
  
  const phases = [
    { key: 'baseline', label: 'Human Baseline ASR' },
    { key: 'additive_synthesis', label: 'Human + Transformation Methods ASR' }
  ];

  useEffect(() => {
    const interval = setInterval(() => {
      setCurrentPhase(prev => prev === 'baseline' ? 'additive_synthesis' : 'baseline');
      setCurrentMethodIndex(0);
    }, 8000);

    return () => clearInterval(interval);
  }, []);

  useEffect(() => {
    if (currentPhase === 'additive_synthesis') {
      const methodInterval = setInterval(() => {
        setCurrentMethodIndex(prev => {
          const nextIndex = prev + 1;
          if (nextIndex > synthesisMethodsOrder.length) {
            return synthesisMethodsOrder.length;
          }
          return nextIndex;
        });
      }, 2000);
      return () => clearInterval(methodInterval);
    }
  }, [currentPhase]);

  const getCurrentValue = (modelData, phase) => {
    if (phase === 'baseline') {
      return modelData.baseline;
    } else if (phase === 'additive_synthesis') {
      // Show the highest ASR achieved by any transformation method tried so far
      let maxASR = modelData.baseline;
      
      for (let i = 0; i < currentMethodIndex; i++) {
        const method = synthesisMethodsOrder[i];
        if (modelData.methods[method] !== undefined) {
          maxASR = Math.max(maxASR, modelData.methods[method]);
        }
      }
      
      return maxASR;
    }
    return 0;
  };

  const getCurrentMethod = (modelData, phase) => {
    if (phase === 'baseline') return 'Human Baseline';
    if (currentMethodIndex === 0) return 'Human Baseline';
    
    const availableMethods = [];
    for (let i = 0; i < currentMethodIndex; i++) {
      const method = synthesisMethodsOrder[i];
      if (modelData.methods[method] !== undefined) {
        availableMethods.push(method);
      }
    }
    
    if (availableMethods.length === 0) return 'Human Baseline';
    
    const lastMethod = availableMethods[availableMethods.length - 1];
    if (lastMethod === 'keyword_objective_combined') return 'Keyword/Objective Transformation';
    if (lastMethod === 'root_problem') return 'Root Problem Transformation';
    
    return lastMethod.replace(/_/g, ' ').replace(/\b\w/g, l => l.toUpperCase());
  };

  const getBarColor = (modelData, phase) => {
    if (phase === 'baseline') {
      return 'from-blue-500 to-blue-600';
    } else if (phase === 'additive_synthesis' && currentMethodIndex > 0) {
      return 'from-green-500 to-green-600';
    } else {
      return 'from-blue-500 to-blue-600';
    }
  };

  return (
    <div className="min-h-screen bg-gradient-to-br from-slate-900 to-slate-800 p-4">
      <div className="max-w-6xl mx-auto">
        {/* Header */}
        <div className="text-center mb-6">
          <h1 className="text-3xl font-bold text-white mb-3">
            LLM Attack Success Rate with Transformation Methods
          </h1>
          <p className="text-slate-300">
            SafetyBench Aug 2025 - Real ASR Calculations
          </p>
          
          {/* Methodology Note */}
          <div className="mt-4 p-3 bg-yellow-900/30 border border-yellow-500/30 rounded-lg max-w-4xl mx-auto">
            <div className="flex items-start space-x-3">
              <div className="text-yellow-400 mt-1">⚠️</div>
              <div className="text-left">
                <p className="text-yellow-200 font-semibold mb-2">Methodology Note</p>
                <p className="text-yellow-100 text-sm leading-relaxed">
                  <strong>Additive Visualization:</strong> This chart shows cumulative impact by progressively adding each transformation method's individual attack success rate. 
                  Values >100% represent transformation of multiple conversations off one failed, human seed conversation. 
                  Results are based on HarmBench Grading methodology and should be interpreted as relative performance indicators.
                </p>
              </div>
            </div>
          </div>
        </div>

        {/* Chart Container - Scrollable Box */}
        <div className="bg-white rounded-xl shadow-2xl p-4">
          <div className="h-96 overflow-y-auto pr-2">
            <div className="space-y-2">
              {benchmarkData.map((modelData, index) => {
                const currentValue = getCurrentValue(modelData, currentPhase);
                const baselineValue = modelData.baseline;
                const maxValue = 90;
                const barWidth = (currentValue / maxValue) * 100;
                const currentMethod = getCurrentMethod(modelData, currentPhase);
                const gain = currentValue - baselineValue;
                
                return (
                  <div key={modelData.model} className="relative">
                    {/* Model Name and Value */}
                    <div className="flex items-center justify-between mb-1">
                      <div>
                        <h3 className="font-semibold text-gray-800 text-sm">
                          {modelData.model}
                        </h3>
                        <p className="text-xs text-gray-600">
                          {currentMethod}
                        </p>
                      </div>
                      <div className="text-right">
                        <span className="text-lg font-bold text-gray-700">
                          {currentValue.toFixed(1)}%
                        </span>
                        {gain > 0 && (
                          <div className="text-xs font-semibold text-green-600">
                            +{gain.toFixed(1)} points
                          </div>
                        )}
                      </div>
                    </div>
                    
                    {/* Progress Bar */}
                    <div className="relative h-6 bg-gray-200 rounded-full overflow-hidden">
                      <div 
                        className={`h-full bg-gradient-to-r ${getBarColor(modelData, currentPhase)} rounded-full transition-all duration-2000 ease-out flex items-center justify-end pr-2`}
                        style={{ width: `${Math.max(barWidth, 5)}%` }}
                      >
                        <div className="text-white font-semibold text-xs">
                          {currentValue > 8 ? `${currentValue.toFixed(1)}%` : ''}
                        </div>
                      </div>
                    </div>
                  </div>
                );
              })}
            </div>
          </div>
          
          {/* Legend */}
          <div className="mt-4 pt-4 border-t border-gray-200 flex justify-center space-x-6 text-sm">
            <div className="flex items-center space-x-2">
              <div className="w-3 h-3 bg-gradient-to-r from-blue-500 to-blue-600 rounded"></div>
              <span className="text-gray-700">Human Baseline</span>
            </div>
            <div className="flex items-center space-x-2">
              <div className="w-3 h-3 bg-gradient-to-r from-green-500 to-green-600 rounded"></div>
              <span className="text-gray-700">With Transformation Methods</span>
            </div>
          </div>
        </div>
        
        {/* Footer */}
        <div className="mt-4 text-center text-slate-400 space-y-1">
          <p className="text-sm">
            Top performers: Grok 4 (85.15%), Deepseek R1-0528 (83.76%), Llama 3.1 405B (80.75%)
          </p>
          <p className="text-xs">
            Shows highest ASR achieved when combining human attempts with transformation methods
          </p>
        </div>
      </div>
    </div>
  );
};

export default BenchmarkChart;