'use client'

import type { TrOCRStatus, TrainingExample, MagicSettings } from './types'

interface TrainingTabProps {
  status: TrOCRStatus | null
  examples: TrainingExample[]
  trainingImage: File | null
  setTrainingImage: (file: File | null) => void
  trainingText: string
  setTrainingText: (text: string) => void
  fineTuning: boolean
  settings: MagicSettings
  handleAddTrainingExample: () => void
  handleFineTune: () => void
}

export default function TrainingTab({
  status,
  examples,
  trainingImage,
  setTrainingImage,
  trainingText,
  setTrainingText,
  fineTuning,
  settings,
  handleAddTrainingExample,
  handleFineTune,
}: TrainingTabProps) {
  const examplesCount = status?.training_examples_count || 0

  return (
    <div className="space-y-6">
      {/* Training Overview */}
      <div className="bg-gray-800/50 border border-gray-700 rounded-xl p-6">
        <h2 className="text-lg font-semibold text-white mb-4">Training mit LoRA</h2>
        <p className="text-sm text-gray-400 mb-4">
          LoRA (Low-Rank Adaptation) ermöglicht effizientes Fine-Tuning ohne das Basismodell zu verändern.
          Das Training erfolgt lokal auf Ihrem System.
        </p>

        <div className="grid grid-cols-2 md:grid-cols-4 gap-4 mb-6">
          <div className="bg-gray-900/50 rounded-lg p-4 text-center">
            <div className="text-3xl font-bold text-white">{examplesCount}</div>
            <div className="text-xs text-gray-400">Trainingsbeispiele</div>
          </div>
          <div className="bg-gray-900/50 rounded-lg p-4 text-center">
            <div className="text-3xl font-bold text-white">10</div>
            <div className="text-xs text-gray-400">Minimum benötigt</div>
          </div>
          <div className="bg-gray-900/50 rounded-lg p-4 text-center">
            <div className="text-3xl font-bold text-white">{settings.loraRank}</div>
            <div className="text-xs text-gray-400">LoRA Rank</div>
          </div>
          <div className="bg-gray-900/50 rounded-lg p-4 text-center">
            <div className="text-3xl font-bold text-white">{status?.has_lora_adapter ? '✓' : '✗'}</div>
            <div className="text-xs text-gray-400">Adapter aktiv</div>
          </div>
        </div>

        {/* Progress Bar */}
        <div className="mb-6">
          <div className="flex justify-between text-sm mb-1">
            <span className="text-gray-400">Fortschritt zum Fine-Tuning</span>
            <span className="text-gray-400">{Math.min(100, (examplesCount / 10) * 100).toFixed(0)}%</span>
          </div>
          <div className="h-2 bg-gray-700 rounded-full overflow-hidden">
            <div
              className="h-full bg-gradient-to-r from-purple-500 to-blue-500 transition-all duration-500"
              style={{ width: `${Math.min(100, (examplesCount / 10) * 100)}%` }}
            />
          </div>
        </div>
      </div>

      <div className="grid grid-cols-1 md:grid-cols-2 gap-6">
        {/* Add Training Example */}
        <div className="bg-gray-800/50 border border-gray-700 rounded-xl p-6">
          <h2 className="text-lg font-semibold text-white mb-4">Trainingsbeispiel hinzufügen</h2>
          <p className="text-sm text-gray-400 mb-4">
            Lade ein Bild mit handgeschriebenem Text hoch und gib die korrekte Transkription ein.
          </p>

          <div className="space-y-4">
            <div>
              <label className="block text-sm text-gray-300 mb-1">Bild</label>
              <input
                type="file"
                accept="image/*"
                className="w-full bg-gray-900 border border-gray-700 rounded-lg px-3 py-2 text-sm"
                onChange={(e) => setTrainingImage(e.target.files?.[0] || null)}
              />
            </div>
            <div>
              <label className="block text-sm text-gray-300 mb-1">Korrekter Text (Ground Truth)</label>
              <textarea
                className="w-full bg-gray-900 border border-gray-700 rounded-lg px-3 py-2 text-sm text-white resize-none"
                rows={3}
                placeholder="Gib hier den korrekten Text ein..."
                value={trainingText}
                onChange={(e) => setTrainingText(e.target.value)}
              />
            </div>
            <button
              onClick={handleAddTrainingExample}
              className="w-full px-4 py-2 bg-purple-600 hover:bg-purple-700 rounded-lg text-sm font-medium transition-colors"
            >
              + Trainingsbeispiel hinzufügen
            </button>
          </div>
        </div>

        {/* Fine-Tuning */}
        <div className="bg-gray-800/50 border border-gray-700 rounded-xl p-6">
          <h2 className="text-lg font-semibold text-white mb-4">Fine-Tuning starten</h2>
          <p className="text-sm text-gray-400 mb-4">
            Trainiere das Modell mit den gesammelten Beispielen. Der Prozess dauert
            je nach Anzahl der Beispiele einige Minuten.
          </p>

          <div className="bg-gray-900/50 rounded-lg p-4 mb-4">
            <div className="grid grid-cols-2 gap-4 text-sm">
              <div>
                <span className="text-gray-400">Epochen:</span>
                <span className="text-white ml-2">{settings.epochs}</span>
              </div>
              <div>
                <span className="text-gray-400">Learning Rate:</span>
                <span className="text-white ml-2">{settings.learningRate}</span>
              </div>
              <div>
                <span className="text-gray-400">LoRA Rank:</span>
                <span className="text-white ml-2">{settings.loraRank}</span>
              </div>
              <div>
                <span className="text-gray-400">Batch Size:</span>
                <span className="text-white ml-2">{settings.batchSize}</span>
              </div>
            </div>
          </div>

          <button
            onClick={handleFineTune}
            disabled={fineTuning || examplesCount < 10}
            className="w-full px-4 py-2 bg-green-600 hover:bg-green-700 disabled:bg-gray-700 disabled:cursor-not-allowed rounded-lg text-sm font-medium transition-colors"
          >
            {fineTuning ? (
              <span className="flex items-center justify-center gap-2">
                <div className="animate-spin rounded-full h-4 w-4 border-b-2 border-white"></div>
                Fine-Tuning läuft...
              </span>
            ) : (
              'Fine-Tuning starten'
            )}
          </button>

          {examplesCount < 10 && (
            <p className="text-xs text-yellow-400 mt-2 text-center">
              Noch {10 - examplesCount} Beispiele benötigt
            </p>
          )}
        </div>
      </div>

      {/* Training Examples List */}
      {examples.length > 0 && (
        <div className="bg-gray-800/50 border border-gray-700 rounded-xl p-6">
          <h2 className="text-lg font-semibold text-white mb-4">Trainingsbeispiele ({examples.length})</h2>
          <div className="space-y-2 max-h-64 overflow-y-auto">
            {examples.map((ex, i) => (
              <div key={i} className="flex items-center gap-4 bg-gray-900/50 rounded-lg p-3">
                <span className="text-gray-500 font-mono text-sm w-8">{i + 1}.</span>
                <span className="text-white text-sm flex-1 truncate">{ex.ground_truth}</span>
                <span className="text-gray-500 text-xs">{new Date(ex.created_at).toLocaleDateString('de-DE')}</span>
              </div>
            ))}
          </div>
        </div>
      )}
    </div>
  )
}