import type {
  DatasetCreateResponse,
  DetectionModelCapability,
  DetectionQaResult,
  DetectionRead,
  DetectionRunRead,
  DetectionRunResponse,
} from '../../types'

interface DetectionLabProps {
  detectionModels: DetectionModelCapability[]
  loadingDetectionModels: boolean
  detectionModelError: string | null
  selectedDetectionDatasetId: string
  selectedDetectionModelId: string
  detectionTileManifestPath: string
  detectionConfidenceThreshold: number
  runningDetection: boolean
  detectionRunResult: DetectionRunResponse | null
  detectionRunError: string | null
  detectionRuns: DetectionRunRead[]
  selectedDetectionRunId: string
  detectionItems: DetectionRead[]
  detectionClassFilter: string
  detectionMinConfidenceFilter: number
  loadingDetectionResults: boolean
  detectionReferenceDatasetId: string
  detectionQaResult: DetectionQaResult | null
  detectionQaError: string | null
  runningDetectionQa: boolean
  selectedProjectId: string | null
  rasterDatasets: DatasetCreateResponse[]
  referenceDatasets: DatasetCreateResponse[]
  onLoadModels: () => void
  onSelectDataset: (datasetId: string) => void
  onSelectModel: (modelId: string) => void
  onSetConfidenceThreshold: (value: number) => void
  onSetTileManifestPath: (value: string) => void
  onRunDetection: () => void
  onLoadRuns: () => void
  onSelectRun: (runId: string) => void
  onSetClassFilter: (value: string) => void
  onSetMinConfidenceFilter: (value: number) => void
  onLoadResults: () => void
  onSelectReferenceDataset: (datasetId: string) => void
  onRunQa: () => void
}

export function DetectionLab({
  detectionModels,
  loadingDetectionModels,
  detectionModelError,
  selectedDetectionDatasetId,
  selectedDetectionModelId,
  detectionTileManifestPath,
  detectionConfidenceThreshold,
  runningDetection,
  detectionRunResult,
  detectionRunError,
  detectionRuns,
  selectedDetectionRunId,
  detectionItems,
  detectionClassFilter,
  detectionMinConfidenceFilter,
  loadingDetectionResults,
  detectionReferenceDatasetId,
  detectionQaResult,
  detectionQaError,
  runningDetectionQa,
  selectedProjectId,
  rasterDatasets,
  referenceDatasets,
  onLoadModels,
  onSelectDataset,
  onSelectModel,
  onSetConfidenceThreshold,
  onSetTileManifestPath,
  onRunDetection,
  onLoadRuns,
  onSelectRun,
  onSetClassFilter,
  onSetMinConfidenceFilter,
  onLoadResults,
  onSelectReferenceDataset,
  onRunQa,
}: DetectionLabProps): JSX.Element {
  return (
    <section className="workspace-panel ai-lab-shell detection-lab-shell">
      <div className="panel-title-row">
        <div>
          <p className="eyebrow">Object detection</p>
          <h2>Detection Lab</h2>
        </div>
        <button className="secondary-action" type="button" onClick={onLoadModels} disabled={loadingDetectionModels}>
          Refresh models
        </button>
      </div>

      <div className="ai-lab-model-surface" aria-label="Detection model capabilities">
        <div className="ai-lab-section-header">
          <div>
            <h3>Model registry</h3>
            <p>Backend-reported detector states and limitations.</p>
          </div>
        </div>
        <div className="ai-lab-state-stack">
          {loadingDetectionModels ? (
            <div className="result-state result-state-loading">
              <strong>Loading detection models.</strong>
              <p>Checking backend model registry availability.</p>
            </div>
          ) : null}
          {detectionModelError ? (
            <div className="result-state result-state-error">
              <strong>Detection model registry unavailable.</strong>
              <p>{detectionModelError}</p>
            </div>
          ) : null}
          {detectionModels.length === 0 && !loadingDetectionModels ? (
            <div className="result-state result-state-empty">
              <strong>No detection models reported by backend.</strong>
              <p>Refresh models after the backend is reachable.</p>
            </div>
          ) : null}
        </div>
        <ul className="model-list">
          {detectionModels.map((model) => (
            <li className={model.configured ? 'model-card model-card-ready' : 'model-card'} key={model.model_id}>
              <strong>{model.display_name}</strong>
              <span className={model.configured ? 'status-badge status-badge-ready' : 'status-badge'}>{model.status}</span>
              <div className="entity-meta">
                <span>{model.model_id}</span>
                <span>{model.framework}</span>
                <span>{model.task_type}</span>
              </div>
              <p className="muted">classes: {model.supported_classes.join(', ')}</p>
              <p className="muted">{model.limitation_message}</p>
            </li>
          ))}
        </ul>
      </div>

      <div className="lab-block">
        <div className="ai-lab-run-surface" aria-label="Detection run controls">
          <h3>Run detection</h3>
          {rasterDatasets.length === 0 ? (
            <div className="result-state result-state-empty">
              <strong>No raster datasets available for detection.</strong>
              <p>Upload or select a raster dataset in Data before running object detection.</p>
            </div>
          ) : null}
          <div className="lab-form-grid">
            <label>
              Raster dataset
              <select value={selectedDetectionDatasetId} onChange={(event) => onSelectDataset(event.target.value)}>
                <option value="">Select raster dataset</option>
                {rasterDatasets.map((dataset) => (
                  <option key={dataset.id} value={dataset.id}>
                    {dataset.name}
                  </option>
                ))}
              </select>
            </label>
            <label>
              Model
              <select value={selectedDetectionModelId} onChange={(event) => onSelectModel(event.target.value)}>
                {detectionModels.map((model) => (
                  <option key={model.model_id} value={model.model_id}>
                    {model.display_name}
                  </option>
                ))}
              </select>
            </label>
            <label>
              Min confidence
              <input
                type="number"
                min="0"
                max="1"
                step="0.05"
                value={detectionConfidenceThreshold}
                onChange={(event) => onSetConfidenceThreshold(Number(event.target.value))}
              />
            </label>
          </div>
          {selectedDetectionModelId === 'yolo-configured' ? (
            <label>
              Tile manifest
              <input
                type="text"
                placeholder="Raster tile manifest path"
                value={detectionTileManifestPath}
                onChange={(event) => onSetTileManifestPath(event.target.value)}
              />
            </label>
          ) : null}
          <button className="primary-action" type="button" onClick={onRunDetection} disabled={runningDetection || !selectedProjectId || rasterDatasets.length === 0}>
            Run detection
          </button>
        </div>
      </div>

      <div className="ai-lab-state-stack">
        {detectionRunError ? (
          <div className="result-state result-state-error">
            <strong>Detection run failed.</strong>
            <p>{detectionRunError}</p>
          </div>
        ) : null}
        {detectionRunResult ? (
          <div className="result-summary-card">
            <p>Status: {detectionRunResult.status}</p>
            <p>Message: {detectionRunResult.message}</p>
            <p>Analysis run: {detectionRunResult.analysis_run_id}</p>
            <p>Job: {detectionRunResult.job_id}</p>
            <p>Detections: {detectionRunResult.detection_count}</p>
            {detectionRunResult.error_code ? <p className="error">Code: {detectionRunResult.error_code}</p> : null}
          </div>
        ) : null}
      </div>

      <div className="ai-lab-results-surface" aria-label="Detection results">
        <div className="panel-title-row">
          <div>
            <h3>Detection results</h3>
            <p className="muted">Load persisted detections and filter by class or confidence.</p>
          </div>
          <button className="secondary-action" type="button" onClick={onLoadRuns} disabled={!selectedProjectId}>
            Refresh runs
          </button>
        </div>
        <div className="lab-form-grid">
          <label>
            Run
            <select value={selectedDetectionRunId} onChange={(event) => onSelectRun(event.target.value)}>
              <option value="">Select detection run</option>
              {detectionRuns.map((run) => (
                <option key={run.id} value={run.id}>
                  {run.model_name || 'detection'} - {run.status} - {run.id}
                </option>
              ))}
            </select>
          </label>
          <label>
            Class
            <input
              type="text"
              placeholder="Class filter"
              value={detectionClassFilter}
              onChange={(event) => onSetClassFilter(event.target.value)}
            />
          </label>
          <label>
            Min confidence
            <input
              type="number"
              min="0"
              max="1"
              step="0.05"
              value={detectionMinConfidenceFilter}
              onChange={(event) => onSetMinConfidenceFilter(Number(event.target.value))}
            />
          </label>
        </div>
        <button className="primary-action" type="button" onClick={onLoadResults} disabled={!selectedDetectionRunId || loadingDetectionResults}>
          Load detections
        </button>
        {loadingDetectionResults ? (
          <div className="result-state result-state-loading">
            <strong>Loading detection results.</strong>
            <p>Retrieving persisted detections for the selected run.</p>
          </div>
        ) : null}
        <div className="ai-lab-state-stack">
          <div className="result-state result-state-ready">
            <strong>Detections loaded: {detectionItems.length}</strong>
            <p>{selectedDetectionRunId ? 'Loaded from persisted detection records.' : 'Select a detection run before loading results.'}</p>
          </div>
        </div>
        {detectionItems.length > 0 ? (
          <div className="table-scroll">
            <table>
              <thead>
                <tr>
                  <th>Class</th>
                  <th>Confidence</th>
                  <th>Model</th>
                  <th>Source tile</th>
                </tr>
              </thead>
              <tbody>
                {detectionItems.map((detection) => (
                  <tr key={detection.id}>
                    <td>{detection.class_name}</td>
                    <td>{detection.confidence.toFixed(2)}</td>
                    <td>{detection.model_name}</td>
                    <td>{detection.source_tile_path || 'n/a'}</td>
                  </tr>
                ))}
              </tbody>
            </table>
          </div>
        ) : null}
      </div>

      <div className="ai-lab-qa-surface" aria-label="Detection QA controls and results">
        <h3>Detection QA</h3>
        <label>
          Reference dataset
          <select value={detectionReferenceDatasetId} onChange={(event) => onSelectReferenceDataset(event.target.value)}>
            <option value="">Select reference dataset</option>
            {referenceDatasets.map((dataset) => (
              <option key={dataset.id} value={dataset.id}>
                {dataset.name}
              </option>
            ))}
          </select>
        </label>
        <button className="primary-action" type="button" onClick={onRunQa} disabled={runningDetectionQa || !selectedDetectionRunId || !detectionReferenceDatasetId}>
          Compare detections to reference
        </button>
        {detectionQaError ? (
          <div className="result-state result-state-error">
            <strong>Detection QA failed.</strong>
          <p>{detectionQaError}</p>
        </div>
      ) : null}
      {detectionQaResult ? (
          <div className="result-summary-card">
            <p>Status: {detectionQaResult.status}</p>
            <p>Quality check: {detectionQaResult.quality_check_id}</p>
            <p>Precision: {detectionQaResult.precision?.toFixed(3) ?? 'n/a'}</p>
            <p>Recall: {detectionQaResult.recall?.toFixed(3) ?? 'n/a'}</p>
            <p>F1: {detectionQaResult.f1_score?.toFixed(3) ?? 'n/a'}</p>
            <p>Mean IoU: {detectionQaResult.mean_iou?.toFixed(3) ?? 'n/a'}</p>
            <p>False positives: {detectionQaResult.false_positives}</p>
            <p>False negatives: {detectionQaResult.false_negatives}</p>
          </div>
        ) : null}
      </div>
    </section>
  )
}