import 'dart:convert';
import 'dart:js_interop';
import 'dart:typed_data';

import 'package:flutter/material.dart';

// ─── JS interop bindings ───────────────────────────────────────────────────

@JS()
external JSPromise<JSBoolean> initFaceApi();

/// Runs liveness detection via a JS-managed fullscreen overlay.
/// No containerId needed — the JS code appends the overlay to document.body
/// directly, which avoids CanvasKit iframe cross-origin restrictions.
@JS()
external JSPromise<JSAny?> runWebLiveness(JSNumber requiredBlinks);

@JS()
external void cancelWebLiveness();

@JS()
external JSPromise<JSAny?> getFaceDescriptorFromDataUrl(JSString dataUrl);

@JS()
external JSPromise<JSAny?> getFaceDescriptorFromUrl(JSString url);

@JS()
external JSNumber compareFaceDescriptors(JSAny desc1, JSAny desc2);

// ─── JS result type ────────────────────────────────────────────────────────

extension type _LivenessJSResult(JSObject _) implements JSObject {
  external JSString get dataUrl;
  external JSNumber get blinkCount;
}

// ─── Public API ─────────────────────────────────────────────────────────────

/// Result from a face liveness check.
class FaceLivenessResult {
  final Uint8List imageBytes;
  final String? imagePath;
  FaceLivenessResult({required this.imageBytes, this.imagePath});
}

/// Run face liveness detection on web using face-api.js.
/// Shows a dialog with camera preview and blink detection.
Future<FaceLivenessResult?> runFaceLiveness(
  BuildContext context, {
  int requiredBlinks = 3,
}) async {
  return showDialog<FaceLivenessResult>(
    context: context,
    barrierDismissible: false,
    builder: (ctx) => _WebLivenessDialog(requiredBlinks: requiredBlinks),
  );
}

/// Compare a captured face photo with enrolled face photo bytes.
/// Uses face-api.js face descriptors on web.
/// Returns similarity score 0.0 (no match) to 1.0 (perfect match).
Future<double> compareFaces(
  Uint8List capturedBytes,
  Uint8List enrolledBytes,
) async {
  try {
    final capturedDataUrl =
        'data:image/jpeg;base64,${base64Encode(capturedBytes)}';
    final enrolledDataUrl =
        'data:image/jpeg;base64,${base64Encode(enrolledBytes)}';

    final desc1Result = await getFaceDescriptorFromDataUrl(
      capturedDataUrl.toJS,
    ).toDart;
    final desc2Result = await getFaceDescriptorFromDataUrl(
      enrolledDataUrl.toJS,
    ).toDart;

    if (desc1Result == null || desc2Result == null) return 0.0;

    final distance = compareFaceDescriptors(
      desc1Result,
      desc2Result,
    ).toDartDouble;

    // face-api.js distance: 0 = identical, ~0.6 = threshold, 1+ = very different
    // Convert to similarity score: 1.0 = perfect match, 0.0 = no match
    return (1.0 - distance).clamp(0.0, 1.0);
  } catch (_) {
    return 0.0;
  }
}

// ─── Web Liveness Dialog ────────────────────────────────────────────────────

class _WebLivenessDialog extends StatefulWidget {
  final int requiredBlinks;
  const _WebLivenessDialog({required this.requiredBlinks});

  @override
  State<_WebLivenessDialog> createState() => _WebLivenessDialogState();
}

enum _WebLivenessState { loading, error }

class _WebLivenessDialogState extends State<_WebLivenessDialog> {
  _WebLivenessState _state = _WebLivenessState.loading;
  String _statusText = 'Loading face detection models…';
  String? _errorText;
  bool _popped = false;

  @override
  void initState() {
    super.initState();
    WidgetsBinding.instance.addPostFrameCallback((_) => _initialize());
  }

  Future<void> _initialize() async {
    // initFaceApi() immediately returns true and starts background loading of
    // face-api.js (needed for compareFaces later).  MediaPipe is initialized
    // inside runWebLiveness() itself, with progress shown in the JS overlay.
    await initFaceApi().toDart;
    if (!mounted) return;
    _runLiveness();
  }

  Future<void> _runLiveness() async {
    try {
      // runWebLiveness opens its own fullscreen JS overlay so the camera video
      // element lives in the top-level document — not inside a CanvasKit iframe.
      final result = await runWebLiveness(widget.requiredBlinks.toJS).toDart;

      if (result == null) {
        if (mounted && !_popped) {
          _popped = true;
          Navigator.of(context).pop(null);
        }
        return;
      }

      final jsResult = result as _LivenessJSResult;
      final dataUrl = jsResult.dataUrl.toDart;
      final base64Data = dataUrl.split(',')[1];
      final bytes = base64Decode(base64Data);

      if (mounted && !_popped) {
        _popped = true;
        Navigator.of(
          context,
        ).pop(FaceLivenessResult(imageBytes: Uint8List.fromList(bytes)));
      }
    } catch (e) {
      _setError('Liveness detection failed: $e');
    }
  }

  void _setError(String message) {
    if (!mounted) return;
    setState(() {
      _state = _WebLivenessState.error;
      _errorText = message;
    });
  }

  void _cancel() {
    if (_popped) return;
    _popped = true;
    cancelWebLiveness();
    Navigator.of(context).pop(null);
  }

  void _retry() {
    setState(() {
      _state = _WebLivenessState.loading;
      _statusText = 'Loading face detection models…';
      _errorText = null;
    });
    _initialize();
  }

  @override
  void dispose() {
    cancelWebLiveness();
    super.dispose();
  }

  @override
  Widget build(BuildContext context) {
    final theme = Theme.of(context);
    final colors = theme.colorScheme;

    Widget content;
    if (_state == _WebLivenessState.error) {
      content = Column(
        mainAxisSize: MainAxisSize.min,
        children: [
          Icon(Icons.error_outline, color: colors.error, size: 40),
          const SizedBox(height: 12),
          Text(
            _errorText ?? 'An error occurred.',
            style: theme.textTheme.bodyMedium?.copyWith(color: colors.error),
            textAlign: TextAlign.center,
          ),
        ],
      );
    } else {
      content = Column(
        mainAxisSize: MainAxisSize.min,
        children: [
          const SizedBox(
            width: 28,
            height: 28,
            child: CircularProgressIndicator(strokeWidth: 2.5),
          ),
          const SizedBox(height: 14),
          Text(
            _statusText,
            style: theme.textTheme.bodyMedium,
            textAlign: TextAlign.center,
          ),
        ],
      );
    }

    return AlertDialog(
      shape: RoundedRectangleBorder(borderRadius: BorderRadius.circular(28)),
      title: Row(
        children: [
          Icon(Icons.face, color: colors.primary),
          const SizedBox(width: 12),
          const Expanded(child: Text('Face Verification')),
        ],
      ),
      content: Padding(
        padding: const EdgeInsets.symmetric(vertical: 8),
        child: content,
      ),
      actions: [
        if (_state == _WebLivenessState.error) ...[
          TextButton(onPressed: _cancel, child: const Text('Cancel')),
          FilledButton(onPressed: _retry, child: const Text('Retry')),
        ] else
          TextButton(onPressed: _cancel, child: const Text('Cancel')),
      ],
    );
  }
}