{"repo": "chaiqueeee/mathmate", "files": {"lib/services/deepseek_service.dart": {"cd430dbed71b344a768a697fd5da313464a413f6": {"t": 1785745912.7021139, "n": 3615, "h": "a009ee3366c9a8b5", "c": "import 'dart:convert';\n\nimport 'package:flutter_dotenv/flutter_dotenv.dart';\nimport 'package:http/http.dart' as http;\nimport 'package:mathmate/services/app_logger.dart';\n\nclass DeepSeekService {\n  static const String _apiKeyEnv = 'DEEPSEEK_API_KEY';\n  static const String _modelIdEnv = 'DEEPSEEK_MODEL_ID';\n  static const String _baseUrlEnv = 'DEEPSEEK_BASE_URL';\n  static const String _defaultBaseUrl = 'https://api.deepseek.com/chat/completions';\n\n  static bool _dotenvLoaded = false;\n\n  Future<void> _ensureEnvLoaded() async {\n    if (_dotenvLoaded) return;\n    await dotenv.load(fileName: '.env');\n    _dotenvLoaded = true;\n  }\n\n  Future<String> callTextPrompt({\n    required String prompt,\n    required String userText,\n  }) async {\n    await _ensureEnvLoaded();\n\n    final String apiKey = (dotenv.env[_apiKeyEnv] ?? '').trim();\n    final String modelId = (dotenv.env[_modelIdEnv] ?? '').trim();\n    final String baseUrl = (dotenv.env[_baseUrlEnv] ?? _defaultBaseUrl).trim();\n\n    AppLogger.instance.info('[DeepSeek] 请求模型: $modelId');\n    AppLogger.instance.info('[DeepSeek] 请求端点: $baseUrl');\n    AppLogger.instance.info('[DeepSeek] system prompt 长度: ${prompt.length} 字符');\n    AppLogger.instance.info('[DeepSeek] user text 长度: ${userText.length} 字符');\n    if (userText.length <= 300) {\n      AppLogger.instance.info('[DeepSeek] user text 内容: $userText');\n    } else {\n      AppLogger.instance.info('[DeepSeek] user text 预览(前300字): ${userText.substring(0, 300)}...');\n    }\n\n    if (apiKey.isEmpty) {\n      throw Exception('Missing env config: DEEPSEEK_API_KEY');\n    }\n    if (modelId.isEmpty) {\n      throw Exception('Missing env config: DEEPSEEK_MODEL_ID');\n    }\n\n    final Map<String, String> headers = <String, String>{\n      'Content-Type': 'application/json',\n      'Authorization': 'Bearer $apiKey',\n    };\n\n    final List<Map<String, String>> messages = <Map<String, String>>[\n      <String, String>{'role': 'system', 'content': prompt},\n      <String, String>{'role': 'user', 'content': userText},\n    ];\n\n    final Stopwatch sw = Stopwatch()..start();\n    final http.Response response = await http.post(\n      Uri.parse(baseUrl),\n      headers: headers,\n      body: jsonEncode(<String, dynamic>{\n        'model': modelId,\n        'messages': messages,\n      }),\n    ).timeout(const Duration(seconds: 60), onTimeout: () {\n      throw Exception('DeepSeek API 请求超时（60秒）');\n    });\n    sw.stop();\n    AppLogger.instance.info('[DeepSeek] 响应状态: ${response.statusCode}，耗时 ${sw.elapsedMilliseconds}ms');\n\n    if (response.statusCode != 200) {\n      final String detail = utf8.decode(response.bodyBytes);\n      AppLogger.instance.error('[DeepSeek] API 错误响应体: $detail');\n      throw Exception('DeepSeek API error: $detail');\n    }\n\n    final dynamic data = jsonDecode(utf8.decode(response.bodyBytes));\n    final String parsed = _extractContentFromResponse(data).trim();\n    AppLogger.instance.info('[DeepSeek] 提取内容长度: ${parsed.length} 字符');\n    if (parsed.length <= 500) {\n      AppLogger.instance.info('[DeepSeek] 响应内容: $parsed');\n    } else {\n      AppLogger.instance.info('[DeepSeek] 响应预览(前500字): ${parsed.substring(0, 500)}...');\n    }\n\n    if (parsed.isEmpty) {\n      AppLogger.instance.warn('[DeepSeek] 返回空内容！原始响应: ${utf8.decode(response.bodyBytes)}');\n      throw Exception('DeepSeek API returned empty content.');\n    }\n    return parsed;\n  }\n\n  String _extractContentFromResponse(dynamic data) {\n    final dynamic chatContent = data['choices']?[0]?['message']?['content'];\n    if (chatContent is String && chatContent.trim().isNotEmpty) {\n      return chatContent.trim();\n    }\n    return '';\n  }\n}\n"}, "94334c08701d284ffe513538298d40c09b964dd1": {"t": 1785757856.2831054, "n": 3615, "h": "a009ee3366c9a8b5", "c": "import 'dart:convert';\n\nimport 'package:flutter_dotenv/flutter_dotenv.dart';\nimport 'package:http/http.dart' as http;\nimport 'package:mathmate/services/app_logger.dart';\n\nclass DeepSeekService {\n  static const String _apiKeyEnv = 'DEEPSEEK_API_KEY';\n  static const String _modelIdEnv = 'DEEPSEEK_MODEL_ID';\n  static const String _baseUrlEnv = 'DEEPSEEK_BASE_URL';\n  static const String _defaultBaseUrl = 'https://api.deepseek.com/chat/completions';\n\n  static bool _dotenvLoaded = false;\n\n  Future<void> _ensureEnvLoaded() async {\n    if (_dotenvLoaded) return;\n    await dotenv.load(fileName: '.env');\n    _dotenvLoaded = true;\n  }\n\n  Future<String> callTextPrompt({\n    required String prompt,\n    required String userText,\n  }) async {\n    await _ensureEnvLoaded();\n\n    final String apiKey = (dotenv.env[_apiKeyEnv] ?? '').trim();\n    final String modelId = (dotenv.env[_modelIdEnv] ?? '').trim();\n    final String baseUrl = (dotenv.env[_baseUrlEnv] ?? _defaultBaseUrl).trim();\n\n    AppLogger.instance.info('[DeepSeek] 请求模型: $modelId');\n    AppLogger.instance.info('[DeepSeek] 请求端点: $baseUrl');\n    AppLogger.instance.info('[DeepSeek] system prompt 长度: ${prompt.length} 字符');\n    AppLogger.instance.info('[DeepSeek] user text 长度: ${userText.length} 字符');\n    if (userText.length <= 300) {\n      AppLogger.instance.info('[DeepSeek] user text 内容: $userText');\n    } else {\n      AppLogger.instance.info('[DeepSeek] user text 预览(前300字): ${userText.substring(0, 300)}...');\n    }\n\n    if (apiKey.isEmpty) {\n      throw Exception('Missing env config: DEEPSEEK_API_KEY');\n    }\n    if (modelId.isEmpty) {\n      throw Exception('Missing env config: DEEPSEEK_MODEL_ID');\n    }\n\n    final Map<String, String> headers = <String, String>{\n      'Content-Type': 'application/json',\n      'Authorization': 'Bearer $apiKey',\n    };\n\n    final List<Map<String, String>> messages = <Map<String, String>>[\n      <String, String>{'role': 'system', 'content': prompt},\n      <String, String>{'role': 'user', 'content': userText},\n    ];\n\n    final Stopwatch sw = Stopwatch()..start();\n    final http.Response response = await http.post(\n      Uri.parse(baseUrl),\n      headers: headers,\n      body: jsonEncode(<String, dynamic>{\n        'model': modelId,\n        'messages': messages,\n      }),\n    ).timeout(const Duration(seconds: 60), onTimeout: () {\n      throw Exception('DeepSeek API 请求超时（60秒）');\n    });\n    sw.stop();\n    AppLogger.instance.info('[DeepSeek] 响应状态: ${response.statusCode}，耗时 ${sw.elapsedMilliseconds}ms');\n\n    if (response.statusCode != 200) {\n      final String detail = utf8.decode(response.bodyBytes);\n      AppLogger.instance.error('[DeepSeek] API 错误响应体: $detail');\n      throw Exception('DeepSeek API error: $detail');\n    }\n\n    final dynamic data = jsonDecode(utf8.decode(response.bodyBytes));\n    final String parsed = _extractContentFromResponse(data).trim();\n    AppLogger.instance.info('[DeepSeek] 提取内容长度: ${parsed.length} 字符');\n    if (parsed.length <= 500) {\n      AppLogger.instance.info('[DeepSeek] 响应内容: $parsed');\n    } else {\n      AppLogger.instance.info('[DeepSeek] 响应预览(前500字): ${parsed.substring(0, 500)}...');\n    }\n\n    if (parsed.isEmpty) {\n      AppLogger.instance.warn('[DeepSeek] 返回空内容！原始响应: ${utf8.decode(response.bodyBytes)}');\n      throw Exception('DeepSeek API returned empty content.');\n    }\n    return parsed;\n  }\n\n  String _extractContentFromResponse(dynamic data) {\n    final dynamic chatContent = data['choices']?[0]?['message']?['content'];\n    if (chatContent is String && chatContent.trim().isNotEmpty) {\n      return chatContent.trim();\n    }\n    return '';\n  }\n}\n"}, "ff928563d170e0b958fbaff90b380f66c7473c8e": {"t": 1785757857.5896492, "n": 2563, "h": "b9d4678132d35982", "c": "import 'dart:convert';\n\nimport 'package:flutter/foundation.dart';\nimport 'package:flutter_dotenv/flutter_dotenv.dart';\nimport 'package:http/http.dart' as http;\n\nclass DeepSeekService {\n  static const String _apiKeyEnv = 'DEEPSEEK_API_KEY';\n  static const String _modelIdEnv = 'DEEPSEEK_MODEL_ID';\n  static const String _baseUrlEnv = 'DEEPSEEK_BASE_URL';\n  static const String _defaultBaseUrl = 'https://api.deepseek.com/chat/completions';\n\n  static bool _dotenvLoaded = false;\n\n  Future<void> _ensureEnvLoaded() async {\n    if (_dotenvLoaded) return;\n    await dotenv.load(fileName: '.env');\n    _dotenvLoaded = true;\n  }\n\n  Future<String> callTextPrompt({\n    required String prompt,\n    required String userText,\n  }) async {\n    await _ensureEnvLoaded();\n\n    final String apiKey = (dotenv.env[_apiKeyEnv] ?? '').trim();\n    final String modelId = (dotenv.env[_modelIdEnv] ?? '').trim();\n    final String baseUrl = (dotenv.env[_baseUrlEnv] ?? _defaultBaseUrl).trim();\n\n    if (apiKey.isEmpty) {\n      throw Exception('Missing env config: DEEPSEEK_API_KEY');\n    }\n    if (modelId.isEmpty) {\n      throw Exception('Missing env config: DEEPSEEK_MODEL_ID');\n    }\n\n    final Map<String, String> headers = <String, String>{\n      'Content-Type': 'application/json',\n      'Authorization': 'Bearer $apiKey',\n    };\n\n    final List<Map<String, String>> messages = <Map<String, String>>[\n      <String, String>{'role': 'system', 'content': prompt},\n      <String, String>{'role': 'user', 'content': userText},\n    ];\n\n    final http.Response response = await http.post(\n      Uri.parse(baseUrl),\n      headers: headers,\n      body: jsonEncode(<String, dynamic>{\n        'model': modelId,\n        'messages': messages,\n      }),\n    ).timeout(const Duration(seconds: 60), onTimeout: () {\n      throw Exception('DeepSeek API 请求超时（60秒）');\n    });\n\n    if (response.statusCode != 200) {\n      final String detail = utf8.decode(response.bodyBytes);\n      debugPrint('DeepSeek API error: $detail');\n      throw Exception('DeepSeek API error: $detail');\n    }\n\n    final dynamic data = jsonDecode(utf8.decode(response.bodyBytes));\n    final String parsed = _extractContentFromResponse(data).trim();\n    if (parsed.isEmpty) {\n      throw Exception('DeepSeek API returned empty content.');\n    }\n    return parsed;\n  }\n\n  String _extractContentFromResponse(dynamic data) {\n    final dynamic chatContent = data['choices']?[0]?['message']?['content'];\n    if (chatContent is String && chatContent.trim().isNotEmpty) {\n      return chatContent.trim();\n    }\n    return '';\n  }\n}\n"}, "4a914e11f67b80b9e472192e937822f0a6be4e62": {"t": 1785757858.921628, "n": 2454, "h": "c4a990b4d2d8ddd6", "c": "import 'dart:convert';\n\nimport 'package:flutter/foundation.dart';\nimport 'package:flutter_dotenv/flutter_dotenv.dart';\nimport 'package:http/http.dart' as http;\n\nclass DeepSeekService {\n  static const String _apiKeyEnv = 'DEEPSEEK_API_KEY';\n  static const String _modelIdEnv = 'DEEPSEEK_MODEL_ID';\n  static const String _baseUrlEnv = 'DEEPSEEK_BASE_URL';\n  static const String _defaultBaseUrl = 'https://api.deepseek.com/chat/completions';\n\n  static bool _dotenvLoaded = false;\n\n  Future<void> _ensureEnvLoaded() async {\n    if (_dotenvLoaded) return;\n    await dotenv.load(fileName: '.env');\n    _dotenvLoaded = true;\n  }\n\n  Future<String> callTextPrompt({\n    required String prompt,\n    required String userText,\n  }) async {\n    await _ensureEnvLoaded();\n\n    final String apiKey = (dotenv.env[_apiKeyEnv] ?? '').trim();\n    final String modelId = (dotenv.env[_modelIdEnv] ?? '').trim();\n    final String baseUrl = (dotenv.env[_baseUrlEnv] ?? _defaultBaseUrl).trim();\n\n    if (apiKey.isEmpty) {\n      throw Exception('Missing env config: DEEPSEEK_API_KEY');\n    }\n    if (modelId.isEmpty) {\n      throw Exception('Missing env config: DEEPSEEK_MODEL_ID');\n    }\n\n    final Map<String, String> headers = <String, String>{\n      'Content-Type': 'application/json',\n      'Authorization': 'Bearer $apiKey',\n    };\n\n    final List<Map<String, String>> messages = <Map<String, String>>[\n      <String, String>{'role': 'system', 'content': prompt},\n      <String, String>{'role': 'user', 'content': userText},\n    ];\n\n    final http.Response response = await http.post(\n      Uri.parse(baseUrl),\n      headers: headers,\n      body: jsonEncode(<String, dynamic>{\n        'model': modelId,\n        'messages': messages,\n      }),\n    );\n\n    if (response.statusCode != 200) {\n      final String detail = utf8.decode(response.bodyBytes);\n      debugPrint('DeepSeek API error: $detail');\n      throw Exception('DeepSeek API error: $detail');\n    }\n\n    final dynamic data = jsonDecode(utf8.decode(response.bodyBytes));\n    final String parsed = _extractContentFromResponse(data).trim();\n    if (parsed.isEmpty) {\n      throw Exception('DeepSeek API returned empty content.');\n    }\n    return parsed;\n  }\n\n  String _extractContentFromResponse(dynamic data) {\n    final dynamic chatContent = data['choices']?[0]?['message']?['content'];\n    if (chatContent is String && chatContent.trim().isNotEmpty) {\n      return chatContent.trim();\n    }\n    return '';\n  }\n}\n"}}, "lib/services/geogebra_agent_service.dart": {"cd430dbed71b344a768a697fd5da313464a413f6": {"t": 1785745918.7735226, "n": 8524, "h": "5db151fe9967cf49", "c": "import 'dart:async';\nimport 'dart:convert';\n\nimport 'package:flutter/foundation.dart';\nimport 'package:flutter_dotenv/flutter_dotenv.dart';\nimport 'package:http/http.dart' as http;\n\nimport 'prompts/geogebra_agent_prompt.dart';\n\n/// Agent 流式响应块\nclass AgentStreamChunk {\n  final String? textDelta;       // 文本增量\n  final String? toolCallName;    // 工具调用名称（开始时）\n  final String? toolCallArgs;    // 工具调用参数（完整 JSON）\n  final String? toolResult;      // 工具执行结果描述\n  final bool isDone;\n  final String? error;\n\n  AgentStreamChunk({\n    this.textDelta,\n    this.toolCallName,\n    this.toolCallArgs,\n    this.toolResult,\n    this.isDone = false,\n    this.error,\n  });\n}\n\n/// 工具定义（发给 LLM）\nclass AgentTool {\n  final String name;\n  final String description;\n  final Map<String, dynamic> parameters; // JSON Schema\n\n  const AgentTool({required this.name, required this.description, required this.parameters});\n\n  Map<String, dynamic> toOpenAITool() => {\n    'type': 'function',\n    'function': {\n      'name': name,\n      'description': description,\n      'parameters': parameters,\n    },\n  };\n}\n\n/// GeoGebra 7 个 MCP 工具定义\nconst List<AgentTool> geogebraTools = [\n  AgentTool(\n    name: 'getCanvasContext',\n    description: '获取当前 GeoGebra 画布的完整状态，包括所有对象和表达式',\n    parameters: {\n      'type': 'object',\n      'properties': {},\n    },\n  ),\n  AgentTool(\n    name: 'executeGeoGebraCommand',\n    description: '在 GeoGebra 画布中执行一条命令，返回执行结果',\n    parameters: {\n      'type': 'object',\n      'properties': {\n        'command': {'type': 'string', 'description': '要执行的 GeoGebra 命令'},\n      },\n      'required': ['command'],\n    },\n  ),\n  AgentTool(\n    name: 'deleteGeoGebraObject',\n    description: '从 GeoGebra 画布中删除指定标签的对象',\n    parameters: {\n      'type': 'object',\n      'properties': {\n        'label': {'type': 'string', 'description': '要删除的对象标签'},\n      },\n      'required': ['label'],\n    },\n  ),\n  AgentTool(\n    name: 'setUndoPoint',\n    description: '在 GeoGebra 画布中设置一个撤销点',\n    parameters: {\n      'type': 'object',\n      'properties': {},\n    },\n  ),\n  AgentTool(\n    name: 'undo',\n    description: '在 GeoGebra 画布中执行撤销操作',\n    parameters: {\n      'type': 'object',\n      'properties': {},\n    },\n  ),\n  AgentTool(\n    name: 'setPerspective',\n    description: \"切换 GeoGebra 视图模式：'G'=2D图形, 'T'=3D图形\",\n    parameters: {\n      'type': 'object',\n      'properties': {\n        'mode': {'type': 'string', 'description': \"视图模式：'G' 或 'T'\"},\n      },\n      'required': ['mode'],\n    },\n  ),\n  AgentTool(\n    name: 'getSelectedObjects',\n    description: '获取用户当前在 GeoGebra 画布中选中的对象标签列表',\n    parameters: {\n      'type': 'object',\n      'properties': {},\n    },\n  ),\n];\n\n/// GeoGebra Agent 服务。\n///\n/// 使用 DeepSeek API 的 function calling 能力，让 LLM 通过工具调用\n/// 操控 GeoGebra 画布。对外提供流式响应。\nclass GeogebraAgentService {\n  final String _apiKeyEnv;\n  final String _modelEnv;\n  final String _baseUrlEnv;\n  final String _defaultBaseUrl;\n  final String _defaultModel;\n\n  /// 工具执行回调 —— 由外部注入，桥接 JS Bridge。\n  Future<String> Function(String toolName, Map<String, dynamic> args)? onToolCall;\n\n  GeogebraAgentService({\n    String apiKeyEnv = 'DEEPSEEK_API_KEY',\n    String modelEnv = 'DEEPSEEK_MODEL_ID',\n    String baseUrlEnv = 'DEEPSEEK_BASE_URL',\n    String defaultBaseUrl = 'https://api.deepseek.com/chat/completions',\n    String defaultModel = 'deepseek-chat',\n  })  : _apiKeyEnv = apiKeyEnv,\n        _modelEnv = modelEnv,\n        _baseUrlEnv = baseUrlEnv,\n        _defaultBaseUrl = defaultBaseUrl,\n        _defaultModel = defaultModel;\n\n  static bool _dotenvLoaded = false;\n  http.Client? _client;\n  bool _cancelled = false;\n\n  Future<void> _ensureEnv() async {\n    if (_dotenvLoaded) return;\n    await dotenv.load(fileName: '.env');\n    _dotenvLoaded = true;\n  }\n\n  void cancel() {\n    _cancelled = true;\n    _closeClient();\n  }\n\n  void _closeClient() {\n    try { _client?.close(); } catch (_) {}\n    _client = null;\n  }\n\n  /// 流式对话入口。\n  /// [messages] 为历史对话，不含 system prompt（会自动添加）。\n  /// 最多 [maxSteps] 轮工具调用。\n  Stream<AgentStreamChunk> chat({\n    required List<Map<String, String>> messages,\n    int maxSteps = 10,\n  }) async* {\n    await _ensureEnv();\n    _cancelled = false;\n\n    final apiKey = (dotenv.env[_apiKeyEnv] ?? '').trim();\n    final model = (dotenv.env[_modelEnv] ?? _defaultModel).trim();\n    final baseUrl = (dotenv.env[_baseUrlEnv] ?? _defaultBaseUrl).trim();\n\n    if (apiKey.isEmpty) {\n      yield AgentStreamChunk(error: '缺少 API Key: $_apiKeyEnv');\n      return;\n    }\n\n    // 构建完整消息列表（含 system prompt）\n    final fullMessages = <Map<String, dynamic>>[\n      {'role': 'system', 'content': geogebraAgentSystemPrompt},\n      ...messages.map((m) => {'role': m['role'], 'content': m['content']}),\n    ];\n\n    int stepCount = 0;\n    while (stepCount < maxSteps && !_cancelled) {\n      stepCount++;\n\n      final response = await _sendRequest(\n        apiKey: apiKey,\n        model: model,\n        baseUrl: baseUrl,\n        messages: fullMessages,\n      );\n\n      if (response == null) {\n        yield AgentStreamChunk(error: 'API 请求失败');\n        return;\n      }\n\n      final choice = response['choices']?[0] as Map<String, dynamic>?;\n      if (choice == null) {\n        yield AgentStreamChunk(error: 'API 响应格式异常');\n        return;\n      }\n\n      final message = choice['message'] as Map<String, dynamic>?;\n      if (message == null) {\n        yield AgentStreamChunk(error: '消息为空');\n        return;\n      }\n\n      // 文本响应\n      final content = (message['content'] as String?)?.trim() ?? '';\n      if (content.isNotEmpty) {\n        yield AgentStreamChunk(textDelta: content);\n      }\n\n      // 工具调用\n      final toolCalls = message['tool_calls'] as List<dynamic>?;\n      if (toolCalls == null || toolCalls.isEmpty) {\n        // 无工具调用，对话结束\n        fullMessages.add(message);\n        yield AgentStreamChunk(isDone: true);\n        return;\n      }\n\n      // 处理工具调用\n      fullMessages.add(message); // 添加 assistant 消息（含 tool_calls）\n\n      for (final tc in toolCalls) {\n        if (_cancelled) break;\n        final toolCall = tc as Map<String, dynamic>;\n        final fn = toolCall['function'] as Map<String, dynamic>?;\n        if (fn == null) continue;\n\n        final toolName = (fn['name'] as String?) ?? '';\n        final toolArgsStr = (fn['arguments'] as String?) ?? '{}';\n\n        yield AgentStreamChunk(toolCallName: toolName, toolCallArgs: toolArgsStr);\n\n        // 解析参数\n        Map<String, dynamic> args;\n        try {\n          args = jsonDecode(toolArgsStr) as Map<String, dynamic>;\n        } catch (_) {\n          args = <String, dynamic>{};\n        }\n\n        // 执行工具\n        String toolResult;\n        if (onToolCall != null) {\n          try {\n            toolResult = await onToolCall!(toolName, args);\n          } catch (e) {\n            toolResult = 'Error: $e';\n          }\n        } else {\n          toolResult = '工具未配置执行回调';\n        }\n\n        yield AgentStreamChunk(toolResult: toolResult);\n\n        // 添加 tool 响应消息\n        fullMessages.add({\n          'role': 'tool',\n          'tool_call_id': toolCall['id'] ?? '',\n          'content': toolResult,\n        });\n      }\n    }\n\n    if (stepCount >= maxSteps) {\n      yield AgentStreamChunk(textDelta: '\\n\\n已达到最大推理步数限制。');\n    }\n    yield AgentStreamChunk(isDone: true);\n  }\n\n  /// 发送一次请求（非流式，等完整响应后再处理，简化 tool calling 逻辑）。\n  Future<Map<String, dynamic>?> _sendRequest({\n    required String apiKey,\n    required String model,\n    required String baseUrl,\n    required List<Map<String, dynamic>> messages,\n  }) async {\n    try {\n      final body = jsonEncode({\n        'model': model,\n        'messages': messages,\n        'tools': geogebraTools.map((t) => t.toOpenAITool()).toList(),\n        'tool_choice': 'auto',\n        'temperature': 0.6,\n      });\n\n      _client = http.Client();\n      final request = http.Request('POST', Uri.parse(baseUrl))\n        ..headers.addAll({\n          'Content-Type': 'application/json; charset=utf-8',\n          'Authorization': 'Bearer $apiKey',\n        })\n        ..body = body;\n\n      final streamedResponse = await _client!.send(request).timeout(\n        const Duration(seconds: 60),\n        onTimeout: () => throw Exception('请求超时'),\n      );\n\n      final responseBody = await streamedResponse.stream.bytesToString();\n\n      if (streamedResponse.statusCode != 200) {\n        debugPrint('[GeoAgent] API error: $responseBody');\n        return null;\n      }\n\n      return jsonDecode(responseBody) as Map<String, dynamic>;\n    } catch (e) {\n      debugPrint('[GeoAgent] Request error: $e');\n      return null;\n    } finally {\n      _closeClient();\n    }\n  }\n}\n"}, "27af3dafd8649ff653f8b0291f422506c388c09f": {"t": 1785757856.3879807, "n": 8524, "h": "5db151fe9967cf49", "c": "import 'dart:async';\nimport 'dart:convert';\n\nimport 'package:flutter/foundation.dart';\nimport 'package:flutter_dotenv/flutter_dotenv.dart';\nimport 'package:http/http.dart' as http;\n\nimport 'prompts/geogebra_agent_prompt.dart';\n\n/// Agent 流式响应块\nclass AgentStreamChunk {\n  final String? textDelta;       // 文本增量\n  final String? toolCallName;    // 工具调用名称（开始时）\n  final String? toolCallArgs;    // 工具调用参数（完整 JSON）\n  final String? toolResult;      // 工具执行结果描述\n  final bool isDone;\n  final String? error;\n\n  AgentStreamChunk({\n    this.textDelta,\n    this.toolCallName,\n    this.toolCallArgs,\n    this.toolResult,\n    this.isDone = false,\n    this.error,\n  });\n}\n\n/// 工具定义（发给 LLM）\nclass AgentTool {\n  final String name;\n  final String description;\n  final Map<String, dynamic> parameters; // JSON Schema\n\n  const AgentTool({required this.name, required this.description, required this.parameters});\n\n  Map<String, dynamic> toOpenAITool() => {\n    'type': 'function',\n    'function': {\n      'name': name,\n      'description': description,\n      'parameters': parameters,\n    },\n  };\n}\n\n/// GeoGebra 7 个 MCP 工具定义\nconst List<AgentTool> geogebraTools = [\n  AgentTool(\n    name: 'getCanvasContext',\n    description: '获取当前 GeoGebra 画布的完整状态，包括所有对象和表达式',\n    parameters: {\n      'type': 'object',\n      'properties': {},\n    },\n  ),\n  AgentTool(\n    name: 'executeGeoGebraCommand',\n    description: '在 GeoGebra 画布中执行一条命令，返回执行结果',\n    parameters: {\n      'type': 'object',\n      'properties': {\n        'command': {'type': 'string', 'description': '要执行的 GeoGebra 命令'},\n      },\n      'required': ['command'],\n    },\n  ),\n  AgentTool(\n    name: 'deleteGeoGebraObject',\n    description: '从 GeoGebra 画布中删除指定标签的对象',\n    parameters: {\n      'type': 'object',\n      'properties': {\n        'label': {'type': 'string', 'description': '要删除的对象标签'},\n      },\n      'required': ['label'],\n    },\n  ),\n  AgentTool(\n    name: 'setUndoPoint',\n    description: '在 GeoGebra 画布中设置一个撤销点',\n    parameters: {\n      'type': 'object',\n      'properties': {},\n    },\n  ),\n  AgentTool(\n    name: 'undo',\n    description: '在 GeoGebra 画布中执行撤销操作',\n    parameters: {\n      'type': 'object',\n      'properties': {},\n    },\n  ),\n  AgentTool(\n    name: 'setPerspective',\n    description: \"切换 GeoGebra 视图模式：'G'=2D图形, 'T'=3D图形\",\n    parameters: {\n      'type': 'object',\n      'properties': {\n        'mode': {'type': 'string', 'description': \"视图模式：'G' 或 'T'\"},\n      },\n      'required': ['mode'],\n    },\n  ),\n  AgentTool(\n    name: 'getSelectedObjects',\n    description: '获取用户当前在 GeoGebra 画布中选中的对象标签列表',\n    parameters: {\n      'type': 'object',\n      'properties': {},\n    },\n  ),\n];\n\n/// GeoGebra Agent 服务。\n///\n/// 使用 DeepSeek API 的 function calling 能力，让 LLM 通过工具调用\n/// 操控 GeoGebra 画布。对外提供流式响应。\nclass GeogebraAgentService {\n  final String _apiKeyEnv;\n  final String _modelEnv;\n  final String _baseUrlEnv;\n  final String _defaultBaseUrl;\n  final String _defaultModel;\n\n  /// 工具执行回调 —— 由外部注入，桥接 JS Bridge。\n  Future<String> Function(String toolName, Map<String, dynamic> args)? onToolCall;\n\n  GeogebraAgentService({\n    String apiKeyEnv = 'DEEPSEEK_API_KEY',\n    String modelEnv = 'DEEPSEEK_MODEL_ID',\n    String baseUrlEnv = 'DEEPSEEK_BASE_URL',\n    String defaultBaseUrl = 'https://api.deepseek.com/chat/completions',\n    String defaultModel = 'deepseek-chat',\n  })  : _apiKeyEnv = apiKeyEnv,\n        _modelEnv = modelEnv,\n        _baseUrlEnv = baseUrlEnv,\n        _defaultBaseUrl = defaultBaseUrl,\n        _defaultModel = defaultModel;\n\n  static bool _dotenvLoaded = false;\n  http.Client? _client;\n  bool _cancelled = false;\n\n  Future<void> _ensureEnv() async {\n    if (_dotenvLoaded) return;\n    await dotenv.load(fileName: '.env');\n    _dotenvLoaded = true;\n  }\n\n  void cancel() {\n    _cancelled = true;\n    _closeClient();\n  }\n\n  void _closeClient() {\n    try { _client?.close(); } catch (_) {}\n    _client = null;\n  }\n\n  /// 流式对话入口。\n  /// [messages] 为历史对话，不含 system prompt（会自动添加）。\n  /// 最多 [maxSteps] 轮工具调用。\n  Stream<AgentStreamChunk> chat({\n    required List<Map<String, String>> messages,\n    int maxSteps = 10,\n  }) async* {\n    await _ensureEnv();\n    _cancelled = false;\n\n    final apiKey = (dotenv.env[_apiKeyEnv] ?? '').trim();\n    final model = (dotenv.env[_modelEnv] ?? _defaultModel).trim();\n    final baseUrl = (dotenv.env[_baseUrlEnv] ?? _defaultBaseUrl).trim();\n\n    if (apiKey.isEmpty) {\n      yield AgentStreamChunk(error: '缺少 API Key: $_apiKeyEnv');\n      return;\n    }\n\n    // 构建完整消息列表（含 system prompt）\n    final fullMessages = <Map<String, dynamic>>[\n      {'role': 'system', 'content': geogebraAgentSystemPrompt},\n      ...messages.map((m) => {'role': m['role'], 'content': m['content']}),\n    ];\n\n    int stepCount = 0;\n    while (stepCount < maxSteps && !_cancelled) {\n      stepCount++;\n\n      final response = await _sendRequest(\n        apiKey: apiKey,\n        model: model,\n        baseUrl: baseUrl,\n        messages: fullMessages,\n      );\n\n      if (response == null) {\n        yield AgentStreamChunk(error: 'API 请求失败');\n        return;\n      }\n\n      final choice = response['choices']?[0] as Map<String, dynamic>?;\n      if (choice == null) {\n        yield AgentStreamChunk(error: 'API 响应格式异常');\n        return;\n      }\n\n      final message = choice['message'] as Map<String, dynamic>?;\n      if (message == null) {\n        yield AgentStreamChunk(error: '消息为空');\n        return;\n      }\n\n      // 文本响应\n      final content = (message['content'] as String?)?.trim() ?? '';\n      if (content.isNotEmpty) {\n        yield AgentStreamChunk(textDelta: content);\n      }\n\n      // 工具调用\n      final toolCalls = message['tool_calls'] as List<dynamic>?;\n      if (toolCalls == null || toolCalls.isEmpty) {\n        // 无工具调用，对话结束\n        fullMessages.add(message);\n        yield AgentStreamChunk(isDone: true);\n        return;\n      }\n\n      // 处理工具调用\n      fullMessages.add(message); // 添加 assistant 消息（含 tool_calls）\n\n      for (final tc in toolCalls) {\n        if (_cancelled) break;\n        final toolCall = tc as Map<String, dynamic>;\n        final fn = toolCall['function'] as Map<String, dynamic>?;\n        if (fn == null) continue;\n\n        final toolName = (fn['name'] as String?) ?? '';\n        final toolArgsStr = (fn['arguments'] as String?) ?? '{}';\n\n        yield AgentStreamChunk(toolCallName: toolName, toolCallArgs: toolArgsStr);\n\n        // 解析参数\n        Map<String, dynamic> args;\n        try {\n          args = jsonDecode(toolArgsStr) as Map<String, dynamic>;\n        } catch (_) {\n          args = <String, dynamic>{};\n        }\n\n        // 执行工具\n        String toolResult;\n        if (onToolCall != null) {\n          try {\n            toolResult = await onToolCall!(toolName, args);\n          } catch (e) {\n            toolResult = 'Error: $e';\n          }\n        } else {\n          toolResult = '工具未配置执行回调';\n        }\n\n        yield AgentStreamChunk(toolResult: toolResult);\n\n        // 添加 tool 响应消息\n        fullMessages.add({\n          'role': 'tool',\n          'tool_call_id': toolCall['id'] ?? '',\n          'content': toolResult,\n        });\n      }\n    }\n\n    if (stepCount >= maxSteps) {\n      yield AgentStreamChunk(textDelta: '\\n\\n已达到最大推理步数限制。');\n    }\n    yield AgentStreamChunk(isDone: true);\n  }\n\n  /// 发送一次请求（非流式，等完整响应后再处理，简化 tool calling 逻辑）。\n  Future<Map<String, dynamic>?> _sendRequest({\n    required String apiKey,\n    required String model,\n    required String baseUrl,\n    required List<Map<String, dynamic>> messages,\n  }) async {\n    try {\n      final body = jsonEncode({\n        'model': model,\n        'messages': messages,\n        'tools': geogebraTools.map((t) => t.toOpenAITool()).toList(),\n        'tool_choice': 'auto',\n        'temperature': 0.6,\n      });\n\n      _client = http.Client();\n      final request = http.Request('POST', Uri.parse(baseUrl))\n        ..headers.addAll({\n          'Content-Type': 'application/json; charset=utf-8',\n          'Authorization': 'Bearer $apiKey',\n        })\n        ..body = body;\n\n      final streamedResponse = await _client!.send(request).timeout(\n        const Duration(seconds: 60),\n        onTimeout: () => throw Exception('请求超时'),\n      );\n\n      final responseBody = await streamedResponse.stream.bytesToString();\n\n      if (streamedResponse.statusCode != 200) {\n        debugPrint('[GeoAgent] API error: $responseBody');\n        return null;\n      }\n\n      return jsonDecode(responseBody) as Map<String, dynamic>;\n    } catch (e) {\n      debugPrint('[GeoAgent] Request error: $e');\n      return null;\n    } finally {\n      _closeClient();\n    }\n  }\n}\n"}}, "deploy/proxy_server.js": {"cd430dbed71b344a768a697fd5da313464a413f6": {"t": 1785746682.0448568, "n": 4445, "h": "a93a2d5c32078cdb", "c": "const http = require('http');\nconst https = require('https');\nconst fs = require('fs');\n\n// ============================================================\n// MathMate API 代理服务\n// 用途：接收 Flutter Web 前端的 API 请求，转发到 DeepSeek/Vivo/Volc\n// 好处：API Key 只存在服务器，前端 JS 中不会泄露\n//\n// 启动: node proxy_server.js\n// 端口: 3001（Nginx 反向代理 /api/* → localhost:3001）\n// ============================================================\n\nfunction loadEnv() {\n  const content = fs.readFileSync(__dirname + '/.env.server', 'utf-8');\n  const env = {};\n  for (const line of content.split('\\n')) {\n    const trimmed = line.trim();\n    if (!trimmed || trimmed.startsWith('#')) continue;\n    const eq = trimmed.indexOf('=');\n    if (eq === -1) continue;\n    env[trimmed.slice(0, eq).trim()] = trimmed.slice(eq + 1).trim();\n  }\n  return env;\n}\n\nconst ROUTES = {\n  '/api/deepseek': {\n    apiKeyEnv: 'DEEPSEEK_API_KEY',\n    modelEnv:   'DEEPSEEK_MODEL_ID',\n    baseUrlEnv: 'DEEPSEEK_BASE_URL',\n    defaultUrl: 'https://api.deepseek.com/chat/completions',\n  },\n  '/api/vivo': {\n    apiKeyEnv: 'VIVO_API_KEY',\n    modelEnv:   'VIVO_MODEL_ID',\n    baseUrlEnv: 'VIVO_BASE_URL',\n    defaultUrl: 'https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions',\n  },\n  '/api/volc': {\n    apiKeyEnv: 'VOLC_API_KEY',\n    modelEnv:   'VOLC_MODEL_ID',\n    baseUrlEnv: 'VOLC_BASE_URL',\n    defaultUrl: 'https://ark.cn-beijing.volces.com/api/v3/chat/completions',\n  },\n};\n\nconst env = loadEnv();\n\n// ---------- 代理转发 ----------\nfunction proxyRequest(clientReq, clientRes, bodyBuffer) {\n  const route = ROUTES[clientReq.url];\n  if (!route) {\n    clientRes.writeHead(404, { 'Content-Type': 'application/json' });\n    clientRes.end(JSON.stringify({ error: 'not found' }));\n    return;\n  }\n\n  const apiKey  = env[route.apiKeyEnv]  || '';\n  const modelId = env[route.modelEnv]   || '';\n  const baseUrl = env[route.baseUrlEnv] || route.defaultUrl;\n\n  if (!apiKey || !modelId) {\n    clientRes.writeHead(500, { 'Content-Type': 'application/json' });\n    clientRes.end(JSON.stringify({ error: `Server config missing: ${route.apiKeyEnv} or ${route.modelEnv}` }));\n    return;\n  }\n\n  const upstream = new URL(baseUrl);\n  const isHttps = upstream.protocol === 'https:';\n  const transport = isHttps ? https : http;\n\n  const options = {\n    hostname: upstream.hostname,\n    port:     upstream.port || (isHttps ? 443 : 80),\n    path:     upstream.pathname + upstream.search,\n    method:   'POST',\n    headers:  {\n      'Content-Type':  'application/json',\n      'Authorization': 'Bearer ' + apiKey,\n      'Content-Length': Buffer.byteLength(bodyBuffer),\n    },\n  };\n\n  console.log(`[proxy] → ${baseUrl}`);\n\n  const upstreamReq = transport.request(options, (upstreamRes) => {\n    const chunks = [];\n    upstreamRes.on('data',  c => chunks.push(c));\n    upstreamRes.on('end', () => {\n      const body = Buffer.concat(chunks);\n      clientRes.writeHead(upstreamRes.statusCode, {\n        'Content-Type':   'application/json',\n        'Access-Control-Allow-Origin': '*',\n      });\n      clientRes.end(body);\n      console.log(`[proxy] ← ${upstreamRes.statusCode} (${body.length} bytes)`);\n    });\n  });\n\n  upstreamReq.on('error', (err) => {\n    console.error('[proxy] error:', err.message);\n    clientRes.writeHead(502, { 'Content-Type': 'application/json' });\n    clientRes.end(JSON.stringify({ error: 'upstream error: ' + err.message }));\n  });\n\n  upstreamReq.write(bodyBuffer);\n  upstreamReq.end();\n}\n\n// ---------- HTTP Server ----------\nconst server = http.createServer((req, res) => {\n  const chunks = [];\n  req.on('data',  c => chunks.push(c));\n  req.on('end',  () => {\n    const body = Buffer.concat(chunks);\n    console.log(`[proxy] ${req.method} ${req.url} (${body.length} bytes)`);\n\n    if (req.method === 'OPTIONS') {\n      res.writeHead(200, {\n        'Access-Control-Allow-Origin':  '*',\n        'Access-Control-Allow-Methods': 'POST, OPTIONS',\n        'Access-Control-Allow-Headers': 'Content-Type, Authorization',\n      });\n      res.end();\n      return;\n    }\n\n    if (req.method === 'POST' && ROUTES[req.url]) {\n      proxyRequest(req, res, body);\n    } else {\n      res.writeHead(200, { 'Content-Type': 'text/plain' });\n      res.end('MathMate Proxy OK');\n    }\n  });\n});\n\nserver.listen(3001, '127.0.0.1', () => {\n  console.log('MathMate API Proxy running on http://127.0.0.1:3001');\n  console.log('Routes:');\n  for (const path of Object.keys(ROUTES)) {\n    console.log(`  POST ${path}`);\n  }\n});\n"}, "7c567d8a98d24a78f1afcb8f155d571631901208": {"t": 1785757857.3075223, "n": 4445, "h": "a93a2d5c32078cdb", "c": "const http = require('http');\nconst https = require('https');\nconst fs = require('fs');\n\n// ============================================================\n// MathMate API 代理服务\n// 用途：接收 Flutter Web 前端的 API 请求，转发到 DeepSeek/Vivo/Volc\n// 好处：API Key 只存在服务器，前端 JS 中不会泄露\n//\n// 启动: node proxy_server.js\n// 端口: 3001（Nginx 反向代理 /api/* → localhost:3001）\n// ============================================================\n\nfunction loadEnv() {\n  const content = fs.readFileSync(__dirname + '/.env.server', 'utf-8');\n  const env = {};\n  for (const line of content.split('\\n')) {\n    const trimmed = line.trim();\n    if (!trimmed || trimmed.startsWith('#')) continue;\n    const eq = trimmed.indexOf('=');\n    if (eq === -1) continue;\n    env[trimmed.slice(0, eq).trim()] = trimmed.slice(eq + 1).trim();\n  }\n  return env;\n}\n\nconst ROUTES = {\n  '/api/deepseek': {\n    apiKeyEnv: 'DEEPSEEK_API_KEY',\n    modelEnv:   'DEEPSEEK_MODEL_ID',\n    baseUrlEnv: 'DEEPSEEK_BASE_URL',\n    defaultUrl: 'https://api.deepseek.com/chat/completions',\n  },\n  '/api/vivo': {\n    apiKeyEnv: 'VIVO_API_KEY',\n    modelEnv:   'VIVO_MODEL_ID',\n    baseUrlEnv: 'VIVO_BASE_URL',\n    defaultUrl: 'https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions',\n  },\n  '/api/volc': {\n    apiKeyEnv: 'VOLC_API_KEY',\n    modelEnv:   'VOLC_MODEL_ID',\n    baseUrlEnv: 'VOLC_BASE_URL',\n    defaultUrl: 'https://ark.cn-beijing.volces.com/api/v3/chat/completions',\n  },\n};\n\nconst env = loadEnv();\n\n// ---------- 代理转发 ----------\nfunction proxyRequest(clientReq, clientRes, bodyBuffer) {\n  const route = ROUTES[clientReq.url];\n  if (!route) {\n    clientRes.writeHead(404, { 'Content-Type': 'application/json' });\n    clientRes.end(JSON.stringify({ error: 'not found' }));\n    return;\n  }\n\n  const apiKey  = env[route.apiKeyEnv]  || '';\n  const modelId = env[route.modelEnv]   || '';\n  const baseUrl = env[route.baseUrlEnv] || route.defaultUrl;\n\n  if (!apiKey || !modelId) {\n    clientRes.writeHead(500, { 'Content-Type': 'application/json' });\n    clientRes.end(JSON.stringify({ error: `Server config missing: ${route.apiKeyEnv} or ${route.modelEnv}` }));\n    return;\n  }\n\n  const upstream = new URL(baseUrl);\n  const isHttps = upstream.protocol === 'https:';\n  const transport = isHttps ? https : http;\n\n  const options = {\n    hostname: upstream.hostname,\n    port:     upstream.port || (isHttps ? 443 : 80),\n    path:     upstream.pathname + upstream.search,\n    method:   'POST',\n    headers:  {\n      'Content-Type':  'application/json',\n      'Authorization': 'Bearer ' + apiKey,\n      'Content-Length': Buffer.byteLength(bodyBuffer),\n    },\n  };\n\n  console.log(`[proxy] → ${baseUrl}`);\n\n  const upstreamReq = transport.request(options, (upstreamRes) => {\n    const chunks = [];\n    upstreamRes.on('data',  c => chunks.push(c));\n    upstreamRes.on('end', () => {\n      const body = Buffer.concat(chunks);\n      clientRes.writeHead(upstreamRes.statusCode, {\n        'Content-Type':   'application/json',\n        'Access-Control-Allow-Origin': '*',\n      });\n      clientRes.end(body);\n      console.log(`[proxy] ← ${upstreamRes.statusCode} (${body.length} bytes)`);\n    });\n  });\n\n  upstreamReq.on('error', (err) => {\n    console.error('[proxy] error:', err.message);\n    clientRes.writeHead(502, { 'Content-Type': 'application/json' });\n    clientRes.end(JSON.stringify({ error: 'upstream error: ' + err.message }));\n  });\n\n  upstreamReq.write(bodyBuffer);\n  upstreamReq.end();\n}\n\n// ---------- HTTP Server ----------\nconst server = http.createServer((req, res) => {\n  const chunks = [];\n  req.on('data',  c => chunks.push(c));\n  req.on('end',  () => {\n    const body = Buffer.concat(chunks);\n    console.log(`[proxy] ${req.method} ${req.url} (${body.length} bytes)`);\n\n    if (req.method === 'OPTIONS') {\n      res.writeHead(200, {\n        'Access-Control-Allow-Origin':  '*',\n        'Access-Control-Allow-Methods': 'POST, OPTIONS',\n        'Access-Control-Allow-Headers': 'Content-Type, Authorization',\n      });\n      res.end();\n      return;\n    }\n\n    if (req.method === 'POST' && ROUTES[req.url]) {\n      proxyRequest(req, res, body);\n    } else {\n      res.writeHead(200, { 'Content-Type': 'text/plain' });\n      res.end('MathMate Proxy OK');\n    }\n  });\n});\n\nserver.listen(3001, '127.0.0.1', () => {\n  console.log('MathMate API Proxy running on http://127.0.0.1:3001');\n  console.log('Routes:');\n  for (const path of Object.keys(ROUTES)) {\n    console.log(`  POST ${path}`);\n  }\n});\n"}}}}