import { Assistant, CallLog, KnowledgeBase, Voice, Workflow, AutoTestAssistant, TestType, TestMethod, Tool, LLMModel, ASRModel } from '../types'; export const mockVoices: Voice[] = [ { id: 'v1', name: 'Xiaoyun', vendor: 'Ali', gender: 'Female', language: 'zh', description: 'Gentle and professional.' }, { id: 'v2', name: 'Kevin', vendor: 'Volcano', gender: 'Male', language: 'en', description: 'Deep and authoritative.' }, { id: 'v3', name: 'Abby', vendor: 'Minimax', gender: 'Female', language: 'en', description: 'Cheerful and lively.' }, { id: 'v4', name: 'Guang', vendor: 'Ali', gender: 'Male', language: 'zh', description: 'Standard newscast style.' }, { id: 'v5', name: 'Doubao', vendor: 'Volcano', gender: 'Female', language: 'zh', description: 'Cute and young.' }, ]; export const mockAssistants: Assistant[] = [ { id: '1', name: 'Customer Support Bot', callCount: 154, opener: 'Hello, how can I help you today?', prompt: 'You are a helpful customer service agent.', knowledgeBaseId: 'kb1', language: 'en', voice: 'v3', speed: 1.0, hotwords: ['refund', 'order'], interruptionSensitivity: 500, }, { id: '2', name: 'Sales Agent', callCount: 89, opener: 'Hi! Are you interested in our new product?', prompt: 'You are an energetic sales representative.', knowledgeBaseId: 'kb2', language: 'zh', voice: 'v1', speed: 1.1, hotwords: ['price', 'discount'], interruptionSensitivity: 300, }, ]; export let mockWorkflows: Workflow[] = [ { id: 'wf1', name: 'Lead Qualification Agent', nodeCount: 11, createdAt: '2024-03-01 10:00', updatedAt: '2024-03-05 14:30', nodes: [ { name: "introduction", type: "conversation", isStart: true, metadata: { position: { x: 100, y: 100 } }, prompt: "You are Morgan from GrowthPartners. Start with: 'Hello, this is Morgan from GrowthPartners. We help businesses improve their operational efficiency through custom software solutions. Do you have a few minutes to chat about how we might be able to help your business?' Use a friendly, consultative tone.", messagePlan: { firstMessage: "Hello, this is Morgan from GrowthPartners. Do you have a few minutes to chat about how we might be able to help your business?" } }, { name: "need_discovery", type: "conversation", metadata: { position: { x: 400, y: 150 } }, prompt: "Conduct need discovery by asking about: 1) Their business and industry, 2) Current systems/processes they use, 3) Biggest challenges with current approach...", variableExtractionPlan: { output: [ { type: "string", title: "industry", description: "the user's industry or business type" }, { type: "string", title: "company_size", description: "approximate number of employees" } ] } } ], edges: [ { from: "introduction", to: "need_discovery" } ] }, { id: 'wf2', name: '售后退款流程', nodeCount: 5, createdAt: '2024-03-01 10:00', updatedAt: '2024-03-05 14:30', nodes: [], edges: [] }, ]; export const mockKnowledgeBases: KnowledgeBase[] = [ { id: 'kb1', name: 'Product Manuals', creator: 'Admin', createdAt: '2023-10-15', documents: [ { id: 'd1', name: 'User Guide v1.pdf', size: '2.4 MB', uploadDate: '2023-10-15' }, { id: 'd2', name: 'Warranty Info.docx', size: '1.1 MB', uploadDate: '2023-10-16' }, ], }, { id: 'kb2', name: 'Sales Scripts', creator: 'Sales Lead', createdAt: '2023-11-01', documents: [ { id: 'd3', name: 'Objection Handling.pdf', size: '500 KB', uploadDate: '2023-11-01' }, ], }, ]; export const mockCallLogs: CallLog[] = [ { id: 'c1', source: 'external', status: 'connected', startTime: '2023-11-20 10:30:00', duration: '5m 23s', agentName: 'Customer Support Bot', type: 'video', details: [ { role: 'user', content: 'Can you see this product?', imageUrls: ['https://images.unsplash.com/photo-1523275335684-37898b6baf30?w=150&h=150&fit=crop'], timestamp: '10:30:05' }, { role: 'assistant', content: 'Yes, I can see the white watch. It looks like a minimalist design.', timestamp: '10:30:08' }, { role: 'user', content: 'How much is it?', imageUrls: [], timestamp: '10:30:15' }, { role: 'assistant', content: 'Based on the database, this model retails for $199.', timestamp: '10:30:18' } ] }, { id: 'c2', source: 'debug', status: 'connected', startTime: '2023-11-20 11:15:00', duration: '1m 10s', agentName: 'Sales Agent', type: 'audio', details: [ { role: 'user', content: 'I am interested in the premium plan.', timestamp: '11:15:02' }, { role: 'assistant', content: 'That is a great choice. The premium plan includes...', timestamp: '11:15:05' } ] }, { id: 'c3', source: 'external', status: 'missed', startTime: '2023-11-20 12:00:00', duration: '0s', agentName: 'Customer Support Bot', type: 'text', details: [] }, { id: 'c4', source: 'debug', status: 'connected', startTime: '2023-11-21 09:30:00', duration: '45s', agentName: 'Refund Bot', type: 'text', details: [ { role: 'user', content: '我想申请退款', timestamp: '09:30:01' }, { role: 'assistant', content: '好的,请提供您的订单号。', timestamp: '09:30:02' }, { role: 'user', content: 'ORDER-2024-888', timestamp: '09:30:10' }, { role: 'assistant', content: '收到,正在为您处理...', timestamp: '09:30:12' } ] } ]; export const mockAutoTestAssistants: AutoTestAssistant[] = [ { id: 'at1', name: '退款流程压力测试', type: TestType.FIXED, method: TestMethod.TEXT, targetAssistantId: '1', fixedWorkflowSteps: ['你好,我要退款', '订单号是123456', '谢谢'], intelligentPrompt: '', createdAt: '2024-03-10 09:00' }, { id: 'at2', name: '愤怒的客户模拟', type: TestType.INTELLIGENT, method: TestMethod.AUDIO, targetAssistantId: '1', fixedWorkflowSteps: [], intelligentPrompt: '你是一个非常愤怒的客户,因为订单延迟了一周。你需要表达你的不满,并要求立即解决。你的语气必须很冲,不接受简单的道歉。', createdAt: '2024-03-11 14:20' } ]; export const mockTools: Tool[] = [ { id: 'cam_open', name: '打开相机', description: '允许 AI 开启摄像头流', category: 'system', icon: 'Camera' }, { id: 'cam_close', name: '关闭相机', description: '允许 AI 停止摄像头流', category: 'system', icon: 'CameraOff' }, { id: 'take_photo', name: '拍照', description: 'AI 触发单张拍摄', category: 'system', icon: 'Image' }, { id: 'burst_3', name: '连拍三张', description: 'AI 触发快速连拍', category: 'system', icon: 'Images' }, { id: 'q_weather', name: '天气查询', description: '查询实时及未来天气', category: 'query', icon: 'CloudSun' }, { id: 'q_calendar', name: '日历查询', description: '查询日程及节假日信息', category: 'query', icon: 'Calendar' }, { id: 'q_stock', name: '股价查询', description: '查询股票实时行情', category: 'query', icon: 'TrendingUp' }, { id: 'q_exchange', name: '汇率查询', description: '查询多国货币汇率', category: 'query', icon: 'Coins' }, { id: 'custom_1', name: '智能家居控制', description: '控制灯光、窗帘等设备', category: 'system', icon: 'Terminal', isCustom: true }, ]; export const mockLLMModels: LLMModel[] = [ { id: 'm1', name: 'GPT-4o', vendor: 'OpenAI Compatible', type: 'text', baseUrl: 'https://api.openai.com/v1', apiKey: 'sk-***', temperature: 0.7 }, { id: 'm2', name: 'DeepSeek-V3', vendor: 'OpenAI Compatible', type: 'text', baseUrl: 'https://api.deepseek.com', apiKey: 'sk-***', temperature: 0.5 }, { id: 'm3', name: 'text-embedding-3-small', vendor: 'OpenAI Compatible', type: 'embedding', baseUrl: 'https://api.openai.com/v1', apiKey: 'sk-***' }, ]; export const mockASRModels: ASRModel[] = [ { id: 'asr1', name: 'Whisper-1', vendor: 'OpenAI Compatible', language: 'Multi-lingual', baseUrl: 'https://api.openai.com/v1', apiKey: 'sk-***' }, { id: 'asr2', name: 'SenseVoiceSmall', vendor: 'OpenAI Compatible', language: 'zh', baseUrl: 'https://api.siliconflow.cn/v1', apiKey: 'sk-***' }, ]; export interface DashboardStats { totalCalls: number; answerRate: number; avgDuration: string; humanTransferCount: number; trend: { label: string; value: number }[]; } export const getDashboardStats = (timeRange: 'week' | 'month' | 'year', assistantId: string): DashboardStats => { const multiplier = assistantId === 'all' ? 1 : (assistantId === '1' ? 0.6 : 0.4); const rangeMultiplier = timeRange === 'week' ? 1 : (timeRange === 'month' ? 4 : 52); const baseCalls = Math.floor(100 * rangeMultiplier * multiplier); const transfers = Math.floor(baseCalls * 0.15); let points = 7; if (timeRange === 'month') points = 30; if (timeRange === 'year') points = 12; const trend = Array.from({ length: points }, (_, i) => { let label = `Day ${i + 1}`; if (timeRange === 'year') { const months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']; label = months[i]; } return { label, value: Math.floor(Math.random() * 50 * multiplier) + 10 }; }); return { totalCalls: baseCalls, answerRate: 85 + Math.floor(Math.random() * 10), avgDuration: `${Math.floor(2 + Math.random() * 3)}m ${Math.floor(Math.random() * 60)}s`, humanTransferCount: transfers, trend }; };