18307996893
/
tihao-ai


			
				
					
						
						
							123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213
							import { createServer, IncomingMessage, ServerResponse } from 'node:http';

type JsonValue = Record<string, unknown> | Array<unknown>;

interface Candidate {
  platform: string;
  name: string;
  fans: string;
  price: number;
  score: number;
  styleMatch: number;
  status: string;
  reason: string;
  risk: string;
}

const port = Number(process.env.TIHAO_AI_API_PORT ?? 4300);

const demoRequirements = [
  { label: '客户/品牌', value: '客户A / 新锐护肤品牌', confidence: 96 },
  { label: '投放目标', value: '新品种草、真实测评、站内转化蓄水', confidence: 92 },
  { label: '平台需求', value: '小红书 20人、抖音 8人、B站 4人', confidence: 90 },
  { label: '内容风格', value: '真实体验、通勤生活、轻专业成分党', confidence: 88 }
];

const demoRules = [
  '按 Brief 平台优先提号',
  '默认推荐数量不少于需求 3 倍',
  '风格匹配低于 80% 自动降级',
  '黑名单与低配合度剔除',
  '优先近期采集有效价格'
];

const demoCandidates: Candidate[] = [
  {
    platform: '小红书',
    name: '梨涡测评室',
    fans: '18.6万',
    price: 6800,
    score: 94,
    styleMatch: 91,
    status: '强推荐',
    reason: '近10篇中 9 篇为真实体验或成分拆解，互动中位数高于同价位账号 28%。',
    risk: '视频内容偏少，可作为图文主推。'
  },
  {
    platform: '抖音',
    name: '林小林认真护肤',
    fans: '42.1万',
    price: 12800,
    score: 87,
    styleMatch: 82,
    status: '备选',
    reason: '爆文率和完播率表现稳定，预算接近上限，建议作为抖音头部备选。',
    risk: '单条报价较高，需确认档期。'
  }
];

function sendJson(response: ServerResponse, statusCode: number, payload: JsonValue): void {
  const body = JSON.stringify(payload);
  response.writeHead(statusCode, {
    'Access-Control-Allow-Origin': '*',
    'Access-Control-Allow-Headers': 'Content-Type',
    'Access-Control-Allow-Methods': 'GET,POST,OPTIONS',
    'Content-Type': 'application/json; charset=utf-8',
    'Content-Length': Buffer.byteLength(body)
  });
  response.end(body);
}

function sendExcel(response: ServerResponse, filename: string, candidates: Candidate[]): void {
  const rows = candidates
    .map(
      (candidate) => `
        <tr>
          <td>${escapeHtml(candidate.platform)}</td>
          <td>${escapeHtml(candidate.name)}</td>
          <td>${escapeHtml(candidate.fans)}</td>
          <td>${candidate.price}</td>
          <td>${candidate.score}</td>
          <td>${candidate.styleMatch}%</td>
          <td>${escapeHtml(candidate.status)}</td>
          <td>${escapeHtml(candidate.reason)}</td>
          <td>${escapeHtml(candidate.risk)}</td>
        </tr>`
    )
    .join('');

  const body = `
    <html>
      <head>
        <meta charset="UTF-8">
        <style>
          table { border-collapse: collapse; font-family: "Microsoft YaHei", Arial, sans-serif; }
          th { background: #1f8a70; color: #fff; }
          th, td { border: 1px solid #cfd7d1; padding: 8px 10px; }
          td:nth-child(5), td:nth-child(6) { background: #eef7f3; font-weight: 700; }
        </style>
      </head>
      <body>
        <table>
          <tr>
            <th>平台</th><th>账号</th><th>粉丝量</th><th>报价</th><th>综合分</th><th>风格匹配</th><th>推荐状态</th><th>推荐理由</th><th>风险提示</th>
          </tr>
          ${rows}
        </table>
      </body>
    </html>`;

  response.writeHead(200, {
    'Access-Control-Allow-Origin': '*',
    'Content-Type': 'application/vnd.ms-excel; charset=utf-8',
    'Content-Disposition': `attachment; filename="${encodeURIComponent(filename)}"`,
    'Content-Length': Buffer.byteLength(body)
  });
  response.end(body);
}

function readBody(request: IncomingMessage): Promise<Record<string, unknown>> {
  return new Promise((resolve) => {
    let body = '';
    request.on('data', (chunk) => {
      body += chunk;
    });
    request.on('end', () => {
      if (!body) {
        resolve({});
        return;
      }

      try {
        resolve(JSON.parse(body));
      } catch {
        resolve({});
      }
    });
  });
}

function escapeHtml(value: string): string {
  return value
    .replaceAll('&', '&amp;')
    .replaceAll('<', '&lt;')
    .replaceAll('>', '&gt;')
    .replaceAll('"', '&quot;');
}

const server = createServer(async (request, response) => {
  const requestUrl = new URL(request.url ?? '/', `http://${request.headers.host ?? 'localhost'}`);

  if (request.method === 'OPTIONS') {
    sendJson(response, 200, { ok: true });
    return;
  }

  if (request.method === 'GET' && requestUrl.pathname === '/api/health') {
    sendJson(response, 200, {
      ok: true,
      name: '提号AI Mock API',
      resourcesPath: 'D:\\公司优秀媒体资源库\\4月份资源库'
    });
    return;
  }

  if (request.method === 'POST' && requestUrl.pathname === '/api/analyze-brief') {
    sendJson(response, 200, {
      requirements: demoRequirements,
      rules: demoRules,
      message: 'Demo 已模拟解析 Brief，真实环境会接入 Excel/Docx 解析与 LLM 抽取。'
    });
    return;
  }

  if (request.method === 'POST' && requestUrl.pathname === '/api/recommend') {
    sendJson(response, 200, {
      candidates: demoCandidates,
      totalPool: 104,
      message: 'Demo 已模拟按规则生成推荐池。'
    });
    return;
  }

  if (request.method === 'POST' && requestUrl.pathname === '/api/rules/learn') {
    sendJson(response, 200, {
      suggestions: [
        {
          title: '小红书减少泛美妆号，优先生活方式和通勤场景',
          confidence: 93
        },
        {
          title: '抖音预算压低时保留爆文率高账号',
          confidence: 87
        }
      ]
    });
    return;
  }

  if (request.method === 'POST' && requestUrl.pathname === '/api/recommendations/export') {
    const body = await readBody(request);
    const candidates = Array.isArray(body['candidates'])
      ? (body['candidates'] as Candidate[])
      : demoCandidates;
    sendExcel(response, '客户A-新锐护肤品牌-需求推荐名单.xls', candidates);
    return;
  }

  sendJson(response, 404, { ok: false, message: 'Not found' });
});

server.listen(port, () => {
  console.log(`Tihao AI mock API listening on http://localhost:${port}`);
});