const OpenAI = require('openai');
const fs = require('fs');

const openai = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY
});

async function transcribeAudio(filePath) {
  const transcription = await openai.audio.transcriptions.create({
    file: fs.createReadStream(filePath),
    model: "whisper-1",
    language: "ja", // 日本語を指定
    response_format: "verbose_json", // タイムスタンプ付き
    timestamp_granularities: ["segment"]
  });

  return transcription;
}

// 使用例
const result = await transcribeAudio('meeting.mp3');
console.log(result.text); // 全文テキスト
console.log(result.segments); // タイムスタンプ付きセグメント

const Anthropic = require('@anthropic-ai/sdk');

const anthropic = new Anthropic({
  apiKey: process.env.ANTHROPIC_API_KEY
});

async function analyzeTranscript(transcript) {
  const message = await anthropic.messages.create({
    model: "claude-sonnet-4-20250514",
    max_tokens: 4000,
    messages: [{
      role: "user",
      content: `以下は会議の文字起こしです。以下の形式でJSON形式で分析してください：

{
  "summary": "会議の要約（3-5文）",
  "action_items": [
    {
      "task": "タスク内容",
      "assignee": "担当者名",
      "deadline": "期限",
      "priority": "高/中/低"
    }
  ],
  "categories": ["カテゴリ1", "カテゴリ2"],
  "key_decisions": ["決定事項1", "決定事項2"],
  "next_steps": ["次のステップ1", "次のステップ2"]
}

文字起こし：
${transcript}`
    }]
  });

  return JSON.parse(message.content[0].text);
}

async function identifySpeakers(transcript, participants) {
  const prompt = `以下の会議文字起こしを、参加者ごとに分割してください。
  
参加者: ${participants.join(', ')}

文字起こし:
${transcript}

出力形式:
[
  {
    "speaker": "佐藤",
    "timestamp": "00:00:15",
    "text": "発言内容"
  }
]`;

  const message = await anthropic.messages.create({
    model: "claude-sonnet-4-20250514",
    max_tokens: 8000,
    messages: [{ role: "user", content: prompt }]
  });

  return JSON.parse(message.content[0].text);
}

const WebSocket = require('ws');
const speech = require('@google-cloud/speech');

const wss = new WebSocket.Server({ port: 8080 });
const client = new speech.SpeechClient();

wss.on('connection', (ws) => {
  const request = {
    config: {
      encoding: 'LINEAR16',
      sampleRateHertz: 16000,
      languageCode: 'ja-JP',
    },
    interimResults: true
  };

  const recognizeStream = client
    .streamingRecognize(request)
    .on('data', (data) => {
      const transcript = data.results[0]?.alternatives[0]?.transcript;
      if (transcript) {
        // クライアントに文字起こし結果を送信
        ws.send(JSON.stringify({
          type: 'transcript',
          text: transcript,
          isFinal: data.results[0]?.isFinal
        }));
      }
    });

  ws.on('message', (audioData) => {
    // マイクからの音声データをストリームに送信
    recognizeStream.write(audioData);
  });
});

import { useState } from 'react';
import { useDropzone } from 'react-dropzone';

function MeetingAnalyzer() {
  const [status, setStatus] = useState('idle');
  const [result, setResult] = useState(null);

  const onDrop = async (files) => {
    const formData = new FormData();
    formData.append('audio', files[0]);
    
    setStatus('transcribing');
    
    // 音声ファイルをアップロードして処理開始
    const res = await fetch('/api/analyze', {
      method: 'POST',
      body: formData
    });
    
    const data = await res.json();
    
    // WebSocketで進捗を監視
    const ws = new WebSocket(`ws://localhost:8080/progress/${data.jobId}`);
    
    ws.onmessage = (event) => {
      const update = JSON.parse(event.data);
      
      if (update.stage === 'analyzing') {
        setStatus('analyzing');
      } else if (update.stage === 'complete') {
        setResult(update.result);
        setStatus('complete');
      }
    };
  };

  const { getRootProps, getInputProps } = useDropzone({ onDrop });

  return (
    <div>
      <div {...getRootProps()}>
        <input {...getInputProps()} />
        <p>音声ファイルをドロップ</p>
      </div>
      
      {status === 'transcribing' && <p>文字起こし中...</p>}
      {status === 'analyzing' && <p>AI分析中...</p>}
      
      {result && (
        <div>
          <h3>{result.summary}</h3>
          <ul>
            {result.action_items.map((item, i) => (
              <li key={i}>{item.task} - {item.assignee}</li>
            ))}
          </ul>
        </div>
      )}
    </div>
  );
}

// pages/api/analyze.js
import OpenAI from 'openai';
import Anthropic from '@anthropic-ai/sdk';

export default async function handler(req, res) {
  const { audioFile } = req.body;
  
  // Step 1: 音声認識
  const openai = new OpenAI();
  const transcript = await openai.audio.transcriptions.create({
    file: audioFile,
    model: "whisper-1"
  });
  
  // Step 2: AI分析
  const anthropic = new Anthropic();
  const analysis = await anthropic.messages.create({
    model: "claude-sonnet-4-20250514",
    max_tokens: 4000,
    messages: [{
      role: "user",
      content: `以下の会議テキストを分析し、要約とアクションアイテムをJSON形式で返してください：
      
${transcript.text}`
    }]
  });
  
  res.json(JSON.parse(analysis.content[0].text));
}