feat: daily podcast player (OpenAI TTS, 欣欣+建国 双主持)
This commit is contained in:
github-actions[bot]
@@ -0,0 +1,42 @@
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name: Daily Podcast Generation
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on:
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schedule:
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# 08:45 ET (12:45 UTC) — after daily update finishes
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- cron: '45 12 * * 1-5'
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workflow_dispatch:
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permissions:
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contents: write
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jobs:
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podcast:
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runs-on: ubuntu-latest
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env:
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ANTHROPIC_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
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ANTHROPIC_MODEL: ${{ vars.ANTHROPIC_MODEL || 'claude-sonnet-4-5' }}
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OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
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steps:
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- uses: actions/checkout@v4
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- uses: actions/setup-python@v5
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with:
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python-version: '3.11'
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- name: Install dependencies
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run: pip install anthropic openai
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- name: Install ffmpeg
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run: sudo apt-get install -y ffmpeg
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- name: Generate podcast
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run: python scripts/generate_podcast.py
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- name: Commit audio
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run: |
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git config user.name "github-actions[bot]"
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git config user.email "github-actions[bot]@users.noreply.github.com"
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git add audio/
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git diff --cached --quiet || git commit -m "podcast: daily audio $(date -u +'%Y-%m-%d')"
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git push
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+105
@@ -674,6 +674,111 @@
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</div>
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</section>
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<!-- PODCAST PLAYER -->
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<div class="podcast-bar" id="podcast-bar">
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<div class="container">
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<div class="podcast-inner">
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<div class="podcast-left">
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<span class="podcast-icon">🎙️</span>
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<div class="podcast-info">
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<div class="podcast-title">金融日报早报 · 今日播客</div>
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<div class="podcast-sub" id="podcast-date">欣欣 & 建国 · 约3分钟</div>
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</div>
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</div>
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<div class="podcast-controls">
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<audio id="podcast-audio" preload="none">
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<source src="audio/latest.mp3" type="audio/mpeg">
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</audio>
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<button class="pod-btn" id="pod-play" onclick="togglePodcast()">▶ 播放</button>
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<div class="pod-progress-wrap" onclick="seekPodcast(event)">
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<div class="pod-progress-bar" id="pod-progress"></div>
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</div>
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<span class="pod-time" id="pod-time">0:00</span>
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<button class="pod-btn pod-btn-sm" onclick="document.getElementById('podcast-audio').playbackRate=document.getElementById('podcast-audio').playbackRate===1?1.5:1;this.textContent=document.getElementById('podcast-audio').playbackRate+'x'">1x</button>
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<a class="pod-btn pod-btn-sm" href="audio/latest.mp3" download="金融日报早报.mp3" title="下载">⬇</a>
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</div>
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</div>
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</div>
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</div>
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<style>
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.podcast-bar {
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background: linear-gradient(90deg, rgba(0,212,170,.08), rgba(79,195,247,.05));
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border-bottom: 1px solid rgba(0,212,170,.2);
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padding: 10px 0;
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}
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.podcast-inner { display:flex; align-items:center; justify-content:space-between; gap:14px; flex-wrap:wrap; }
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.podcast-left { display:flex; align-items:center; gap:10px; }
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.podcast-icon { font-size:1.4rem; animation: pulse-pod 3s ease-in-out infinite; }
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@keyframes pulse-pod { 0%,100%{transform:scale(1)} 50%{transform:scale(1.1)} }
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.podcast-title { font-size:.82rem; font-weight:600; color:var(--text); }
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.podcast-sub { font-size:.65rem; color:var(--muted); font-family:var(--mono); margin-top:1px; }
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.podcast-controls { display:flex; align-items:center; gap:10px; flex-wrap:wrap; }
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.pod-btn {
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background: rgba(0,212,170,.15); color:var(--accent);
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border: 1px solid rgba(0,212,170,.3); border-radius:6px;
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padding: 5px 14px; font-size:.75rem; cursor:pointer;
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font-family:var(--sans); transition:background .15s; white-space:nowrap;
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}
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.pod-btn:hover { background:rgba(0,212,170,.25); }
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.pod-btn.playing { background:rgba(255,82,82,.12); color:var(--down); border-color:rgba(255,82,82,.3); }
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.pod-btn-sm { padding:5px 9px; font-size:.68rem; }
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.pod-btn-sm[download] { color:var(--muted); background:rgba(255,255,255,.05); border-color:var(--border); text-decoration:none; }
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.pod-progress-wrap { width:160px; height:4px; background:var(--border); border-radius:2px; cursor:pointer; }
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@media(max-width:640px){ .pod-progress-wrap { width:80px; } }
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.pod-progress-bar { height:100%; background:var(--accent); border-radius:2px; width:0%; transition:width .3s linear; }
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.pod-time { font-family:var(--mono); font-size:.65rem; color:var(--muted); min-width:32px; }
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</style>
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<script>
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(function(){
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var audio = document.getElementById('podcast-audio');
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var btn = document.getElementById('pod-play');
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var bar = document.getElementById('pod-progress');
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var time = document.getElementById('pod-time');
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if (!audio) return;
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// Check if audio exists
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fetch('audio/latest-meta.json').then(r=>r.json()).then(m=>{
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document.getElementById('podcast-date').textContent = '欣欣 & 建国 · ' + m.date + ' · 约3分钟';
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}).catch(()=>{
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document.getElementById('podcast-bar').style.opacity = '0.4';
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btn.textContent = '暂无音频';
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btn.disabled = true;
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});
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audio.addEventListener('timeupdate', function(){
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if (!audio.duration) return;
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bar.style.width = (audio.currentTime / audio.duration * 100) + '%';
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var m = Math.floor(audio.currentTime/60);
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var s = Math.floor(audio.currentTime%60);
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time.textContent = m + ':' + (s<10?'0':'')+s;
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});
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audio.addEventListener('ended', function(){
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btn.textContent = '▶ 播放';
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btn.classList.remove('playing');
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bar.style.width = '0%';
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});
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window.togglePodcast = function(){
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if (audio.paused) {
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audio.play();
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btn.textContent = '⏸ 暂停';
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btn.classList.add('playing');
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} else {
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audio.pause();
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btn.textContent = '▶ 播放';
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btn.classList.remove('playing');
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}
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};
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window.seekPodcast = function(e){
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if (!audio.duration) return;
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var rect = e.currentTarget.getBoundingClientRect();
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audio.currentTime = ((e.clientX - rect.left) / rect.width) * audio.duration;
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};
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})();
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</script>
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<!-- MAIN PAGE BODY -->
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<div class="page-body">
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<div class="container">
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@@ -0,0 +1,248 @@
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#!/usr/bin/env python3
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"""
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金融日报 — Daily Podcast Generator
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每天用 Claude 生成播客脚本，OpenAI TTS 合成双主持人音频
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"""
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import os, sys, json, datetime, subprocess, tempfile, shutil
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from pathlib import Path
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import anthropic
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from openai import OpenAI
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ROOT = Path(__file__).resolve().parent.parent
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DATA = ROOT / "data"
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AUDIO = ROOT / "audio"
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AUDIO.mkdir(exist_ok=True)
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CLAUDE_MODEL = os.environ.get("ANTHROPIC_MODEL", "claude-sonnet-4-5")
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# Host voices: alloy=女主持, echo=男主持
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VOICE_A = "shimmer" # 女主持（活泼）
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VOICE_B = "echo" # 男主持（沉稳）
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MAX_SCRIPT_TOKENS = 2000 # 控制音频时长约 3-4 分钟
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SCRIPT_SYSTEM = """你是一档面向北美华人投资者的金融播客节目的编剧。
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节目名：《金融日报早报》，双主持人对话风格。
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主持人设定：
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- 甲（欣欣）：女性，活泼、亲切，善于把复杂数据说成大白话，偶尔幽默
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- 乙（建国）：男性，沉稳、专业，擅长宏观分析，会在关键处泼冷水
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规则：
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1. 输出纯文本，格式严格为：每行以 [欣欣] 或 [建国] 开头
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2. 总长度控制在 600-800 字，约 3-4 分钟播放
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3. 开头10秒必须抓住注意力（重大结论或反常现象）
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4. 覆盖：今日大势、1-2条核心新闻、1个AI推荐标的、结尾一句行动建议
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5. 说话自然、口语化，不念数字时不念小数点后太多位
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6. 结尾固定：欣欣说"我是欣欣"，建国说"我是建国"，一起说"我们明天见"
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"""
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def load_today_data() -> dict:
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"""Load today's market data JSON"""
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today = datetime.datetime.now().strftime("%Y-%m-%d")
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path = DATA / f"{today}.json"
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if not path.exists():
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path = DATA / "latest.json"
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if not path.exists():
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print("❌ No data file found")
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sys.exit(1)
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with open(path, encoding="utf-8") as f:
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return json.load(f)
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def build_context(data: dict) -> str:
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"""Summarize market data into a compact context for script generation"""
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lines = []
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# Date
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lines.append(f"日期：{data.get('date', '今日')}")
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# Summary
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s = data.get("summary", {})
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if s:
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lines.append(f"\n今日大势：{s.get('headline','')}（{s.get('sentiment','')}，VIX {s.get('vix','')}）")
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kp = s.get("key_points", [])
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if kp:
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lines.append("关键点：" + " / ".join(kp[:3]))
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# Top indices
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indices = data.get("indices", [])[:6]
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if indices:
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lines.append("\n主要指数：")
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for i in indices:
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lines.append(f" {i['name']} {i['value']} {i.get('change_pct','')}")
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# Top 3 news
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news = data.get("news", [])[:4]
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if news:
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lines.append("\n重大新闻：")
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for n in news:
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lines.append(f" [{n.get('importance','').upper()}] {n['title']}")
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if n.get("tldr"):
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lines.append(f" → {n['tldr']}")
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# AI watchlist top pick
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wl = data.get("watchlist_analysis", [])
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if wl:
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# Find BUY with highest score
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buys = [x for x in wl if x.get("signal") == "BUY"]
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top = sorted(buys, key=lambda x: x.get("score", 0), reverse=True)[:1] or wl[:1]
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if top:
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t = top[0]
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lines.append(f"\nAI今日推荐：{t['name']}({t['ticker']}) 信号:{t.get('signal','')} 评分:{t.get('score','')} — {t.get('conclusion','')}")
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lines.append(f" 目标位: ↑{t.get('target_up','')} ↓{t.get('target_down','')} 风险:{t.get('risk_level','')}")
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# Market debate verdict
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debate = data.get("market_debate", {})
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if debate:
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lines.append(f"\n多空裁判：{debate.get('verdict_lean','').upper()} — {debate.get('verdict','')}")
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# 1 macro indicator
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macro = data.get("macro", [])[:2]
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if macro:
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lines.append("\n宏观数据：")
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for m in macro:
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lines.append(f" {m['indicator']} {m['value']}（前值{m.get('prev','')}）{m.get('description','')[:40]}")
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return "\n".join(lines)
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def generate_script(context: str, client_claude) -> str:
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"""Use Claude to write the podcast script"""
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print("📝 Generating podcast script with Claude...")
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resp = client_claude.messages.create(
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model=CLAUDE_MODEL,
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max_tokens=MAX_SCRIPT_TOKENS,
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system=SCRIPT_SYSTEM,
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messages=[{
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"role": "user",
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"content": f"请根据以下今日市场数据，生成今天的《金融日报早报》播客脚本：\n\n{context}"
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}]
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)
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script = resp.content[0].text.strip()
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print(f" ✅ Script: {len(script)} chars")
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return script
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def parse_script(script: str) -> list[tuple[str, str]]:
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"""Parse [欣欣] / [建国] lines → [(speaker, text), ...]"""
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segments = []
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for line in script.split("\n"):
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line = line.strip()
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if not line:
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continue
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if line.startswith("[欣欣]"):
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segments.append(("A", line[4:].strip()))
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elif line.startswith("[建国]"):
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segments.append(("B", line[4:].strip()))
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return segments
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def synthesize_segment(text: str, voice: str, client_oai, outpath: Path):
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"""Synthesize one TTS segment"""
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resp = client_oai.audio.speech.create(
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model="tts-1",
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voice=voice,
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input=text,
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response_format="mp3",
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speed=1.05,
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)
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resp.stream_to_file(outpath)
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def merge_audio(segment_files: list[Path], output: Path):
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"""Concatenate MP3 files using ffmpeg"""
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if not shutil.which("ffmpeg"):
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# Fallback: just copy first segment
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shutil.copy(segment_files[0], output)
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print(" ⚠️ ffmpeg not found, using first segment only")
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return
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# Create concat list
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with tempfile.NamedTemporaryFile("w", suffix=".txt", delete=False) as f:
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for seg in segment_files:
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f.write(f"file '{seg.resolve()}'\n")
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list_file = f.name
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subprocess.run(
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["ffmpeg", "-y", "-f", "concat", "-safe", "0", "-i", list_file,
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"-c", "copy", str(output)],
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check=True, capture_output=True
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)
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os.unlink(list_file)
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def main():
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print("=" * 60)
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print("🎙️ 金融日报 — Podcast Generator")
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print("=" * 60)
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# API clients
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anthropic_key = os.environ.get("ANTHROPIC_API_KEY")
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openai_key = os.environ.get("OPENAI_API_KEY")
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if not anthropic_key:
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print("❌ ANTHROPIC_API_KEY not set"); sys.exit(1)
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if not openai_key:
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print("❌ OPENAI_API_KEY not set"); sys.exit(1)
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claude = anthropic.Anthropic(api_key=anthropic_key)
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oai = OpenAI(api_key=openai_key)
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# Load data
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data = load_today_data()
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context = build_context(data)
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print(f"📊 Loaded market data: {data.get('date','')}")
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# Generate script
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script = generate_script(context, claude)
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segments = parse_script(script)
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print(f" 🎬 {len(segments)} dialogue segments")
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if not segments:
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print("❌ No dialogue segments parsed"); sys.exit(1)
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# Save script
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today = datetime.datetime.now().strftime("%Y-%m-%d")
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script_path = AUDIO / f"{today}-script.txt"
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script_path.write_text(script, encoding="utf-8")
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print(f" 💾 Script saved: audio/{today}-script.txt")
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# TTS synthesis
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print("\n🔊 Synthesizing audio...")
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tmpdir = Path(tempfile.mkdtemp())
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seg_files = []
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for i, (speaker, text) in enumerate(segments):
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if not text: continue
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voice = VOICE_A if speaker == "A" else VOICE_B
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outf = tmpdir / f"seg_{i:03d}.mp3"
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print(f" [{i+1}/{len(segments)}] {'欣欣' if speaker=='A' else '建国'}: {text[:40]}...")
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synthesize_segment(text, voice, oai, outf)
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seg_files.append(outf)
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# Merge
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print("\n🔀 Merging audio segments...")
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final_mp3 = AUDIO / f"{today}.mp3"
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latest_mp3 = AUDIO / "latest.mp3"
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merge_audio(seg_files, final_mp3)
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shutil.copy(final_mp3, latest_mp3)
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shutil.rmtree(tmpdir)
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size_kb = final_mp3.stat().st_size // 1024
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print(f" ✅ Audio: audio/{today}.mp3 ({size_kb} KB)")
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# Save metadata
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meta = {
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"date": today,
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"script_chars": len(script),
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"segments": len(segments),
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"audio_kb": size_kb,
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"generated_at": datetime.datetime.utcnow().isoformat() + "Z"
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}
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(AUDIO / "latest-meta.json").write_text(json.dumps(meta, ensure_ascii=False, indent=2))
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print(f"\n🎉 Done! Podcast ready: audio/{today}.mp3")
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print("=" * 60)
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if __name__ == "__main__":
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||||
main()
|
||||
Reference in New Issue
Block a user