第三方服务集成方案

{ "config": { "encoding": "LINEAR16", "sample_rate_hertz": 16000, "language_code": "zh-CN", "model": "latest_long", "use_enhanced": true, "enable_automatic_punctuation": true, "enable_speaker_diarization": false, "profanity_filter": false, "max_alternatives": 1, "streaming": { "interim_results": true, "single_utterance": false } } }

# Phase 1 末期（DAU 20 万，人均 10 次通话，每次 50 句） daily_chars = 200000 * 10 * 50 * 20 # 用户 * 次数 * 句数 * 平均字符 = 2,000,000,000 字符/天 # 缓存命中 35% → 实际调用 65% actual_chars = 2B * 0.65 = 1.3B 字符/天 # 成本 daily_cost = 1.3B / 1M * $20 = $26,000/天 ❌ 太贵！ # 优化：短句合并 + 缓存优化 + 批量 # 实际：每句平均 15 字符（短句多） daily_chars_real = 200000 * 10 * 50 * 15 = 1.5B actual_chars = 1.5B * 0.65 = 975M daily_cost = 975M / 1M * $20 = $19,500/天 ❌ 仍然太贵 # 结论：必须做激进缓存 + 短句过滤 # 最终方案：缓存命中 60% + 只翻译 > 3 字符的句子 # → 实际成本 ~$5,000/天 → $150,000/月 → 仍然贵 # # ⚠️ 重要发现：Google Translate 按字符计费在高频场景下极贵 # 解决方案：Phase 1 使用 Google Translate，Phase 2 起逐步替换自研

<speak version="1.0" xmlns="http://www.w3.org/2001/10/synthesis" xml:lang="en-US"> <voice name="en-US-JennyMultilingualNeural"> <prosody rate="-10%" pitch="+0Hz"> I want to eat hotpot today. </prosody> </voice> </speak>

// 1. 前端：创建 PaymentIntent POST /v1/payment/charge { "package_id": "pkg_1200", "channel": "stripe", "amount_sgd": 9.99 } // 2. 后端 → Stripe：创建 PaymentIntent stripe.payment_intents.create({ amount: 999, // 分 currency: "sgd", payment_method_types: ["card"], metadata: { order_id: "ord_xxx", user_id: "usr_xxx" } }) // 3. 返回 client_secret → 前端 Stripe SDK 确认支付 // 4. Stripe Webhook → 后端确认 → 发放金币

# Priority chain ASR_PROVIDERS = [ ("google", "zh-CN", latency=200ms, cost=$0.024/min), ("azure", "en-US", latency=250ms, cost=$0.017/min), ("google", "en-US", latency=220ms, cost=$0.024/min), # fallback ] def get_asr_provider(lang, exclude=None): for name, supported_lang, *_ in ASR_PROVIDERS: if lang == supported_lang and name != exclude: return name raise NoASRAvailableError()