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import { ChatGPTClient } from "@waylaidwanderer/chatgpt-api";
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const client = new ChatGPTClient("OPENAI_API_KEY", {
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  modelOptions: {
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    model: "gpt-4",
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    temperature: 0.8,
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    max_tokens: 2048,
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  },
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});
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const response = await client.sendMessage("你好，请介绍一下自己");

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你是一个名为「小芯」的虚拟主播，性格活泼可爱，喜欢二次元文化。
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说话风格要轻松幽默，适当使用颜文字和表情符号。
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你正在直播，要与弹幕观众互动。
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记住以下设定：
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- 年龄：永远18岁
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- 喜好：动漫、游戏、奶茶
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- 口头禅：「喵～」「好耶！」

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import aiohttp
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async def synthesize_speech(text: str) -> bytes:
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    """调用 TTS 服务合成语音"""
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    async with aiohttp.ClientSession() as session:
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        async with session.post(
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            'http://localhost:8080/api/tts',
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            json={
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                'text': text,
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                'voice': 'zh-CN-XiaoxiaoNeural',
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                'rate': '+0%',
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                'pitch': '+0Hz'
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            }
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        ) as response:
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            return await response.read()

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<speak version="1.0" xmlns="http://www.w3.org/2001/10/synthesis" xml:lang="zh-CN">
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  <voice name="zh-CN-XiaoxiaoNeural">
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    <prosody rate="1.1" pitch="+5%">
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      大家好，欢迎来到我的直播间！
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    </prosody>
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    <break time="300ms"/>
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    <prosody rate="0.9">
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      今天我们来聊聊编程那些事儿～
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    </prosody>
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  </voice>
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</speak>

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interface Live2DParams {
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  mouthOpenY: number; // 嘴巴开合度 [0, 1]
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  eyeOpenL: number; // 左眼开度 [0, 1]
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  eyeOpenR: number; // 右眼开度 [0, 1]
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  angleX: number; // 头部左右转动 [-30, 30]
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  angleY: number; // 头部上下转动 [-30, 30]
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  bodyAngleX: number; // 身体转动
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}
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function driveLive2D(audioData: Float32Array): Live2DParams {
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  const volume = calculateVolume(audioData);
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  const mouthOpenY = smoothVolumeToMouth(volume);
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  return {
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    mouthOpenY,
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    eyeOpenL: 1.0,
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    eyeOpenR: 1.0,
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    angleX: Math.sin(Date.now() / 1000) * 5,
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    angleY: 0,
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    bodyAngleX: Math.sin(Date.now() / 2000) * 3,
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  };
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}

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from transformers import pipeline
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classifier = pipeline("text-classification",
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                       model="lxyuan/distilbert-base-multilingual-cased-sentiments-student")
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def analyze_emotion(text: str) -> str:
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    """分析文本情感，返回表情标签"""
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    result = classifier(text)[0]
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    emotion_map = {
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        'positive': 'happy',
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        'negative': 'sad',
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        'neutral': 'neutral'
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    }
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    return emotion_map.get(result['label'], 'neutral')

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import asyncio
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from collections import deque
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class DanmakuProcessor:
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    def __init__(self, max_queue_size: int = 50):
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        self.danmaku_queue = deque(maxlen=max_queue_size)
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        self.seen_users = set()
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    async def add_danmaku(self, user: str, content: str):
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        """添加弹幕到处理队列"""
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        # 去重过滤
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        if user in self.seen_users:
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            return
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        self.seen_users.add(user)
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        # 过滤敏感内容
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        if self._contains_sensitive(content):
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            return
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        self.danmaku_queue.append({
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            'user': user,
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            'content': content,
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            'timestamp': time.time()
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        })
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    async def get_batch(self, window_seconds: int = 5) -> list:
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        """获取时间窗口内的弹幕批次"""
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        now = time.time()
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        return [
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            d for d in self.danmaku_queue
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            if now - d['timestamp'] < window_seconds
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        ]