Azure AI 语音实时翻译 Python SDK

azure-ai-voicelive-py
分类编程
作者Agentic Awesome Skills 社区
许可MIT
评分4.90/5
使用12.5K

Azure AI Voice Live SDK

通过双向 WebSocket 通信构建实时语音 AI 应用。

安装

bash
pip install azure-ai-voicelive aiohttp azure-identity

环境变量

bash
AZURE_COGNITIVE_SERVICES_ENDPOINT=https://<region>.api.cognitive.microsoft.com

用于 API 密钥认证（生产环境不推荐）

AZURE_COGNITIVE_SERVICES_KEY=<api-key>

身份验证

DefaultAzureCredential (推荐):

python
from azure.ai.voicelive.aio import connect
from azure.identity.aio import DefaultAzureCredential


async with connect(
    endpoint=os.environ["AZURE_COGNITIVE_SERVICES_ENDPOINT"],
    credential=DefaultAzureCredential(),
    model="gpt-4o-realtime-preview",
    credential_scopes=["https://cognitiveservices.azure.com/.default"]
) as conn:
    ...

API 密钥:

python
from azure.ai.voicelive.aio import connect
from azure.core.credentials import AzureKeyCredential


async with connect(
    endpoint=os.environ["AZURE_COGNITIVE_SERVICES_ENDPOINT"],
    credential=AzureKeyCredential(os.environ["AZURE_COGNITIVE_SERVICES_KEY"]),
    model="gpt-4o-realtime-preview"
) as conn:
    ...

快速上手

python
import asyncio
import os
from azure.ai.voicelive.aio import connect
from azure.identity.aio import DefaultAzureCredential

async def main():
    async with connect(
        endpoint=os.environ["AZURE_COGNITIVE_SERVICES_ENDPOINT"],
        credential=DefaultAzureCredential(),
        model="gpt-4o-realtime-preview",
        credential_scopes=["https://cognitiveservices.azure.com/.default"]
    ) as conn:
        # 使用指令更新会话
        await conn.session.update(session={
            "instructions": "You are a helpful assistant.",
            "modalities": ["text", "audio"],
            "voice": "alloy"
        })
        
        # 监听事件
        async for event in conn:
            print(f"Event: {event.type}")
            if event.type == "response.audio_transcript.done":
                print(f"Transcript: {event.transcript}")
            elif event.type == "response.done":
                break


asyncio.run(main())

核心架构

连接资源

VoiceLiveConnection 提供了以下资源：

| 资源 | 用途 | 关键方法 |
|----------|---------|-------------|
| conn.session | 会话配置 | update(session=...) |
| conn.response | 模型响应 | create(), cancel() |
| conn.input_audio_buffer | 音频输入 | append(), commit(), clear() |
| conn.output_audio_buffer | 音频输出 | clear() |
| conn.conversation | 对话状态 | item.create(), item.delete(), item.truncate() |
| conn.transcription_session | 转录配置 | update(session=...) |

会话配置

python
from azure.ai.voicelive.models import RequestSession, FunctionTool

await conn.session.update(session=RequestSession(
    instructions="You are a helpful voice assistant.",
    modalities=["text", "audio"],
    voice="alloy",  # 或 "echo", "shimmer", "sage" 等
    input_audio_format="pcm16",
    output_audio_format="pcm16",
    turn_detection={
        "type": "server_vad",
        "threshold": 0.5,
        "prefix_padding_ms": 300,
        "silence_duration_ms": 500
    },
    tool
s=[
        FunctionTool(
            type="function",
            name="get_weather",
            description="Get current weather",
            parameters={
                "type": "object",
                "properties": {
                    "location": {"type": "string"}
                },
                "required": ["location"]
            }
        )
    ]
))

音频流

发送音频 (Base64 PCM16)

python
import base64

读取音频分片 (16-bit PCM, 24kHz 单声道)

audio_chunk = await read_audio_from_microphone()
b64_audio = base64.b64encode(audio_chunk).decode()

await conn.input_audio_buffer.append(audio=b64_audio)

接收音频

python
async for event in conn:
    if event.type == "response.audio.delta":
        audio_bytes = base64.b64decode(event.delta)
        await play_audio(audio_bytes)
    elif event.type == "response.audio.done":
        print("音频传输完成")

事件处理

python
async for event in conn:
    match event.type:
        # 会话事件
        case "session.created":
            print(f"会话: {event.session}")
        case "session.updated":
            print("会话已更新")
        
        # 音频输入事件
        case "input_audio_buffer.speech_started":
            print(f"语音开始于 {event.audio_start_ms}ms")
        case "input_audio_buffer.speech_stopped":
            print(f"语音结束于 {event.audio_end_ms}ms")
        
        # 转录事件
        case "conversation.item.input_audio_transcription.completed":
            print(f"用户说: {event.transcript}")
        case "conversation.item.input_audio_transcription.delta":
            print(f"部分转录: {event.delta}")
        
        # 响应事件
        case "response.created":
            print(f"响应开始: {event.response.id}")
        case "response.audio_transcript.delta":
            print(event.delta, end="", flush=True)
        case "response.audio.delta":
            audio = base64.b64decode(event.delta)
        case "response.done":
            print(f"响应完成: {event.response.status}")
        
        # 函数调用
        case "response.function_call_arguments.done":
            result = handle_function(event.name, event.arguments)
            await conn.conversation.item.create(item={
                "type": "function_call_output",
                "call_id": event.call_id,
                "output": json.dumps(result)
            })
            await conn.response.create()
        
        # 错误
        case "error":
            print(f"错误: {event.error.message}")

常见模式

手动轮替模式 (禁用 VAD)

python
await conn.session.update(session={"turn_detection": None})

手动控制轮替

await conn.input_audio_buffer.append(audio=b64_audio)
await conn.input_audio_buffer.commit()  # 结束用户轮替
await conn.response.create()  # 触发响应

中断处理

python
async for event in conn:
    if event.type == "input_audio_buffer.speech_started":
        # 用户中断 - 取消当前响应
        await conn.response.cancel()
        await conn.output_audio_buffer.clear()

对话历史

python
# 添加系统消息
await conn.conversation.item.create(item={
    "type": "message",
    "role": "system",
    "content": [{"type": "input_text", "text": "Be concise."}]
})

添加用户消息

await conn.conversation.item.create(item={
    "type": "message",
"role": "user", "content": [{"type": "input_text", "text": "Hello!"}] })

await conn.response.create()

code
## 语音选项


| 语音 | 描述 |
|-------|-------------|
| alloy | 中立，均衡 |
| echo | 温暖，对话感强 |
| shimmer | 清晰，专业 |
| sage | 冷静，权威 |
| coral | 友好，轻快 |
| ash | 深沉，稳重 |
| ballad | 富有表现力 |
| verse | 叙事感强 |


Azure 语音：请使用 AzureStandardVoice、AzureCustomVoice 或 AzurePersonalVoice 模型。


音频格式


| 格式 | 采样率 | 使用场景 |
|--------|-------------|----------|
| pcm16 | 24kHz | 默认，高质量 |
| pcm16-8000hz | 8kHz | 电话通信 |
| pcm16-16000hz | 16kHz | 语音助手 |
| g711_ulaw | 8kHz | 电话通信 (美国) |
| g711_alaw | 8kHz | 电话通信 (欧盟) |


话轮检测选项 (Turn Detection)
python

服务器端 VAD (默认)

{"type": "server_vad", "threshold": 0.5, "silence_duration_ms": 500}

Azure 语义 VAD (更智能的检测)

{"type": "azure_semantic_vad"} {"type": "azure_semantic_vad_en"} # 针对英语优化 {"type": "azure_semantic_vad_multilingual"}
code
## 错误处理
python from azure.ai.voicelive.aio import ConnectionError, ConnectionClosed

try:
async with connect(...) as conn:
async for event in conn:
if event.type == "error":
print(f"API Error: {event.error.code} - {event.error.message}")
except ConnectionClosed as e:
print(f"Connection closed: {e.code} - {e.reason}")
except ConnectionError as e:
print(f"Connection error: {e}")
```

参考资料

  • 详细 API 参考: 见 references/api-reference.md
  • 完整示例: 见 references/examples.md
  • 所有模型与类型: 见 references/models.md

使用场景

本技能适用于执行概览中所描述的工作流或操作。

局限性

  • 仅在任务明确符合上述范围时使用此技能。
  • 不要将输出结果视为特定环境验证、测试或专家评审的替代方案。
  • 如果缺少必要的输入、权限、安全边界或成功标准，请停止操作并请求澄清。