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# 快速入门

## 先决条件

请确保你已按照 Agents SDK 的基础[快速入门说明](../quickstart.md)进行操作，并设置好虚拟环境。然后，从 SDK 安装可选的语音依赖：

```bash
pip install 'openai-agents[voice]'
```

## 概念

需要了解的主要概念是一个 [`VoicePipeline`][agents.voice.pipeline.VoicePipeline]，这是一个三步流程：

1. 运行语音转文本模型，将音频转为文本。
2. 运行你的代码（通常是一个智能体式工作流），以生成结果。
3. 运行文本转语音模型，将结果文本转换回音频。

```mermaid
graph LR
    %% Input
    A["🎤 Audio Input"]

    %% Voice Pipeline
    subgraph Voice_Pipeline [Voice Pipeline]
        direction TB
        B["Transcribe (speech-to-text)"]
        C["Your Code"]:::highlight
        D["Text-to-speech"]
        B --> C --> D
    end

    %% Output
    E["🎧 Audio Output"]

    %% Flow
    A --> Voice_Pipeline
    Voice_Pipeline --> E

    %% Custom styling
    classDef highlight fill:#ffcc66,stroke:#333,stroke-width:1px,font-weight:700;

```

## 智能体

首先，让我们设置一些智能体。如果你曾使用此 SDK 构建过智能体，这部分会很熟悉。我们将有几个智能体、一次任务转移，以及一个工具。

```python
import asyncio
import random

from agents import (
    Agent,
    function_tool,
)
from agents.extensions.handoff_prompt import prompt_with_handoff_instructions



@function_tool
def get_weather(city: str) -> str:
    """Get the weather for a given city."""
    print(f"[debug] get_weather called with city: {city}")
    choices = ["sunny", "cloudy", "rainy", "snowy"]
    return f"The weather in {city} is {random.choice(choices)}."


spanish_agent = Agent(
    name="Spanish",
    handoff_description="A spanish speaking agent.",
    instructions=prompt_with_handoff_instructions(
        "You're speaking to a human, so be polite and concise. Speak in Spanish.",
    ),
    model="gpt-5.2",
)

agent = Agent(
    name="Assistant",
    instructions=prompt_with_handoff_instructions(
        "You're speaking to a human, so be polite and concise. If the user speaks in Spanish, handoff to the spanish agent.",
    ),
    model="gpt-5.2",
    handoffs=[spanish_agent],
    tools=[get_weather],
)
```

## 语音管道

我们将设置一个简单的语音管道，使用 [`SingleAgentVoiceWorkflow`][agents.voice.workflow.SingleAgentVoiceWorkflow] 作为工作流。

```python
from agents.voice import SingleAgentVoiceWorkflow, VoicePipeline
pipeline = VoicePipeline(workflow=SingleAgentVoiceWorkflow(agent))
```

## 管道运行

```python
import numpy as np
import sounddevice as sd
from agents.voice import AudioInput

# For simplicity, we'll just create 3 seconds of silence
# In reality, you'd get microphone data
buffer = np.zeros(24000 * 3, dtype=np.int16)
audio_input = AudioInput(buffer=buffer)

result = await pipeline.run(audio_input)

# Create an audio player using `sounddevice`
player = sd.OutputStream(samplerate=24000, channels=1, dtype=np.int16)
player.start()

# Play the audio stream as it comes in
async for event in result.stream():
    if event.type == "voice_stream_event_audio":
        player.write(event.data)

```

## 完整示例

```python
import asyncio
import random

import numpy as np
import sounddevice as sd

from agents import (
    Agent,
    function_tool,
    set_tracing_disabled,
)
from agents.voice import (
    AudioInput,
    SingleAgentVoiceWorkflow,
    VoicePipeline,
)
from agents.extensions.handoff_prompt import prompt_with_handoff_instructions


@function_tool
def get_weather(city: str) -> str:
    """Get the weather for a given city."""
    print(f"[debug] get_weather called with city: {city}")
    choices = ["sunny", "cloudy", "rainy", "snowy"]
    return f"The weather in {city} is {random.choice(choices)}."


spanish_agent = Agent(
    name="Spanish",
    handoff_description="A spanish speaking agent.",
    instructions=prompt_with_handoff_instructions(
        "You're speaking to a human, so be polite and concise. Speak in Spanish.",
    ),
    model="gpt-5.2",
)

agent = Agent(
    name="Assistant",
    instructions=prompt_with_handoff_instructions(
        "You're speaking to a human, so be polite and concise. If the user speaks in Spanish, handoff to the spanish agent.",
    ),
    model="gpt-5.2",
    handoffs=[spanish_agent],
    tools=[get_weather],
)


async def main():
    pipeline = VoicePipeline(workflow=SingleAgentVoiceWorkflow(agent))
    buffer = np.zeros(24000 * 3, dtype=np.int16)
    audio_input = AudioInput(buffer=buffer)

    result = await pipeline.run(audio_input)

    # Create an audio player using `sounddevice`
    player = sd.OutputStream(samplerate=24000, channels=1, dtype=np.int16)
    player.start()

    # Play the audio stream as it comes in
    async for event in result.stream():
        if event.type == "voice_stream_event_audio":
            player.write(event.data)


if __name__ == "__main__":
    asyncio.run(main())
```

如果你运行此示例，智能体会和你对话！查看 [examples/voice/static](https://github.com/openai/openai-agents-python/tree/main/examples/voice/static) 中的示例，体验一个你可以亲自与智能体对话的演示。