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+# Quickstart
+
+## Prerequisites
+
+Make sure you've followed the base [quickstart instructions](../quickstart.md) for the Agents SDK, and set up a virtual environment. Then, install the optional voice dependencies from the SDK:
+
+```bash
+pip install 'openai-agents[voice]'
+```
+
+## Concepts
+
+The main concept to know about is a [`VoicePipeline`][agents.voice.pipeline.VoicePipeline], which is a 3 step process:
+
+1. Run a speech-to-text model to turn audio into text.
+2. Run your code, which is usually an agentic workflow, to produce a result.
+3. Run a text-to-speech model to turn the result text back into audio.
+
+```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;
+
+```
+
+## Agents
+
+First, let's set up some Agents. This should feel familiar to you if you've built any agents with this SDK. We'll have a couple of Agents, a handoff, and a tool.
+
+```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-5.6-sol",
+)
+
+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, hand off to the Spanish agent.",
+    ),
+    model="gpt-5.6-sol",
+    handoffs=[spanish_agent],
+    tools=[get_weather],
+)
+```
+
+## Voice pipeline
+
+We'll set up a simple voice pipeline, using [`SingleAgentVoiceWorkflow`][agents.voice.workflow.SingleAgentVoiceWorkflow] as the workflow.
+
+```python
+from agents.voice import SingleAgentVoiceWorkflow, VoicePipeline
+pipeline = VoicePipeline(workflow=SingleAgentVoiceWorkflow(agent))
+```
+
+## Run the pipeline
+
+```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)
+
+```
+
+## Put it all together
+
+```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-5.6-sol",
+)
+
+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, hand off to the Spanish agent.",
+    ),
+    model="gpt-5.6-sol",
+    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())
+```
+
+If you run this example, the agent will speak to you! Check out the example in [examples/voice/static](https://github.com/openai/openai-agents-python/tree/main/examples/voice/static) to see a demo where you can speak to the agent yourself.