chore: import upstream snapshot with attribution

examples/voice/static/main.py

@@ -0,0 +1,88 @@
+import asyncio
+import random
+
+import numpy as np
+
+from agents import Agent, function_tool
+from agents.extensions.handoff_prompt import prompt_with_handoff_instructions
+from agents.voice import (
+    AudioInput,
+    SingleAgentVoiceWorkflow,
+    SingleAgentWorkflowCallbacks,
+    VoicePipeline,
+)
+
+from .util import AudioPlayer, record_audio
+
+"""
+This is a simple example that uses a recorded audio buffer. Run it via:
+`python -m examples.voice.static.main`
+
+1. You can record an audio clip in the terminal.
+2. The pipeline automatically transcribes the audio.
+3. The agent workflow is a simple one that starts at the Assistant agent.
+4. The output of the agent is streamed to the audio player.
+
+Try examples like:
+- Tell me a joke (will respond with a joke)
+- What's the weather in Tokyo? (will call the `get_weather` tool and then speak)
+- Hola, como estas? (will handoff to the spanish agent)
+"""
+
+
+@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-mini",
+)
+
+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-mini",
+    handoffs=[spanish_agent],
+    tools=[get_weather],
+)
+
+
+class WorkflowCallbacks(SingleAgentWorkflowCallbacks):
+    def on_run(self, workflow: SingleAgentVoiceWorkflow, transcription: str) -> None:
+        print(f"[debug] on_run called with transcription: {transcription}")
+
+
+async def main():
+    pipeline = VoicePipeline(
+        workflow=SingleAgentVoiceWorkflow(agent, callbacks=WorkflowCallbacks())
+    )
+
+    audio_input = AudioInput(buffer=record_audio())
+
+    result = await pipeline.run(audio_input)
+
+    with AudioPlayer() as player:
+        async for event in result.stream():
+            if event.type == "voice_stream_event_audio":
+                player.add_audio(event.data)
+                print("Received audio")
+            elif event.type == "voice_stream_event_lifecycle":
+                print(f"Received lifecycle event: {event.event}")
+
+        # Add 1 second of silence to the end of the stream to avoid cutting off the last audio.
+        player.add_audio(np.zeros(24000 * 1, dtype=np.int16))
+
+
+if __name__ == "__main__":
+    asyncio.run(main())