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app.py

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+import numpy as np
+from fastapi import FastAPI
+from fastapi.responses import RedirectResponse
+from fastrtc import ReplyOnPause, Stream, get_twilio_turn_credentials
+from gradio.utils import get_space
+
+
+def detection(audio: tuple[int, np.ndarray]):
+    # Implement any iterator that yields audio
+    # See "LLM Voice Chat" for a more complete example
+    yield audio
+
+
+stream = Stream(
+    handler=ReplyOnPause(detection),
+    modality="audio",
+    mode="send-receive",
+    rtc_configuration=get_twilio_turn_credentials() if get_space() else None,
+    concurrency_limit=20 if get_space() else None,
+)
+
+app = FastAPI()
+
+stream.mount(app)
+
+
+@app.get("/")
+async def index():
+    return RedirectResponse(
+        url="/ui" if not get_space() else "https://fastrtc-echo-audio.hf.space/ui/"
+    )
+
+
+if __name__ == "__main__":
+    import os
+
+    if (mode := os.getenv("MODE")) == "UI":
+        stream.ui.launch(server_port=7860, server_name="0.0.0.0")
+    elif mode == "PHONE":
+        stream.fastphone(host="0.0.0.0", port=7860)
+    else:
+        import uvicorn
+
+        uvicorn.run(app, host="0.0.0.0", port=7860)

requirements.txt

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+fastrtc[vad]
+twilio
+python-dotenv