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{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: stream_audio"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio numpy "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import numpy as np\n", "import time\n", "\n", "def add_to_stream(audio, instream):\n", " time.sleep(1)\n", " if audio is None:\n", " return gr.Audio(), instream\n", " if instream is None:\n", " ret = audio\n", " else:\n", " ret = (audio[0], np.concatenate((instream[1], audio[1])))\n", " return ret, ret\n", "\n", "with gr.Blocks() as demo:\n", " inp = gr.Audio(sources=[\"microphone\"])\n", " out = gr.Audio()\n", " stream = gr.State()\n", " clear = gr.Button(\"Clear\")\n", "\n", " inp.stream(add_to_stream, [inp, stream], [out, stream])\n", " clear.click(lambda: [None, None, None], None, [inp, out, stream])\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} |