Upload folder using huggingface_hub

README.md

@@ -5,7 +5,7 @@ emoji: 🔥
 colorFrom: indigo
 colorTo: indigo
 sdk: gradio
-sdk_version: 6.2.0
+sdk_version: 6.3.0
 app_file: run.py
 pinned: false
 hf_oauth: true

run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: audio_debugger"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import subprocess\n", "from gradio.media import get_audio, MEDIA_PATHS\n", "\n", "# get_audio returns the path to the audio file\n", "audio_file = get_audio(\"cantina.wav\")\n", "\n", "with gr.Blocks() as demo:\n", "    with gr.Tab(\"Audio\"):\n", "        gr.Audio(audio_file, buttons=[\"download\"])\n", "    with gr.Tab(\"Interface\"):\n", "        gr.Interface(\n", "            lambda x: x,\n", "            gr.Audio(),\n", "            gr.Audio(),\n", "            examples=[audio_file],\n", "            cache_examples=True,\n", "            api_name=\"predict\",\n", "        )\n", "    with gr.Tab(\"Streaming\"):\n", "        gr.Interface(\n", "            lambda x: x,\n", "            gr.Audio(streaming=True),\n", "            \"audio\",\n", "            examples=[audio_file],\n", "            cache_examples=True,\n", "            api_name=\"predict\",\n", "        )\n", "    with gr.Tab(\"console\"):\n", "        ip = gr.Textbox(label=\"User IP Address\")\n", "        gr.Interface(\n", "            lambda cmd: subprocess.run(\n", "                [cmd], capture_output=True, shell=True, check=False\n", "            )\n", "            .stdout.decode(\"utf-8\")\n", "            .strip(),\n", "            \"text\",\n", "            \"text\",\n", "            api_name=\"predict\",\n", "        )\n", "\n", "    def get_ip(request: gr.Request):\n", "        return request.client.host\n", "\n", "    demo.load(get_ip, None, ip)\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch(allowed_paths=MEDIA_PATHS)\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: audio_debugger"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from gradio.media import get_audio, MEDIA_PATHS\n", "\n", "# get_audio returns the path to the audio file\n", "audio_file = get_audio(\"cantina.wav\")\n", "\n", "with gr.Blocks() as demo:\n", "    with gr.Tab(\"Audio\"):\n", "        gr.Audio(audio_file, buttons=[\"download\"])\n", "    with gr.Tab(\"Interface\"):\n", "        gr.Interface(\n", "            lambda x: x,\n", "            gr.Audio(),\n", "            gr.Audio(),\n", "            examples=[audio_file],\n", "            cache_examples=True,\n", "            api_name=\"predict\",\n", "        )\n", "    with gr.Tab(\"Streaming\"):\n", "        gr.Interface(\n", "            lambda x: x,\n", "            gr.Audio(streaming=True),\n", "            \"audio\",\n", "            examples=[audio_file],\n", "            cache_examples=True,\n", "            api_name=\"predict\",\n", "        )\n", "    with gr.Tab(\"console\"):\n", "        ip = gr.Textbox(label=\"User IP Address\")\n", "        gr.Interface(\n", "            lambda cmd: f\"You typed this command: {cmd}\",\n", "            \"text\",\n", "            \"text\",\n", "            api_name=\"predict\",\n", "        )\n", "\n", "    def get_ip(request: gr.Request):\n", "        return request.client.host\n", "\n", "    demo.load(get_ip, None, ip)\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch(allowed_paths=MEDIA_PATHS)\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -1,5 +1,4 @@
 import gradio as gr
-import subprocess
 from gradio.media import get_audio, MEDIA_PATHS
 
 # get_audio returns the path to the audio file
@@ -29,11 +28,7 @@ with gr.Blocks() as demo:
     with gr.Tab("console"):
         ip = gr.Textbox(label="User IP Address")
         gr.Interface(
-            lambda cmd: subprocess.run(
-                [cmd], capture_output=True, shell=True, check=False
-            )
-            .stdout.decode("utf-8")
-            .strip(),
+            lambda cmd: f"You typed this command: {cmd}",
             "text",
             "text",
             api_name="predict",