Commit 2: Add 49 file(s)

demos/kitchen_sink/run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: kitchen_sink"]}, {"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 os\n", "import json\n", "\n", "import numpy as np\n", "\n", "import gradio as gr\n", "from gradio.media import get_image, get_video, get_audio\n", "\n", "CHOICES = [\"foo\", \"bar\", \"baz\"]\n", "JSONOBJ = \"\"\"{\"items\":{\"item\":[{\"id\": \"0001\",\"type\": null,\"is_good\": false,\"ppu\": 0.55,\"batters\":{\"batter\":[{ \"id\": \"1001\", \"type\": \"Regular\" },{ \"id\": \"1002\", \"type\": \"Chocolate\" },{ \"id\": \"1003\", \"type\": \"Blueberry\" },{ \"id\": \"1004\", \"type\": \"Devil's Food\" }]},\"topping\":[{ \"id\": \"5001\", \"type\": \"None\" },{ \"id\": \"5002\", \"type\": \"Glazed\" },{ \"id\": \"5005\", \"type\": \"Sugar\" },{ \"id\": \"5007\", \"type\": \"Powdered Sugar\" },{ \"id\": \"5006\", \"type\": \"Chocolate with Sprinkles\" },{ \"id\": \"5003\", \"type\": \"Chocolate\" },{ \"id\": \"5004\", \"type\": \"Maple\" }]}]}}\"\"\"\n", "\n", "def fn(\n", "    text1,\n", "    text2,\n", "    num,\n", "    slider1,\n", "    slider2,\n", "    single_checkbox,\n", "    checkboxes,\n", "    radio,\n", "    dropdown,\n", "    multi_dropdown,\n", "    im1,\n", "    # im2,\n", "    # im3,\n", "    im4,\n", "    video,\n", "    audio1,\n", "    audio2,\n", "    file,\n", "    df1,\n", "    time,\n", "):\n", "    return (\n", "        (text1 if single_checkbox else text2)\n", "        + \", selected:\"\n", "        + \", \".join(checkboxes),  # Text\n", "        {\n", "            \"positive\": num / (num + slider1 + slider2),\n", "            \"negative\": slider1 / (num + slider1 + slider2),\n", "            \"neutral\": slider2 / (num + slider1 + slider2),\n", "        },  # Label\n", "        (audio1[0], np.flipud(audio1[1]))\n", "        if audio1 is not None\n", "        else os.path.join(os.path.abspath(''), \"files/cantina.wav\"),  # Audio\n", "        np.flipud(im1)\n", "        if im1 is not None\n", "        else get_image(\"cheetah1.jpg\"),  # Image\n", "        video\n", "        if video is not None\n", "        else get_video(\"world.mp4\"),  # Video\n", "        [\n", "            (\"The\", \"art\"),\n", "            (\"quick brown\", \"adj\"),\n", "            (\"fox\", \"nn\"),\n", "            (\"jumped\", \"vrb\"),\n", "            (\"testing testing testing\", None),\n", "            (\"over\", \"prp\"),\n", "            (\"the\", \"art\"),\n", "            (\"testing\", None),\n", "            (\"lazy\", \"adj\"),\n", "            (\"dogs\", \"nn\"),\n", "            (\".\", \"punc\"),\n", "        ]\n", "        + [(f\"test {x}\", f\"test {x}\") for x in range(10)],  # HighlightedText\n", "        # [(\"The testing testing testing\", None), (\"quick brown\", 0.2), (\"fox\", 1), (\"jumped\", -1), (\"testing testing testing\", 0), (\"over\", 0), (\"the\", 0), (\"testing\", 0), (\"lazy\", 1), (\"dogs\", 0), (\".\", 1)] + [(f\"test {x}\",  x/10) for x in range(-10, 10)],  # HighlightedText\n", "        [\n", "            (\"The testing testing testing\", None),\n", "            (\"over\", 0.6),\n", "            (\"the\", 0.2),\n", "            (\"testing\", None),\n", "            (\"lazy\", -0.1),\n", "            (\"dogs\", 0.4),\n", "            (\".\", 0),\n", "        ]\n", "        + [(\"test\", x / 10) for x in range(-10, 10)],  # HighlightedText\n", "        json.loads(JSONOBJ),  # JSON\n", "        \"<button style='background-color: red'>Click Me: \"\n", "        + radio\n", "        + \"</button>\",  # HTML\n", "        os.path.join(os.path.abspath(''), \"files/titanic.csv\"),\n", "        df1,  # Dataframe\n", "        np.random.randint(0, 10, (4, 4)),  # Dataframe\n", "        time, # DateTime\n", "    )\n", "\n", "demo = gr.Interface(\n", "    fn,\n", "    inputs=[\n", "        gr.Textbox(value=\"Lorem ipsum\", label=\"Textbox\"),\n", "        gr.Textbox(lines=3, placeholder=\"Type here..\", label=\"Textbox 2\"),\n", "        gr.Number(label=\"Number\", value=42),\n", "        gr.Slider(10, 20, value=15, label=\"Slider: 10 - 20\"),\n", "        gr.Slider(maximum=20, step=0.04, label=\"Slider: step @ 0.04\"),\n", "        gr.Checkbox(label=\"Checkbox\"),\n", "        gr.CheckboxGroup(label=\"CheckboxGroup\", choices=CHOICES, value=CHOICES[0:2]),\n", "        gr.Radio(label=\"Radio\", choices=CHOICES, value=CHOICES[2]),\n", "        gr.Dropdown(label=\"Dropdown\", choices=CHOICES),\n", "        gr.Dropdown(\n", "            label=\"Multiselect Dropdown (Max choice: 2)\",\n", "            choices=CHOICES,\n", "            multiselect=True,\n", "            max_choices=2,\n", "        ),\n", "        gr.Image(label=\"Image\"),\n", "        # gr.Image(label=\"Image w/ Cropper\", tool=\"select\"),\n", "        # gr.Image(label=\"Sketchpad\", source=\"canvas\"),\n", "        gr.Image(label=\"Webcam\", sources=[\"webcam\"]),\n", "        gr.Video(label=\"Video\"),\n", "        gr.Audio(label=\"Audio\"),\n", "        gr.Audio(label=\"Microphone\", sources=[\"microphone\"]),\n", "        gr.File(label=\"File\"),\n", "        gr.Dataframe(label=\"Dataframe\", headers=[\"Name\", \"Age\", \"Gender\"]),\n", "        gr.DateTime(label=\"DateTime\"),\n", "    ],\n", "    outputs=[\n", "        gr.Textbox(label=\"Textbox\"),\n", "        gr.Label(label=\"Label\"),\n", "        gr.Audio(label=\"Audio\"),\n", "        gr.Image(label=\"Image\", elem_id=\"output-img\"),\n", "        gr.Video(label=\"Video\"),\n", "        gr.HighlightedText(\n", "            label=\"HighlightedText\", color_map={\"punc\": \"pink\", \"test 0\": \"blue\"}\n", "        ),\n", "        gr.HighlightedText(label=\"HighlightedText\", show_legend=True),\n", "        gr.JSON(label=\"JSON\", show_indices=True),\n", "        gr.HTML(label=\"HTML\"),\n", "        gr.File(label=\"File\"),\n", "        gr.Dataframe(label=\"Dataframe\"),\n", "        gr.Dataframe(label=\"Numpy\"),\n", "        gr.DateTime(label=\"DateTime\"),\n", "    ],\n", "    examples=[\n", "        [\n", "            \"the quick brown fox\",\n", "            \"jumps over the lazy dog\",\n", "            10,\n", "            12,\n", "            4,\n", "            True,\n", "            [\"foo\", \"baz\"],\n", "            \"baz\",\n", "            \"bar\",\n", "            [\"foo\", \"bar\"],\n", "            get_image(\"cheetah1.jpg\"),\n", "            # get_image(\"cheetah1.jpg\"),\n", "            # get_image(\"cheetah1.jpg\"),\n", "            get_image(\"cheetah1.jpg\"),\n", "            get_video(\"world.mp4\"),\n", "            get_audio(\"cantina.wav\"),\n", "            get_audio(\"cantina.wav\"),\n", "            os.path.join(os.path.abspath(''), \"files/titanic.csv\"),\n", "            [[1, 2, 3, 4], [4, 5, 6, 7], [8, 9, 1, 2], [3, 4, 5, 6]],\n", "            \"2025-06-10 12:00:00\",\n", "        ]\n", "    ]\n", "    * 3,\n", "    title=\"Kitchen Sink\",\n", "    description=\"Try out all the components!\",\n", "    article=\"Learn more about [Gradio](http://gradio.app)\",\n", "    cache_examples=True,\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: kitchen_sink"]}, {"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 os\n", "import json\n", "\n", "import numpy as np\n", "\n", "import gradio as gr\n", "from gradio.media import get_image, get_video, get_audio, get_file\n", "\n", "CHOICES = [\"foo\", \"bar\", \"baz\"]\n", "JSONOBJ = \"\"\"{\"items\":{\"item\":[{\"id\": \"0001\",\"type\": null,\"is_good\": false,\"ppu\": 0.55,\"batters\":{\"batter\":[{ \"id\": \"1001\", \"type\": \"Regular\" },{ \"id\": \"1002\", \"type\": \"Chocolate\" },{ \"id\": \"1003\", \"type\": \"Blueberry\" },{ \"id\": \"1004\", \"type\": \"Devil's Food\" }]},\"topping\":[{ \"id\": \"5001\", \"type\": \"None\" },{ \"id\": \"5002\", \"type\": \"Glazed\" },{ \"id\": \"5005\", \"type\": \"Sugar\" },{ \"id\": \"5007\", \"type\": \"Powdered Sugar\" },{ \"id\": \"5006\", \"type\": \"Chocolate with Sprinkles\" },{ \"id\": \"5003\", \"type\": \"Chocolate\" },{ \"id\": \"5004\", \"type\": \"Maple\" }]}]}}\"\"\"\n", "\n", "def fn(\n", "    text1,\n", "    text2,\n", "    num,\n", "    slider1,\n", "    slider2,\n", "    single_checkbox,\n", "    checkboxes,\n", "    radio,\n", "    dropdown,\n", "    multi_dropdown,\n", "    im1,\n", "    # im2,\n", "    # im3,\n", "    im4,\n", "    video,\n", "    audio1,\n", "    audio2,\n", "    file,\n", "    df1,\n", "    time,\n", "):\n", "    return (\n", "        (text1 if single_checkbox else text2)\n", "        + \", selected:\"\n", "        + \", \".join(checkboxes),  # Text\n", "        {\n", "            \"positive\": num / (num + slider1 + slider2),\n", "            \"negative\": slider1 / (num + slider1 + slider2),\n", "            \"neutral\": slider2 / (num + slider1 + slider2),\n", "        },  # Label\n", "        (audio1[0], np.flipud(audio1[1]))\n", "        if audio1 is not None\n", "        else get_audio(\"cantina.wav\"),  # Audio\n", "        np.flipud(im1)\n", "        if im1 is not None\n", "        else get_image(\"cheetah1.jpg\"),  # Image\n", "        video\n", "        if video is not None\n", "        else get_video(\"world.mp4\"),  # Video\n", "        [\n", "            (\"The\", \"art\"),\n", "            (\"quick brown\", \"adj\"),\n", "            (\"fox\", \"nn\"),\n", "            (\"jumped\", \"vrb\"),\n", "            (\"testing testing testing\", None),\n", "            (\"over\", \"prp\"),\n", "            (\"the\", \"art\"),\n", "            (\"testing\", None),\n", "            (\"lazy\", \"adj\"),\n", "            (\"dogs\", \"nn\"),\n", "            (\".\", \"punc\"),\n", "        ]\n", "        + [(f\"test {x}\", f\"test {x}\") for x in range(10)],  # HighlightedText\n", "        # [(\"The testing testing testing\", None), (\"quick brown\", 0.2), (\"fox\", 1), (\"jumped\", -1), (\"testing testing testing\", 0), (\"over\", 0), (\"the\", 0), (\"testing\", 0), (\"lazy\", 1), (\"dogs\", 0), (\".\", 1)] + [(f\"test {x}\",  x/10) for x in range(-10, 10)],  # HighlightedText\n", "        [\n", "            (\"The testing testing testing\", None),\n", "            (\"over\", 0.6),\n", "            (\"the\", 0.2),\n", "            (\"testing\", None),\n", "            (\"lazy\", -0.1),\n", "            (\"dogs\", 0.4),\n", "            (\".\", 0),\n", "        ]\n", "        + [(\"test\", x / 10) for x in range(-10, 10)],  # HighlightedText\n", "        json.loads(JSONOBJ),  # JSON\n", "        \"<button style='background-color: red'>Click Me: \"\n", "        + radio\n", "        + \"</button>\",  # HTML\n", "        get_file(\"titanic.csv\"),  # File\n", "        df1,  # Dataframe\n", "        np.random.randint(0, 10, (4, 4)),  # Dataframe\n", "        time, # DateTime\n", "    )\n", "\n", "demo = gr.Interface(\n", "    fn,\n", "    inputs=[\n", "        gr.Textbox(value=\"Lorem ipsum\", label=\"Textbox\"),\n", "        gr.Textbox(lines=3, placeholder=\"Type here..\", label=\"Textbox 2\"),\n", "        gr.Number(label=\"Number\", value=42),\n", "        gr.Slider(10, 20, value=15, label=\"Slider: 10 - 20\"),\n", "        gr.Slider(maximum=20, step=0.04, label=\"Slider: step @ 0.04\"),\n", "        gr.Checkbox(label=\"Checkbox\"),\n", "        gr.CheckboxGroup(label=\"CheckboxGroup\", choices=CHOICES, value=CHOICES[0:2]),\n", "        gr.Radio(label=\"Radio\", choices=CHOICES, value=CHOICES[2]),\n", "        gr.Dropdown(label=\"Dropdown\", choices=CHOICES),\n", "        gr.Dropdown(\n", "            label=\"Multiselect Dropdown (Max choice: 2)\",\n", "            choices=CHOICES,\n", "            multiselect=True,\n", "            max_choices=2,\n", "        ),\n", "        gr.Image(label=\"Image\"),\n", "        # gr.Image(label=\"Image w/ Cropper\", tool=\"select\"),\n", "        # gr.Image(label=\"Sketchpad\", source=\"canvas\"),\n", "        gr.Image(label=\"Webcam\", sources=[\"webcam\"]),\n", "        gr.Video(label=\"Video\"),\n", "        gr.Audio(label=\"Audio\"),\n", "        gr.Audio(label=\"Microphone\", sources=[\"microphone\"]),\n", "        gr.File(label=\"File\"),\n", "        gr.Dataframe(label=\"Dataframe\", headers=[\"Name\", \"Age\", \"Gender\"]),\n", "        gr.DateTime(label=\"DateTime\"),\n", "    ],\n", "    outputs=[\n", "        gr.Textbox(label=\"Textbox\"),\n", "        gr.Label(label=\"Label\"),\n", "        gr.Audio(label=\"Audio\"),\n", "        gr.Image(label=\"Image\", elem_id=\"output-img\"),\n", "        gr.Video(label=\"Video\"),\n", "        gr.HighlightedText(\n", "            label=\"HighlightedText\", color_map={\"punc\": \"pink\", \"test 0\": \"blue\"}\n", "        ),\n", "        gr.HighlightedText(label=\"HighlightedText\", show_legend=True),\n", "        gr.JSON(label=\"JSON\", show_indices=True),\n", "        gr.HTML(label=\"HTML\"),\n", "        gr.File(label=\"File\"),\n", "        gr.Dataframe(label=\"Dataframe\"),\n", "        gr.Dataframe(label=\"Numpy\"),\n", "        gr.DateTime(label=\"DateTime\"),\n", "    ],\n", "    examples=[\n", "        [\n", "            \"the quick brown fox\",\n", "            \"jumps over the lazy dog\",\n", "            10,\n", "            12,\n", "            4,\n", "            True,\n", "            [\"foo\", \"baz\"],\n", "            \"baz\",\n", "            \"bar\",\n", "            [\"foo\", \"bar\"],\n", "            get_image(\"cheetah1.jpg\"),\n", "            # get_image(\"cheetah1.jpg\"),\n", "            # get_image(\"cheetah1.jpg\"),\n", "            get_image(\"cheetah1.jpg\"),\n", "            get_video(\"world.mp4\"),\n", "            get_audio(\"cantina.wav\"),\n", "            get_audio(\"cantina.wav\"),\n", "            get_file(\"titanic.csv\"),\n", "            [[1, 2, 3, 4], [4, 5, 6, 7], [8, 9, 1, 2], [3, 4, 5, 6]],\n", "            \"2025-06-10 12:00:00\",\n", "        ]\n", "    ]\n", "    * 3,\n", "    title=\"Kitchen Sink\",\n", "    description=\"Try out all the components!\",\n", "    article=\"Learn more about [Gradio](http://gradio.app)\",\n", "    cache_examples=True,\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

demos/kitchen_sink/run.py

@@ -4,7 +4,7 @@ import json
 import numpy as np
 
 import gradio as gr
-from gradio.media import get_image, get_video, get_audio
+from gradio.media import get_image, get_video, get_audio, get_file
 
 CHOICES = ["foo", "bar", "baz"]
 JSONOBJ = """{"items":{"item":[{"id": "0001","type": null,"is_good": false,"ppu": 0.55,"batters":{"batter":[{ "id": "1001", "type": "Regular" },{ "id": "1002", "type": "Chocolate" },{ "id": "1003", "type": "Blueberry" },{ "id": "1004", "type": "Devil's Food" }]},"topping":[{ "id": "5001", "type": "None" },{ "id": "5002", "type": "Glazed" },{ "id": "5005", "type": "Sugar" },{ "id": "5007", "type": "Powdered Sugar" },{ "id": "5006", "type": "Chocolate with Sprinkles" },{ "id": "5003", "type": "Chocolate" },{ "id": "5004", "type": "Maple" }]}]}}"""
@@ -42,7 +42,7 @@ def fn(
         },  # Label
         (audio1[0], np.flipud(audio1[1]))
         if audio1 is not None
-        else os.path.join(os.path.dirname(__file__), "files/cantina.wav"),  # Audio
+        else get_audio("cantina.wav"),  # Audio
         np.flipud(im1)
         if im1 is not None
         else get_image("cheetah1.jpg"),  # Image
@@ -78,7 +78,7 @@ def fn(
         "<button style='background-color: red'>Click Me: "
         + radio
         + "</button>",  # HTML
-        os.path.join(os.path.dirname(__file__), "files/titanic.csv"),
+        get_file("titanic.csv"),  # File
         df1,  # Dataframe
         np.random.randint(0, 10, (4, 4)),  # Dataframe
         time, # DateTime
@@ -149,7 +149,7 @@ demo = gr.Interface(
             get_video("world.mp4"),
             get_audio("cantina.wav"),
             get_audio("cantina.wav"),
-            os.path.join(os.path.dirname(__file__), "files/titanic.csv"),
+            get_file("titanic.csv"),
             [[1, 2, 3, 4], [4, 5, 6, 7], [8, 9, 1, 2], [3, 4, 5, 6]],
             "2025-06-10 12:00:00",
         ]

demos/model3D/run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: model3D"]}, {"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": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('files')\n", "!wget -q -O files/source.txt https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/source.txt"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "# get_model3d() returns the file path to sample 3D models included with Gradio\n", "from gradio.media import get_model3d\n", "\n", "\n", "def load_mesh(mesh_file_name):\n", "    return mesh_file_name\n", "\n", "\n", "demo = gr.Interface(\n", "    fn=load_mesh,\n", "    inputs=gr.Model3D(label=\"Other name\", display_mode=\"wireframe\"),\n", "    outputs=gr.Model3D(\n", "        clear_color=(0.0, 0.0, 0.0, 0.0), label=\"3D Model\", display_mode=\"wireframe\"\n", "    ),\n", "    examples=[\n", "        [get_model3d(\"Bunny.obj\")],\n", "        [get_model3d(\"Duck.glb\")],\n", "        [get_model3d(\"Fox.gltf\")],\n", "        [get_model3d(\"face.obj\")],\n", "        [get_model3d(\"sofia.stl\")],\n", "        [\n", "            \"https://huggingface.co/datasets/dylanebert/3dgs/resolve/main/bonsai/bonsai-7k-mini.splat\"\n", "        ],\n", "        [\n", "            \"https://huggingface.co/datasets/dylanebert/3dgs/resolve/main/luigi/luigi.ply\"\n", "        ],\n", "    ],\n", "    cache_examples=True,\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: model3D"]}, {"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", "# get_model3d() returns the file path to sample 3D models included with Gradio\n", "from gradio.media import get_model3d, MEDIA_ROOT\n", "\n", "\n", "def load_mesh(mesh_file_name):\n", "    return mesh_file_name\n", "\n", "\n", "demo = gr.Interface(\n", "    fn=load_mesh,\n", "    inputs=gr.Model3D(label=\"Other name\", display_mode=\"wireframe\"),\n", "    outputs=gr.Model3D(\n", "        clear_color=(0.0, 0.0, 0.0, 0.0), label=\"3D Model\", display_mode=\"wireframe\"\n", "    ),\n", "    examples=[\n", "        [get_model3d(\"Bunny.obj\")],\n", "        [get_model3d(\"Duck.glb\")],\n", "        [get_model3d(\"Fox.gltf\")],\n", "        [get_model3d(\"face.obj\")],\n", "        [get_model3d(\"sofia.stl\")],\n", "        [\n", "            \"https://huggingface.co/datasets/dylanebert/3dgs/resolve/main/bonsai/bonsai-7k-mini.splat\"\n", "        ],\n", "        [\n", "            \"https://huggingface.co/datasets/dylanebert/3dgs/resolve/main/luigi/luigi.ply\"\n", "        ],\n", "    ],\n", "    cache_examples=True,\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch(allowed_paths=[str(MEDIA_ROOT)])\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

demos/model3D/run.py

@@ -1,6 +1,6 @@
 import gradio as gr
 # get_model3d() returns the file path to sample 3D models included with Gradio
-from gradio.media import get_model3d
+from gradio.media import get_model3d, MEDIA_ROOT
 
 
 def load_mesh(mesh_file_name):
@@ -30,4 +30,4 @@ demo = gr.Interface(
 )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(allowed_paths=[str(MEDIA_ROOT)])

demos/zip_files/run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: zip_files"]}, {"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 os\n", "from zipfile import ZipFile\n", "\n", "import gradio as gr\n", "\n", "def zip_files(files):\n", "    with ZipFile(\"tmp.zip\", \"w\") as zipObj:\n", "        for idx, file in enumerate(files):\n", "            zipObj.write(file.name, file.name.split(\"/\")[-1])\n", "    return \"tmp.zip\"\n", "\n", "demo = gr.Interface(\n", "    zip_files,\n", "    gr.File(file_count=\"multiple\", file_types=[\"text\", \".json\", \".csv\"]),\n", "    \"file\",\n", "    examples=[[[os.path.join(os.path.abspath(''),\"files/titanic.csv\"),\n", "    os.path.join(os.path.abspath(''),\"files/titanic.csv\"),\n", "    os.path.join(os.path.abspath(''),\"files/titanic.csv\")]]],\n", "    cache_examples=True\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: zip_files"]}, {"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": ["from zipfile import ZipFile\n", "\n", "import gradio as gr\n", "\n", "def zip_files(files):\n", "    with ZipFile(\"tmp.zip\", \"w\") as zip_obj:\n", "        for file in files:\n", "            zip_obj.write(file.name, file.name.split(\"/\")[-1])\n", "    return \"tmp.zip\"\n", "\n", "demo = gr.Interface(\n", "    zip_files,\n", "    gr.File(file_count=\"multiple\", file_types=[\"text\", \".json\", \".csv\"]),\n", "    \"file\",\n", "    examples=[[[gr.get_file(\"titanic.csv\"),\n", "    gr.get_file(\"titanic.csv\"),\n", "    gr.get_file(\"titanic.csv\")]]],\n", "    cache_examples=True\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

demos/zip_files/run.py

@@ -1,21 +1,20 @@
-import os
 from zipfile import ZipFile
 
 import gradio as gr
 
 def zip_files(files):
-    with ZipFile("tmp.zip", "w") as zipObj:
-        for idx, file in enumerate(files):
-            zipObj.write(file.name, file.name.split("/")[-1])
+    with ZipFile("tmp.zip", "w") as zip_obj:
+        for file in files:
+            zip_obj.write(file.name, file.name.split("/")[-1])
     return "tmp.zip"
 
 demo = gr.Interface(
     zip_files,
     gr.File(file_count="multiple", file_types=["text", ".json", ".csv"]),
     "file",
-    examples=[[[os.path.join(os.path.dirname(__file__),"files/titanic.csv"),
-    os.path.join(os.path.dirname(__file__),"files/titanic.csv"),
-    os.path.join(os.path.dirname(__file__),"files/titanic.csv")]]],
+    examples=[[[gr.get_file("titanic.csv"),
+    gr.get_file("titanic.csv"),
+    gr.get_file("titanic.csv")]]],
     cache_examples=True
 )
 

requirements.txt

@@ -1,5 +1,5 @@
-gradio-client @ git+https://github.com/gradio-app/gradio@5cd6ee6e9198ddfa3f36b7e9240fd0bc01cedea2#subdirectory=client/python
-https://gradio-pypi-previews.s3.amazonaws.com/5cd6ee6e9198ddfa3f36b7e9240fd0bc01cedea2/gradio-5.48.0-py3-none-any.whl
+gradio-client @ git+https://github.com/gradio-app/gradio@5731ff93cc4c8f53e33fa18fcfbe397815a7d81b#subdirectory=client/python
+https://gradio-pypi-previews.s3.amazonaws.com/5731ff93cc4c8f53e33fa18fcfbe397815a7d81b/gradio-5.49.0-py3-none-any.whl
 pypistats==1.1.0
 plotly
 matplotlib

run.py

@@ -4,6 +4,7 @@ import os
 import sys
 import copy
 import pathlib
+from gradio.media import MEDIA_ROOT
 
 os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
 
@@ -42,4 +43,4 @@ for demo_name, demo, _ in all_demos:
     # app = gr.mount_gradio_app(app, demo, f"/demo/{demo_name}")
 
 if __name__ == "__main__":
-    app.launch()
+    app.launch(allowed_paths=[str(MEDIA_ROOT)])