Commit 3: Add 35 file(s)

.gitattributes

@@ -35,3 +35,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 demos/calculator/screenshot.gif filter=lfs diff=lfs merge=lfs -text
 demos/kitchen_sink/files/world.mp4 filter=lfs diff=lfs merge=lfs -text
+demos/video_component/files/world.mp4 filter=lfs diff=lfs merge=lfs -text

demos/model3D/run.py

@@ -0,0 +1,25 @@
+import gradio as gr
+import os
+
+def load_mesh(mesh_file_name):
+    return mesh_file_name
+
+demo = gr.Interface(
+    fn=load_mesh,
+    inputs=gr.Model3D(),
+    outputs=gr.Model3D(
+            clear_color=(0.0, 0.0, 0.0, 0.0),  label="3D Model", display_mode="wireframe"),
+    examples=[
+        [os.path.join(os.path.dirname(__file__), "files/Bunny.obj")],
+        [os.path.join(os.path.dirname(__file__), "files/Duck.glb")],
+        [os.path.join(os.path.dirname(__file__), "files/Fox.gltf")],
+        [os.path.join(os.path.dirname(__file__), "files/face.obj")],
+        [os.path.join(os.path.dirname(__file__), "files/sofia.stl")],
+        ["https://huggingface.co/datasets/dylanebert/3dgs/resolve/main/bonsai/bonsai-7k-mini.splat"],
+        ["https://huggingface.co/datasets/dylanebert/3dgs/resolve/main/luigi/luigi.ply"],
+    ],
+    cache_examples=True
+)
+
+if __name__ == "__main__":
+    demo.launch()

demos/native_plots/bar_plot_demo.py

@@ -0,0 +1,74 @@
+import gradio as gr
+from data import temp_sensor_data, food_rating_data
+
+with gr.Blocks() as bar_plots:
+    with gr.Row():
+        start = gr.DateTime("2021-01-01 00:00:00", label="Start")
+        end = gr.DateTime("2021-01-05 00:00:00", label="End")
+        apply_btn = gr.Button("Apply", scale=0)
+    with gr.Row():
+        group_by = gr.Radio(["None", "30m", "1h", "4h", "1d"], value="None", label="Group by")
+        aggregate = gr.Radio(["sum", "mean", "median", "min", "max"], value="sum", label="Aggregation")
+
+    temp_by_time = gr.BarPlot(
+        temp_sensor_data,
+        x="time",
+        y="temperature",
+    )
+    temp_by_time_location = gr.BarPlot(
+        temp_sensor_data,
+        x="time",
+        y="temperature",
+        color="location",
+    )
+
+    time_graphs = [temp_by_time, temp_by_time_location]
+    group_by.change(
+        lambda group: [gr.BarPlot(x_bin=None if group == "None" else group)] * len(time_graphs),
+        group_by,
+        time_graphs
+    )
+    aggregate.change(
+        lambda aggregate: [gr.BarPlot(y_aggregate=aggregate)] * len(time_graphs),
+        aggregate,
+        time_graphs
+    )
+
+    def rescale(select: gr.SelectData):
+        return select.index
+    rescale_evt = gr.on([plot.select for plot in time_graphs], rescale, None, [start, end])
+
+    for trigger in [apply_btn.click, rescale_evt.then]:
+        trigger(
+            lambda start, end: [gr.BarPlot(x_lim=[start, end])] * len(time_graphs), [start, end], time_graphs
+        )
+
+    with gr.Row():
+        price_by_cuisine = gr.BarPlot(
+            food_rating_data,
+            x="cuisine",
+            y="price",
+        )
+        with gr.Column(scale=0):
+            gr.Button("Sort $ > $$$").click(lambda: gr.BarPlot(sort="y"), None, price_by_cuisine)
+            gr.Button("Sort $$$ > $").click(lambda: gr.BarPlot(sort="-y"), None, price_by_cuisine)
+            gr.Button("Sort A > Z").click(lambda: gr.BarPlot(sort=["Chinese", "Italian", "Mexican"]), None, price_by_cuisine)
+
+    with gr.Row():
+        price_by_rating = gr.BarPlot(
+            food_rating_data,
+            x="rating",
+            y="price",
+            x_bin=1,
+        )
+        price_by_rating_color = gr.BarPlot(
+            food_rating_data,
+            x="rating",
+            y="price",
+            color="cuisine",
+            x_bin=1,
+            color_map={"Italian": "red", "Mexican": "green", "Chinese": "blue"},
+        )
+
+if __name__ == "__main__":
+    bar_plots.launch()

demos/native_plots/data.py

@@ -0,0 +1,20 @@
+import pandas as pd
+from random import randint, random
+
+temp_sensor_data = pd.DataFrame(
+    {
+        "time": pd.date_range("2021-01-01", end="2021-01-05", periods=200),
+        "temperature": [randint(50 + 10 * (i % 2), 65 + 15 * (i % 2)) for i in range(200)],
+        "humidity": [randint(50 + 10 * (i % 2), 65 + 15 * (i % 2)) for i in range(200)],
+        "location": ["indoor", "outdoor"] * 100,
+    }
+)
+
+food_rating_data = pd.DataFrame(
+    {
+        "cuisine": [["Italian", "Mexican", "Chinese"][i % 3] for i in range(100)],
+        "rating": [random() * 4 + 0.5 * (i % 3) for i in range(100)],
+        "price": [randint(10, 50) + 4 * (i % 3) for i in range(100)],
+        "wait": [random() for i in range(100)],
+    }
+)

demos/native_plots/line_plot_demo.py

@@ -0,0 +1,66 @@
+import gradio as gr
+from data import temp_sensor_data, food_rating_data
+
+with gr.Blocks() as line_plots:
+    with gr.Row():
+        start = gr.DateTime("2021-01-01 00:00:00", label="Start")
+        end = gr.DateTime("2021-01-05 00:00:00", label="End")
+        apply_btn = gr.Button("Apply", scale=0)
+    with gr.Row():
+        group_by = gr.Radio(["None", "30m", "1h", "4h", "1d"], value="None", label="Group by")
+        aggregate = gr.Radio(["sum", "mean", "median", "min", "max"], value="sum", label="Aggregation")
+
+    temp_by_time = gr.LinePlot(
+        temp_sensor_data,
+        x="time",
+        y="temperature",
+    )
+    temp_by_time_location = gr.LinePlot(
+        temp_sensor_data,
+        x="time",
+        y="temperature",
+        color="location",
+    )
+
+    time_graphs = [temp_by_time, temp_by_time_location]
+    group_by.change(
+        lambda group: [gr.LinePlot(x_bin=None if group == "None" else group)] * len(time_graphs),
+        group_by,
+        time_graphs
+    )
+    aggregate.change(
+        lambda aggregate: [gr.LinePlot(y_aggregate=aggregate)] * len(time_graphs),
+        aggregate,
+        time_graphs
+    )
+
+    def rescale(select: gr.SelectData):
+        return select.index
+    rescale_evt = gr.on([plot.select for plot in time_graphs], rescale, None, [start, end])
+
+    for trigger in [apply_btn.click, rescale_evt.then]:
+        trigger(
+            lambda start, end: [gr.LinePlot(x_lim=[start, end])] * len(time_graphs), [start, end], time_graphs
+        )
+
+    price_by_cuisine = gr.LinePlot(
+        food_rating_data,
+        x="cuisine",
+        y="price",
+    )
+    with gr.Row():
+        price_by_rating = gr.LinePlot(
+            food_rating_data,
+            x="rating",
+            y="price",
+        )
+        price_by_rating_color = gr.LinePlot(
+            food_rating_data,
+            x="rating",
+            y="price",
+            color="cuisine",
+            color_map={"Italian": "red", "Mexican": "green", "Chinese": "blue"},
+        )
+
+if __name__ == "__main__":
+    line_plots.launch()

demos/native_plots/requirements.txt

@@ -0,0 +1,2 @@
+vega_datasets
+pandas

demos/native_plots/run.ipynb

@@ -0,0 +1 @@
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: native_plots"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio vega_datasets pandas "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/native_plots/bar_plot_demo.py\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/native_plots/data.py\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/native_plots/line_plot_demo.py\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/native_plots/scatter_plot_demo.py"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "from scatter_plot_demo import scatter_plots\n", "from line_plot_demo import line_plots\n", "from bar_plot_demo import bar_plots\n", "\n", "with gr.Blocks() as demo:\n", "    with gr.Tabs():\n", "        with gr.TabItem(\"Line Plot\"):\n", "            line_plots.render()\n", "        with gr.TabItem(\"Scatter Plot\"):\n", "            scatter_plots.render()\n", "        with gr.TabItem(\"Bar Plot\"):\n", "            bar_plots.render()\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

demos/native_plots/run.py

@@ -0,0 +1,17 @@
+import gradio as gr
+
+from scatter_plot_demo import scatter_plots
+from line_plot_demo import line_plots
+from bar_plot_demo import bar_plots
+
+with gr.Blocks() as demo:
+    with gr.Tabs():
+        with gr.TabItem("Line Plot"):
+            line_plots.render()
+        with gr.TabItem("Scatter Plot"):
+            scatter_plots.render()
+        with gr.TabItem("Bar Plot"):
+            bar_plots.render()
+
+if __name__ == "__main__":
+    demo.launch()

demos/native_plots/scatter_plot_demo.py

@@ -0,0 +1,68 @@
+import gradio as gr
+from data import temp_sensor_data, food_rating_data
+
+with gr.Blocks() as scatter_plots:
+    with gr.Row():
+        start = gr.DateTime("2021-01-01 00:00:00", label="Start")
+        end = gr.DateTime("2021-01-05 00:00:00", label="End")
+        apply_btn = gr.Button("Apply", scale=0)
+    with gr.Row():
+        group_by = gr.Radio(["None", "30m", "1h", "4h", "1d"], value="None", label="Group by")
+        aggregate = gr.Radio(["sum", "mean", "median", "min", "max"], value="sum", label="Aggregation")
+
+    temp_by_time = gr.ScatterPlot(
+        temp_sensor_data,
+        x="time",
+        y="temperature",
+    )
+    temp_by_time_location = gr.ScatterPlot(
+        temp_sensor_data,
+        x="time",
+        y="temperature",
+        color="location",
+    )
+
+    time_graphs = [temp_by_time, temp_by_time_location]
+    group_by.change(
+        lambda group: [gr.ScatterPlot(x_bin=None if group == "None" else group)] * len(time_graphs),
+        group_by,
+        time_graphs
+    )
+    aggregate.change(
+        lambda aggregate: [gr.ScatterPlot(y_aggregate=aggregate)] * len(time_graphs),
+        aggregate,
+        time_graphs
+    )
+
+    # def rescale(select: gr.SelectData):
+    #     return select.index
+    # rescale_evt = gr.on([plot.select for plot in time_graphs], rescale, None, [start, end])
+
+    # for trigger in [apply_btn.click, rescale_evt.then]:
+    #     trigger(
+    #         lambda start, end: [gr.ScatterPlot(x_lim=[start, end])] * len(time_graphs), [start, end], time_graphs
+    #     )
+
+    price_by_cuisine = gr.ScatterPlot(
+        food_rating_data,
+        x="cuisine",
+        y="price",
+    )
+    with gr.Row():
+        price_by_rating = gr.ScatterPlot(
+            food_rating_data,
+            x="rating",
+            y="price",
+            color="wait",
+            show_actions_button=True,
+        )
+        price_by_rating_color = gr.ScatterPlot(
+            food_rating_data,
+            x="rating",
+            y="price",
+            color="cuisine",
+            # color_map={"Italian": "red", "Mexican": "green", "Chinese": "blue"},
+        )
+
+if __name__ == "__main__":
+    scatter_plots.launch()

demos/reverse_audio/requirements.txt

@@ -0,0 +1 @@
+numpy

demos/reverse_audio/run.ipynb

@@ -0,0 +1 @@
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: reverse_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": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('audio')\n", "!wget -q -O audio/cantina.wav https://github.com/gradio-app/gradio/raw/main/demo/reverse_audio/audio/cantina.wav\n", "!wget -q -O audio/recording1.wav https://github.com/gradio-app/gradio/raw/main/demo/reverse_audio/audio/recording1.wav"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["\n", "import numpy as np\n", "\n", "import gradio as gr\n", "\n", "def reverse_audio(audio):\n", "    sr, data = audio\n", "    return (sr, np.flipud(data))\n", "\n", "input_audio = gr.Audio(\n", "    sources=[\"microphone\"],\n", "    waveform_options=gr.WaveformOptions(\n", "        waveform_color=\"#01C6FF\",\n", "        waveform_progress_color=\"#0066B4\",\n", "        skip_length=2,\n", "        show_controls=False,\n", "    ),\n", ")\n", "demo = gr.Interface(\n", "    fn=reverse_audio,\n", "    inputs=input_audio,\n", "    outputs=\"audio\"\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

demos/reverse_audio/run.py

@@ -0,0 +1,26 @@
+
+import numpy as np
+
+import gradio as gr
+
+def reverse_audio(audio):
+    sr, data = audio
+    return (sr, np.flipud(data))
+
+input_audio = gr.Audio(
+    sources=["microphone"],
+    waveform_options=gr.WaveformOptions(
+        waveform_color="#01C6FF",
+        waveform_progress_color="#0066B4",
+        skip_length=2,
+        show_controls=False,
+    ),
+)
+demo = gr.Interface(
+    fn=reverse_audio,
+    inputs=input_audio,
+    outputs="audio"
+)
+
+if __name__ == "__main__":
+    demo.launch()

demos/stream_audio/requirements.txt

@@ -0,0 +1 @@
+numpy

demos/stream_audio/run.ipynb

@@ -0,0 +1 @@
+{"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}

demos/stream_audio/run.py

@@ -0,0 +1,25 @@
+import gradio as gr
+import numpy as np
+import time
+
+def add_to_stream(audio, instream):
+    time.sleep(1)
+    if audio is None:
+        return gr.Audio(), instream
+    if instream is None:
+        ret = audio
+    else:
+        ret = (audio[0], np.concatenate((instream[1], audio[1])))
+    return ret, ret
+
+with gr.Blocks() as demo:
+    inp = gr.Audio(sources=["microphone"])
+    out = gr.Audio()
+    stream = gr.State()
+    clear = gr.Button("Clear")
+
+    inp.stream(add_to_stream, [inp, stream], [out, stream])
+    clear.click(lambda: [None, None, None], None, [inp, out, stream])
+
+if __name__ == "__main__":
+    demo.launch()

demos/stream_frames/requirements.txt

@@ -0,0 +1 @@
+numpy

demos/stream_frames/run.ipynb

@@ -0,0 +1 @@
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: stream_frames"]}, {"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", "\n", "def flip(im):\n", "    return np.flipud(im)\n", "\n", "demo = gr.Interface(\n", "    flip,\n", "    gr.Image(sources=[\"webcam\"], streaming=True),\n", "    \"image\",\n", "    live=True\n", ")\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

demos/stream_frames/run.py

@@ -0,0 +1,14 @@
+import gradio as gr
+import numpy as np
+
+def flip(im):
+    return np.flipud(im)
+
+demo = gr.Interface(
+    flip,
+    gr.Image(sources=["webcam"], streaming=True),
+    "image",
+    live=True
+)
+if __name__ == "__main__":
+    demo.launch()

demos/stt_or_tts/run.ipynb

@@ -0,0 +1 @@
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: stt_or_tts"]}, {"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", "\n", "tts_examples = [\n", "    \"I love learning machine learning\",\n", "    \"How do you do?\",\n", "]\n", "\n", "tts_demo = gr.load(\n", "    \"huggingface/facebook/fastspeech2-en-ljspeech\",\n", "    title=None,\n", "    examples=tts_examples,\n", "    description=\"Give me something to say!\",\n", ")\n", "\n", "stt_demo = gr.load(\n", "    \"huggingface/facebook/wav2vec2-base-960h\",\n", "    title=None,\n", "    inputs=gr.Microphone(type=\"filepath\"),\n", "    description=\"Let me try to guess what you're saying!\",\n", ")\n", "\n", "demo = gr.TabbedInterface([tts_demo, stt_demo], [\"Text-to-speech\", \"Speech-to-text\"])\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

demos/stt_or_tts/run.py

@@ -0,0 +1,25 @@
+import gradio as gr
+
+tts_examples = [
+    "I love learning machine learning",
+    "How do you do?",
+]
+
+tts_demo = gr.load(
+    "huggingface/facebook/fastspeech2-en-ljspeech",
+    title=None,
+    examples=tts_examples,
+    description="Give me something to say!",
+)
+
+stt_demo = gr.load(
+    "huggingface/facebook/wav2vec2-base-960h",
+    title=None,
+    inputs=gr.Microphone(type="filepath"),
+    description="Let me try to guess what you're saying!",
+)
+
+demo = gr.TabbedInterface([tts_demo, stt_demo], ["Text-to-speech", "Speech-to-text"])
+
+if __name__ == "__main__":
+    demo.launch()

demos/video_component/files/world.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:71944d7430c461f0cd6e7fd10cee7eb72786352a3678fc7bc0ae3d410f72aece
+size 1570024

demos/video_component/run.ipynb

@@ -0,0 +1 @@
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: video_component"]}, {"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/a.mp4 https://github.com/gradio-app/gradio/raw/main/demo/video_component/files/a.mp4\n", "!wget -q -O files/b.mp4 https://github.com/gradio-app/gradio/raw/main/demo/video_component/files/b.mp4\n", "!wget -q -O files/world.mp4 https://github.com/gradio-app/gradio/raw/main/demo/video_component/files/world.mp4"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "\n", "a = os.path.join(os.path.abspath(''), \"files/world.mp4\")  # Video\n", "b = os.path.join(os.path.abspath(''), \"files/a.mp4\")  # Video\n", "c = os.path.join(os.path.abspath(''), \"files/b.mp4\")  # Video\n", "\n", "demo = gr.Interface(\n", "    fn=lambda x: x,\n", "    inputs=gr.Video(),\n", "    outputs=gr.Video(),\n", "    examples=[\n", "        [a],\n", "        [b],\n", "        [c],\n", "    ],\n", "    cache_examples=True\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

demos/video_component/run.py

@@ -0,0 +1,21 @@
+import gradio as gr
+import os
+
+a = os.path.join(os.path.dirname(__file__), "files/world.mp4")  # Video
+b = os.path.join(os.path.dirname(__file__), "files/a.mp4")  # Video
+c = os.path.join(os.path.dirname(__file__), "files/b.mp4")  # Video
+
+demo = gr.Interface(
+    fn=lambda x: x,
+    inputs=gr.Video(),
+    outputs=gr.Video(),
+    examples=[
+        [a],
+        [b],
+        [c],
+    ],
+    cache_examples=True
+)
+
+if __name__ == "__main__":
+    demo.launch()

demos/zip_files/files/titanic.csv

@@ -0,0 +1,892 @@
+PassengerId,Survived,Pclass,Name,Sex,Age,SibSp,Parch,Ticket,Fare,Cabin,Embarked
+1,0,3,"Braund, Mr. Owen Harris",male,22,1,0,A/5 21171,7.25,,S
+2,1,1,"Cumings, Mrs. John Bradley (Florence Briggs Thayer)",female,38,1,0,PC 17599,71.2833,C85,C
+3,1,3,"Heikkinen, Miss. Laina",female,26,0,0,STON/O2. 3101282,7.925,,S
+4,1,1,"Futrelle, Mrs. Jacques Heath (Lily May Peel)",female,35,1,0,113803,53.1,C123,S
+5,0,3,"Allen, Mr. William Henry",male,35,0,0,373450,8.05,,S
+6,0,3,"Moran, Mr. James",male,,0,0,330877,8.4583,,Q
+7,0,1,"McCarthy, Mr. Timothy J",male,54,0,0,17463,51.8625,E46,S
+8,0,3,"Palsson, Master. Gosta Leonard",male,2,3,1,349909,21.075,,S
+9,1,3,"Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)",female,27,0,2,347742,11.1333,,S
+10,1,2,"Nasser, Mrs. Nicholas (Adele Achem)",female,14,1,0,237736,30.0708,,C
+11,1,3,"Sandstrom, Miss. Marguerite Rut",female,4,1,1,PP 9549,16.7,G6,S
+12,1,1,"Bonnell, Miss. Elizabeth",female,58,0,0,113783,26.55,C103,S
+13,0,3,"Saundercock, Mr. William Henry",male,20,0,0,A/5. 2151,8.05,,S
+14,0,3,"Andersson, Mr. Anders Johan",male,39,1,5,347082,31.275,,S
+15,0,3,"Vestrom, Miss. Hulda Amanda Adolfina",female,14,0,0,350406,7.8542,,S
+16,1,2,"Hewlett, Mrs. (Mary D Kingcome) ",female,55,0,0,248706,16,,S
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+18,1,2,"Williams, Mr. Charles Eugene",male,,0,0,244373,13,,S
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+24,1,1,"Sloper, Mr. William Thompson",male,28,0,0,113788,35.5,A6,S
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+26,1,3,"Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson)",female,38,1,5,347077,31.3875,,S
+27,0,3,"Emir, Mr. Farred Chehab",male,,0,0,2631,7.225,,C
+28,0,1,"Fortune, Mr. Charles Alexander",male,19,3,2,19950,263,C23 C25 C27,S
+29,1,3,"O'Dwyer, Miss. Ellen ""Nellie""",female,,0,0,330959,7.8792,,Q
+30,0,3,"Todoroff, Mr. Lalio",male,,0,0,349216,7.8958,,S
+31,0,1,"Uruchurtu, Don. Manuel E",male,40,0,0,PC 17601,27.7208,,C
+32,1,1,"Spencer, Mrs. William Augustus (Marie Eugenie)",female,,1,0,PC 17569,146.5208,B78,C
+33,1,3,"Glynn, Miss. Mary Agatha",female,,0,0,335677,7.75,,Q
+34,0,2,"Wheadon, Mr. Edward H",male,66,0,0,C.A. 24579,10.5,,S
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+44,1,2,"Laroche, Miss. Simonne Marie Anne Andree",female,3,1,2,SC/Paris 2123,41.5792,,C
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+79,1,2,"Caldwell, Master. Alden Gates",male,0.83,0,2,248738,29,,S
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+84,0,1,"Carrau, Mr. Francisco M",male,28,0,0,113059,47.1,,S
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+99,1,2,"Doling, Mrs. John T (Ada Julia Bone)",female,34,0,1,231919,23,,S
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+112,0,3,"Zabour, Miss. Hileni",female,14.5,1,0,2665,14.4542,,C
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+115,0,3,"Attalah, Miss. Malake",female,17,0,0,2627,14.4583,,C
+116,0,3,"Pekoniemi, Mr. Edvard",male,21,0,0,STON/O 2. 3101294,7.925,,S
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+128,1,3,"Madsen, Mr. Fridtjof Arne",male,24,0,0,C 17369,7.1417,,S
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+858,1,1,"Daly, Mr. Peter Denis ",male,51,0,0,113055,26.55,E17,S
+859,1,3,"Baclini, Mrs. Solomon (Latifa Qurban)",female,24,0,3,2666,19.2583,,C
+860,0,3,"Razi, Mr. Raihed",male,,0,0,2629,7.2292,,C
+861,0,3,"Hansen, Mr. Claus Peter",male,41,2,0,350026,14.1083,,S
+862,0,2,"Giles, Mr. Frederick Edward",male,21,1,0,28134,11.5,,S
+863,1,1,"Swift, Mrs. Frederick Joel (Margaret Welles Barron)",female,48,0,0,17466,25.9292,D17,S
+864,0,3,"Sage, Miss. Dorothy Edith ""Dolly""",female,,8,2,CA. 2343,69.55,,S
+865,0,2,"Gill, Mr. John William",male,24,0,0,233866,13,,S
+866,1,2,"Bystrom, Mrs. (Karolina)",female,42,0,0,236852,13,,S
+867,1,2,"Duran y More, Miss. Asuncion",female,27,1,0,SC/PARIS 2149,13.8583,,C
+868,0,1,"Roebling, Mr. Washington Augustus II",male,31,0,0,PC 17590,50.4958,A24,S
+869,0,3,"van Melkebeke, Mr. Philemon",male,,0,0,345777,9.5,,S
+870,1,3,"Johnson, Master. Harold Theodor",male,4,1,1,347742,11.1333,,S
+871,0,3,"Balkic, Mr. Cerin",male,26,0,0,349248,7.8958,,S
+872,1,1,"Beckwith, Mrs. Richard Leonard (Sallie Monypeny)",female,47,1,1,11751,52.5542,D35,S
+873,0,1,"Carlsson, Mr. Frans Olof",male,33,0,0,695,5,B51 B53 B55,S
+874,0,3,"Vander Cruyssen, Mr. Victor",male,47,0,0,345765,9,,S
+875,1,2,"Abelson, Mrs. Samuel (Hannah Wizosky)",female,28,1,0,P/PP 3381,24,,C
+876,1,3,"Najib, Miss. Adele Kiamie ""Jane""",female,15,0,0,2667,7.225,,C
+877,0,3,"Gustafsson, Mr. Alfred Ossian",male,20,0,0,7534,9.8458,,S
+878,0,3,"Petroff, Mr. Nedelio",male,19,0,0,349212,7.8958,,S
+879,0,3,"Laleff, Mr. Kristo",male,,0,0,349217,7.8958,,S
+880,1,1,"Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)",female,56,0,1,11767,83.1583,C50,C
+881,1,2,"Shelley, Mrs. William (Imanita Parrish Hall)",female,25,0,1,230433,26,,S
+882,0,3,"Markun, Mr. Johann",male,33,0,0,349257,7.8958,,S
+883,0,3,"Dahlberg, Miss. Gerda Ulrika",female,22,0,0,7552,10.5167,,S
+884,0,2,"Banfield, Mr. Frederick James",male,28,0,0,C.A./SOTON 34068,10.5,,S
+885,0,3,"Sutehall, Mr. Henry Jr",male,25,0,0,SOTON/OQ 392076,7.05,,S
+886,0,3,"Rice, Mrs. William (Margaret Norton)",female,39,0,5,382652,29.125,,Q
+887,0,2,"Montvila, Rev. Juozas",male,27,0,0,211536,13,,S
+888,1,1,"Graham, Miss. Margaret Edith",female,19,0,0,112053,30,B42,S
+889,0,3,"Johnston, Miss. Catherine Helen ""Carrie""",female,,1,2,W./C. 6607,23.45,,S
+890,1,1,"Behr, Mr. Karl Howell",male,26,0,0,111369,30,C148,C
+891,0,3,"Dooley, Mr. Patrick",male,32,0,0,370376,7.75,,Q

demos/zip_files/run.ipynb

@@ -0,0 +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": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('files')\n", "!wget -q -O files/titanic.csv https://github.com/gradio-app/gradio/raw/main/demo/zip_files/files/titanic.csv"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "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}

demos/zip_files/run.py

@@ -0,0 +1,23 @@
+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])
+    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")]]],
+    cache_examples=True
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1,6 @@
+gradio-client @ git+https://github.com/gradio-app/gradio@96e66f7cba28acb1b47cabbb23afd94c76600724#subdirectory=client/python
+https://gradio-pypi-previews.s3.amazonaws.com/96e66f7cba28acb1b47cabbb23afd94c76600724/gradio-5.5.0-py3-none-any.whl
+pypistats==1.1.0
+plotly
+altair
+vega_datasets

run.py

@@ -0,0 +1,57 @@
+import importlib
+import gradio as gr
+import os
+import sys
+import copy
+import pathlib
+from fastapi import FastAPI, Request
+from fastapi.templating import Jinja2Templates
+import uvicorn
+from gradio.utils import get_space
+
+os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
+
+demo_dir = pathlib.Path(__file__).parent / "demos"
+
+app = FastAPI()
+
+templates = Jinja2Templates(directory="templates")
+
+names = sorted(os.listdir("./demos"))
+
+
+@app.get("/")
+def index(request: Request):
+    names = [[p[0], p[2]] for p in all_demos]
+    return templates.TemplateResponse(
+        "index.html",
+        {
+            "request": request,
+            "names": names,
+            "initial_demo": names[0][0],
+            "is_space": get_space(),
+        },
+    )
+
+
+all_demos = []
+demo_module = None
+for p in sorted(os.listdir("./demos")):
+    old_path = copy.deepcopy(sys.path)
+    sys.path = [os.path.join(demo_dir, p)] + sys.path
+    try:  # Some demos may not be runnable because of 429 timeouts, etc.
+        if demo_module is None:
+            demo_module = importlib.import_module("run")
+        else:
+            demo_module = importlib.reload(demo_module)
+        all_demos.append((p, demo_module.demo, False))
+    except Exception as e:
+        with gr.Blocks() as demo:
+            gr.Markdown(f"Error loading demo: {e}")
+        all_demos.append((p, demo, True))
+
+for demo_name, demo, _ in all_demos:
+    app = gr.mount_gradio_app(app, demo, f"/demo/{demo_name}")
+
+if __name__ == "__main__":
+    uvicorn.run(app, port=7860, host="0.0.0.0")

templates/index.html

@@ -0,0 +1,118 @@
+<!DOCTYPE html>
+<html>
+<head>
+    {%if is_space %}
+        <meta http-equiv="Content-Security-Policy" content="upgrade-insecure-requests">
+    {% endif %}
+    <style>
+        /* Reset some default styles */
+        body, h1, h2, h3, p, ul {
+            margin: 0;
+            padding: 0;
+        }
+
+        body {
+            font-family: 'Arial', sans-serif;
+            overflow-y: hidden;
+        }
+
+        .sidebar {
+            position: absolute;
+            top: 0;
+            left: 0;
+            height: 100vh;
+            max-height: calc(100vh - 50px);
+            width: 300px;
+            overflow-y: scroll;
+            overflow-x: hidden;
+            font-size: 0.875rem; /* 14px */
+            line-height: 1.25rem; /* 20px */
+            transition: width 0.3s ease;
+        }
+
+        .sidebar.collapsed {
+            width: 0;
+        }
+
+        .sidebar a {
+            display: block;
+            padding: 8px 16px;
+            text-decoration: none;
+            color: rgb(107 114 128);
+        }
+
+        .sidebar a:hover {
+            color: black;
+            transform: translateX(1px);
+        }
+
+        /* Apply a different style to the selected item in the sidebar */
+        .sidebar a.active {
+            background-color: rgb(251 146 60);
+            color: white;
+            border-radius: 0.75rem;
+            font-weight: bold;
+        }
+
+        /* Styling for the close button */
+        .close-btn {
+            cursor: pointer;
+            border: none;
+            background-color: white;
+            font-size: xx-large;
+            position: relative;
+        }
+
+        /* Styling for the content */
+        .content {
+            margin-left: 300px;
+            padding: 20px;
+            display: block;
+            height: 100vh;
+            transition: margin-left 0.3s ease;
+        }
+
+        .content.collapsed {
+            margin-left: 0;
+        }
+
+        /* Make the iframe responsive */
+        .content iframe {
+            width: 100%;
+            border: 0;
+            height: 100%;
+        }
+
+        @media only screen and (max-width: 600px) {
+            /* Adjust styles for smaller screens */
+            .sidebar {
+                width: 100%;
+                position: relative;
+                height: auto;
+            }
+
+            .content {
+                margin-left: 0;
+            }
+        }
+    </style>
+    <script src="//unpkg.com/alpinejs" defer></script>
+</head>
+<body x-data="{ current_demo: '{{ initial_demo }}', is_collapsed: false }">
+    <div style="display: flex; flex-direction: column;">
+        <div>
+            <button @click="is_collapsed = !is_collapsed" class="close-btn">
+                <a x-text="is_collapsed ? '➡️' : '⬅️'"></a>
+            </button>
+        </div>
+        <div :class="{ 'sidebar': true, 'collapsed': is_collapsed }" style="margin-top: 50px;">
+            {% for name in names %}
+                <a @click="current_demo = '{{ name[0] }}'" :class="current_demo == '{{ name[0] }}' ? 'active' : ''">{{ name[0] }} {% if name[1] %}❌{% endif %}</a>
+            {% endfor %}
+        </div>
+    </div>
+    <div :class="{ 'content': true, 'collapsed': is_collapsed }">
+        <iframe :src="`/demo/${current_demo}${document.location.search}`"></iframe>
+    </div>
+</body>
+</html>