Add support for altair plots (#2741)

* Try clean install * Resolve peer dependencies? * frozen lockfile install * Explicitly use version 16 * Add env * Add altair demo * Add unit test * CHANGELOG * Add image to changelog * Add outbreak_forcast notebook * Try again * generate again * Update ui/packages/plot/src/Plot.svelte Co-authored-by: aliabid94 <aabid94@gmail.com> * Fix title Co-authored-by: aliabid94 <aabid94@gmail.com>
2025-03-31 12:20:26 +08:00 · 2022-12-02 14:53:42 -03:00 · 2022-12-02 14:53:42 -03:00 · bed288a509
commit bed288a509
parent 82cd554ff2
18 changed files with 922 additions and 36 deletions
--- a/.github/workflows/deploy-spaces.yml
+++ b/.github/workflows/deploy-spaces.yml
@ -19,6 +19,11 @@ jobs:
      uses: pnpm/action-setup@v2.2.2
      with:
        version: 7
+    - uses: actions/setup-node@v3
+      with:
+        node-version: 16
+        cache: pnpm
+        cache-dependency-path: ui/pnpm-lock.yaml
    - name: Install pip
      run: python -m pip install build requests
    - name: Get PR Number
@ -33,11 +38,13 @@ jobs:
        export AWS_DEFAULT_REGION=us-east-1
        echo ${{ env.GRADIO_VERSION }} > gradio/version.txt
        cd ui
-        pnpm i
+        pnpm i --frozen-lockfile
        pnpm build
        cd ..
        python3 -m build -w
        aws s3 cp dist/gradio-${{ env.GRADIO_VERSION }}-py3-none-any.whl s3://gradio-builds/${{ github.sha  }}/
+      env:
+        NODE_OPTIONS: --max_old_space_size=8192
    - name: Install Hub Client Library
      run: pip install huggingface-hub
    - name: Set up Demos
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@ -2,7 +2,38 @@

 ## New Features:

-### Set the color of a Label component with a function
+### Support for altair plots
+
+The `Plot` component can now accept altair plots as values! 
+Simply return an altair plot from your event listener and gradio will display it in the front-end.
+See the example below:
+
+```python
+import gradio as gr
+import altair as alt
+from vega_datasets import data
+
+cars = data.cars()
+chart = (
+    alt.Chart(cars)
+    .mark_point()
+    .encode(
+        x="Horsepower",
+        y="Miles_per_Gallon",
+        color="Origin",
+    )
+)
+
+with gr.Blocks() as demo:
+    gr.Plot(value=chart)
+demo.launch()
+```
+
+<img width="1366" alt="image" src="https://user-images.githubusercontent.com/41651716/204660697-f994316f-5ca7-4e8a-93bc-eb5e0d556c91.png">
+
+By [@freddyaboulton](https://github.com/freddyaboulton) in [PR 2741](https://github.com/gradio-app/gradio/pull/2741)
+
+### Set the background color of a Label component 

 The `Label` component now accepts a `color` argument by [@freddyaboulton](https://github.com/freddyaboulton) in [PR 2736](https://github.com/gradio-app/gradio/pull/2736).
 The `color` argument should either be a valid css color name or hexadecimal string.
--- a/demo/altair_plot/requirements.txt
+++ b/demo/altair_plot/requirements.txt
@ -0,0 +1,2 @@
+altair
+vega_datasets
--- a/demo/altair_plot/run.ipynb
+++ b/demo/altair_plot/run.ipynb
--- a/demo/altair_plot/run.py
+++ b/demo/altair_plot/run.py
@ -0,0 +1,140 @@
+import altair as alt
+import gradio as gr
+import numpy as np
+import pandas as pd
+from vega_datasets import data
+
+
+def make_plot(plot_type):
+    if plot_type == "scatter_plot":
+        cars = data.cars()
+        return alt.Chart(cars).mark_point().encode(
+            x='Horsepower',
+            y='Miles_per_Gallon',
+            color='Origin',
+        )
+    elif plot_type == "heatmap":
+        # Compute x^2 + y^2 across a 2D grid
+        x, y = np.meshgrid(range(-5, 5), range(-5, 5))
+        z = x ** 2 + y ** 2
+
+        # Convert this grid to columnar data expected by Altair
+        source = pd.DataFrame({'x': x.ravel(),
+                            'y': y.ravel(),
+                            'z': z.ravel()})
+        return alt.Chart(source).mark_rect().encode(
+            x='x:O',
+            y='y:O',
+            color='z:Q'
+        )
+    elif plot_type == "us_map":
+        states = alt.topo_feature(data.us_10m.url, 'states')
+        source = data.income.url
+
+        return alt.Chart(source).mark_geoshape().encode(
+            shape='geo:G',
+            color='pct:Q',
+            tooltip=['name:N', 'pct:Q'],
+            facet=alt.Facet('group:N', columns=2),
+        ).transform_lookup(
+            lookup='id',
+            from_=alt.LookupData(data=states, key='id'),
+            as_='geo'
+        ).properties(
+            width=300,
+            height=175,
+        ).project(
+            type='albersUsa'
+        )
+    elif plot_type == "interactive_barplot":
+        source = data.movies.url
+
+        pts = alt.selection(type="single", encodings=['x'])
+
+        rect = alt.Chart(data.movies.url).mark_rect().encode(
+            alt.X('IMDB_Rating:Q', bin=True),
+            alt.Y('Rotten_Tomatoes_Rating:Q', bin=True),
+            alt.Color('count()',
+                scale=alt.Scale(scheme='greenblue'),
+                legend=alt.Legend(title='Total Records')
+            )
+        )
+
+        circ = rect.mark_point().encode(
+            alt.ColorValue('grey'),
+            alt.Size('count()',
+                legend=alt.Legend(title='Records in Selection')
+            )
+        ).transform_filter(
+            pts
+        )
+
+        bar = alt.Chart(source).mark_bar().encode(
+            x='Major_Genre:N',
+            y='count()',
+            color=alt.condition(pts, alt.ColorValue("steelblue"), alt.ColorValue("grey"))
+        ).properties(
+            width=550,
+            height=200
+        ).add_selection(pts)
+
+        plot = alt.vconcat(
+            rect + circ,
+            bar
+        ).resolve_legend(
+            color="independent",
+            size="independent"
+        )
+        return plot
+    elif plot_type == "radial":
+        source = pd.DataFrame({"values": [12, 23, 47, 6, 52, 19]})
+
+        base = alt.Chart(source).encode(
+            theta=alt.Theta("values:Q", stack=True),
+            radius=alt.Radius("values", scale=alt.Scale(type="sqrt", zero=True, rangeMin=20)),
+            color="values:N",
+        )
+
+        c1 = base.mark_arc(innerRadius=20, stroke="#fff")
+
+        c2 = base.mark_text(radiusOffset=10).encode(text="values:Q")
+
+        return c1 + c2
+    elif plot_type == "multiline":
+        source = data.stocks()
+
+        highlight = alt.selection(type='single', on='mouseover',
+                                fields=['symbol'], nearest=True)
+
+        base = alt.Chart(source).encode(
+            x='date:T',
+            y='price:Q',
+            color='symbol:N'
+        )
+
+        points = base.mark_circle().encode(
+            opacity=alt.value(0)
+        ).add_selection(
+            highlight
+        ).properties(
+            width=600
+        )
+
+        lines = base.mark_line().encode(
+            size=alt.condition(~highlight, alt.value(1), alt.value(3))
+        )
+
+        return points + lines
+
+
+with gr.Blocks() as demo:
+    button = gr.Radio(label="Plot type",
+                      choices=['scatter_plot', 'heatmap', 'us_map',
+                               'interactive_barplot', "radial", "multiline"], value='scatter_plot')
+    plot = gr.Plot(label="Plot")
+    button.change(make_plot, inputs=button, outputs=[plot])
+    demo.load(make_plot, inputs=[button], outputs=[plot])
+
+
+if __name__ == "__main__":
+    demo.launch()
--- a/demo/outbreak_forecast/requirements.txt
+++ b/demo/outbreak_forecast/requirements.txt
@ -1,4 +1,5 @@
 numpy
 matplotlib
 bokeh
-plotly
+plotly
+altair
--- a/demo/outbreak_forecast/run.ipynb
+++ b/demo/outbreak_forecast/run.ipynb
@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: outbreak_forecast\n", "### Generate a plot based on 5 inputs.\n", "        "]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio numpy matplotlib bokeh plotly"]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from math import sqrt\n", "import matplotlib\n", "\n", "matplotlib.use(\"Agg\")\n", "\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import plotly.express as px\n", "import pandas as pd\n", "\n", "\n", "def outbreak(plot_type, r, month, countries, social_distancing):\n", "    months = [\"January\", \"February\", \"March\", \"April\", \"May\"]\n", "    m = months.index(month)\n", "    start_day = 30 * m\n", "    final_day = 30 * (m + 1)\n", "    x = np.arange(start_day, final_day + 1)\n", "    pop_count = {\"USA\": 350, \"Canada\": 40, \"Mexico\": 300, \"UK\": 120}\n", "    if social_distancing:\n", "        r = sqrt(r)\n", "    df = pd.DataFrame({\"day\": x})\n", "    for country in countries:\n", "        df[country] = x ** (r) * (pop_count[country] + 1)\n", "\n", "    if plot_type == \"Matplotlib\":\n", "        fig = plt.figure()\n", "        plt.plot(df[\"day\"], df[countries].to_numpy())\n", "        plt.title(\"Outbreak in \" + month)\n", "        plt.ylabel(\"Cases\")\n", "        plt.xlabel(\"Days since Day 0\")\n", "        plt.legend(countries)\n", "        return fig\n", "    elif plot_type == \"Plotly\":\n", "        fig = px.line(df, x=\"day\", y=countries)\n", "        fig.update_layout(\n", "            title=\"Outbreak in \" + month,\n", "            xaxis_title=\"Cases\",\n", "            yaxis_title=\"Days Since Day 0\",\n", "        )\n", "        return fig\n", "    else:\n", "        raise ValueError(\"A plot type must be selected\")\n", "\n", "\n", "inputs = [\n", "    gr.Dropdown([\"Matplotlib\", \"Plotly\"], label=\"Plot Type\"),\n", "    gr.Slider(1, 4, 3.2, label=\"R\"),\n", "    gr.Dropdown([\"January\", \"February\", \"March\", \"April\", \"May\"], label=\"Month\"),\n", "    gr.CheckboxGroup(\n", "        [\"USA\", \"Canada\", \"Mexico\", \"UK\"], label=\"Countries\", value=[\"USA\", \"Canada\"]\n", "    ),\n", "    gr.Checkbox(label=\"Social Distancing?\"),\n", "]\n", "outputs = gr.Plot()\n", "\n", "demo = gr.Interface(\n", "    fn=outbreak,\n", "    inputs=inputs,\n", "    outputs=outputs,\n", "    examples=[\n", "        [\"Matplotlib\", 2, \"March\", [\"Mexico\", \"UK\"], True],\n", "        [\"Plotly\", 3.6, \"February\", [\"Canada\", \"Mexico\", \"UK\"], False],\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: outbreak_forecast\n", "### Generate a plot based on 5 inputs.\n", "        "]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio numpy matplotlib bokeh plotly altair"]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["import altair\n", "\n", "import gradio as gr\n", "from math import sqrt\n", "import matplotlib\n", "\n", "matplotlib.use(\"Agg\")\n", "\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import plotly.express as px\n", "import pandas as pd\n", "\n", "\n", "def outbreak(plot_type, r, month, countries, social_distancing):\n", "    months = [\"January\", \"February\", \"March\", \"April\", \"May\"]\n", "    m = months.index(month)\n", "    start_day = 30 * m\n", "    final_day = 30 * (m + 1)\n", "    x = np.arange(start_day, final_day + 1)\n", "    pop_count = {\"USA\": 350, \"Canada\": 40, \"Mexico\": 300, \"UK\": 120}\n", "    if social_distancing:\n", "        r = sqrt(r)\n", "    df = pd.DataFrame({\"day\": x})\n", "    for country in countries:\n", "        df[country] = x ** (r) * (pop_count[country] + 1)\n", "\n", "    if plot_type == \"Matplotlib\":\n", "        fig = plt.figure()\n", "        plt.plot(df[\"day\"], df[countries].to_numpy())\n", "        plt.title(\"Outbreak in \" + month)\n", "        plt.ylabel(\"Cases\")\n", "        plt.xlabel(\"Days since Day 0\")\n", "        plt.legend(countries)\n", "        return fig\n", "    elif plot_type == \"Plotly\":\n", "        fig = px.line(df, x=\"day\", y=countries)\n", "        fig.update_layout(\n", "            title=\"Outbreak in \" + month,\n", "            xaxis_title=\"Cases\",\n", "            yaxis_title=\"Days Since Day 0\",\n", "        )\n", "        return fig\n", "    elif plot_type == \"Altair\":\n", "        df = df.melt(id_vars=\"day\").rename(columns={\"variable\": \"country\"})\n", "        fig = altair.Chart(df).mark_line().encode(x=\"day\", y='value', color='country')\n", "        return fig\n", "    else:\n", "        raise ValueError(\"A plot type must be selected\")\n", "\n", "\n", "inputs = [\n", "    gr.Dropdown([\"Matplotlib\", \"Plotly\", \"Altair\"], label=\"Plot Type\"),\n", "    gr.Slider(1, 4, 3.2, label=\"R\"),\n", "    gr.Dropdown([\"January\", \"February\", \"March\", \"April\", \"May\"], label=\"Month\"),\n", "    gr.CheckboxGroup(\n", "        [\"USA\", \"Canada\", \"Mexico\", \"UK\"], label=\"Countries\", value=[\"USA\", \"Canada\"]\n", "    ),\n", "    gr.Checkbox(label=\"Social Distancing?\"),\n", "]\n", "outputs = gr.Plot()\n", "\n", "demo = gr.Interface(\n", "    fn=outbreak,\n", "    inputs=inputs,\n", "    outputs=outputs,\n", "    examples=[\n", "        [\"Matplotlib\", 2, \"March\", [\"Mexico\", \"UK\"], True],\n", "        [\"Altair\", 2, \"March\", [\"Mexico\", \"Canada\"], True],\n", "        [\"Plotly\", 3.6, \"February\", [\"Canada\", \"Mexico\", \"UK\"], False],\n", "    ],\n", "    cache_examples=True,\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
--- a/demo/outbreak_forecast/run.py
+++ b/demo/outbreak_forecast/run.py
@ -1,3 +1,5 @@
+import altair
+
 import gradio as gr
 from math import sqrt
 import matplotlib
@ -39,12 +41,16 @@ def outbreak(plot_type, r, month, countries, social_distancing):
            yaxis_title="Days Since Day 0",
        )
        return fig
+    elif plot_type == "Altair":
+        df = df.melt(id_vars="day").rename(columns={"variable": "country"})
+        fig = altair.Chart(df).mark_line().encode(x="day", y='value', color='country')
+        return fig
    else:
        raise ValueError("A plot type must be selected")


 inputs = [
-    gr.Dropdown(["Matplotlib", "Plotly"], label="Plot Type"),
+    gr.Dropdown(["Matplotlib", "Plotly", "Altair"], label="Plot Type"),
    gr.Slider(1, 4, 3.2, label="R"),
    gr.Dropdown(["January", "February", "March", "April", "May"], label="Month"),
    gr.CheckboxGroup(
@ -60,6 +66,7 @@ demo = gr.Interface(
    outputs=outputs,
    examples=[
        ["Matplotlib", 2, "March", ["Mexico", "UK"], True],
+        ["Altair", 2, "March", ["Mexico", "Canada"], True],
        ["Plotly", 3.6, "February", ["Canada", "Mexico", "UK"], False],
    ],
    cache_examples=True,
--- a/gradio/components.py
+++ b/gradio/components.py
@ -3862,7 +3862,7 @@ class Plot(Changeable, Clearable, IOComponent, JSONSerializable):
    Preprocessing: this component does *not* accept input.
    Postprocessing: expects either a {matplotlib.figure.Figure}, a {plotly.graph_objects._figure.Figure}, or a {dict} corresponding to a bokeh plot (json_item format)

-    Demos: outbreak_forecast, blocks_kinematics, stock_forecast, map_airbnb
+    Demos: altair_plot, outbreak_forecast, blocks_kinematics, stock_forecast, map_airbnb
    Guides: plot_component_for_maps
    """

@ -3878,7 +3878,7 @@ class Plot(Changeable, Clearable, IOComponent, JSONSerializable):
    ):
        """
        Parameters:
-            value: Optionally, supply a default plot object to display, must be a matplotlib, plotly, or bokeh figure. If callable, the function will be called whenever the app loads to set the initial value of the component.
+            value: Optionally, supply a default plot object to display, must be a matplotlib, plotly, altair, or bokeh figure. If callable, the function will be called whenever the app loads to set the initial value of the component.
            label: component name in interface.
            show_label: if True, will display label.
            visible: If False, component will be hidden.
@ -3929,7 +3929,11 @@ class Plot(Changeable, Clearable, IOComponent, JSONSerializable):
            dtype = "bokeh"
            out_y = json.dumps(y)
        else:
-            dtype = "plotly"
+            is_altair = "altair" in y.__module__
+            if is_altair:
+                dtype = "altair"
+            else:
+                dtype = "plotly"
            out_y = y.to_json()
        return {"type": dtype, "plot": out_y}

--- a/scripts/copy_demos.py
+++ b/scripts/copy_demos.py
@ -8,6 +8,7 @@ import argparse
 def copy_all_demos(source_dir: str, dest_dir: str):
    demos_to_copy = [
        "audio_debugger",
+        "altair_plot",
        "blocks_essay",
        "blocks_js_methods",
        "blocks_layout",
@ -64,5 +65,7 @@ if __name__ == "__main__":
    opencv-python==4.6.0.66
    transformers==4.21.1
    torch==1.12.1
+    altair
+    vega_datasets
    """
    open(reqs_file_path, "w").write(textwrap.dedent(requirements))
--- a/test/requirements.in
+++ b/test/requirements.in
@ -19,4 +19,6 @@ flake8
 httpx
 pydantic
 respx
-fastapi>=0.87.0
+fastapi>=0.87.0
+altair
+vega_datasets
--- a/test/requirements.txt
+++ b/test/requirements.txt
@ -6,6 +6,8 @@
 #
 alembic==1.8.1
    # via mlflow
+altair==4.2.0
+    # via -r requirements.in
 anyio==3.6.1
    # via
    #   httpcore
@ -61,7 +63,9 @@ docker-pycreds==0.4.0
 dulwich==0.20.45
    # via comet-ml
 entrypoints==0.4
-    # via mlflow
+    # via
+    #   altair
+    #   mlflow
 everett[ini]==3.0.0
    # via comet-ml
 fastapi==0.87.0
@ -123,11 +127,15 @@ itsdangerous==2.1.2
 jedi==0.18.1
    # via ipython
 jinja2==3.1.2
-    # via flask
+    # via
+    #   altair
+    #   flask
 joblib==1.1.0
    # via scikit-learn
 jsonschema==4.7.2
-    # via comet-ml
+    # via
+    #   altair
+    #   comet-ml
 llvmlite==0.38.1
    # via numba
 mako==1.2.1
@ -150,6 +158,7 @@ numba==0.55.2
    # via shap
 numpy==1.21.6
    # via
+    #   altair
    #   imageio
    #   mlflow
    #   numba
@ -175,8 +184,10 @@ packaging==21.3
    #   transformers
 pandas==1.3.5
    # via
+    #   altair
    #   mlflow
    #   shap
+    #   vega-datasets
 parso==0.8.3
    # via jedi
 pathspec==0.9.0
@ -334,6 +345,8 @@ tomli==2.0.1
    #   black
    #   coverage
    #   pytest
+toolz==0.12.0
+    # via altair
 torch==1.12.0
    # via -r requirements.in
 tqdm==4.64.0
@ -359,6 +372,8 @@ urllib3==1.26.10
    #   dulwich
    #   requests
    #   sentry-sdk
+vega-datasets==0.9.0
+    # via -r requirements.in
 wandb==0.12.21
    # via -r requirements.in
 wcwidth==0.2.5
--- a/test/test_components.py
+++ b/test/test_components.py
@ -688,6 +688,24 @@ class TestPlot:
        component = gr.Plot(None)
        assert component.get_config().get("value") is None

+    def test_postprocess_altair(self):
+        import altair as alt
+        from vega_datasets import data
+
+        cars = data.cars()
+        chart = (
+            alt.Chart(cars)
+            .mark_point()
+            .encode(
+                x="Horsepower",
+                y="Miles_per_Gallon",
+                color="Origin",
+            )
+        )
+        out = gr.Plot().postprocess(chart)
+        assert isinstance(out["plot"], str)
+        assert out["plot"] == chart.to_json()
+

 class TestAudio:
    def test_component_functions(self):
--- a/ui/packages/app/package.json
+++ b/ui/packages/app/package.json
@ -40,6 +40,7 @@
 		"@gradio/video": "workspace:^0.0.1",
 		"d3-dsv": "^3.0.1",
 		"mime-types": "^2.1.34",
+		"svelte": "^3.25.1",
 		"svelte-i18n": "^3.3.13"
 	}
 }
--- a/ui/packages/plot/package.json
+++ b/ui/packages/plot/package.json
@ -10,6 +10,10 @@
 	"dependencies": {
 		"@gradio/icons": "workspace:^0.0.1",
 		"@gradio/utils": "workspace:^0.0.1",
-		"plotly.js-dist-min": "^2.10.1"
+		"@rollup/plugin-json": "^5.0.2",
+		"plotly.js-dist-min": "^2.10.1",
+		"svelte-vega": "^1.2.0",
+		"vega": ">=5.21.0 <6.0.0",
+		"vega-lite": "*"
 	}
 }
--- a/ui/packages/plot/src/Plot.svelte
+++ b/ui/packages/plot/src/Plot.svelte
@ -2,14 +2,21 @@
 	//@ts-nocheck
 	import Plotly from "plotly.js-dist-min";
 	import { Plot as PlotIcon } from "@gradio/icons";
+	import { Vega } from "svelte-vega";

 	import { afterUpdate, onDestroy } from "svelte";

 	export let value;
 	export let target;
+	let spec = null;
+
+	$: if(value && value['type'] == "altair") {
+		spec = JSON.parse(value['plot'])
+	}
+

 	// Plotly
-	let plotDiv;
+	let plotDiv;	
 	let plotlyGlobalStyle;

 	const main_src = "https://cdn.bokeh.org/bokeh/release/bokeh-2.4.2.min.js";
@ -109,6 +116,10 @@
 	<div bind:this={plotDiv} />
 {:else if value && value["type"] == "bokeh"}
 	<div id="bokehDiv" />
+{:else if value && value['type'] == "altair"}
+	<div class="flex justify-center items-center w-full h-full">
+	<Vega spec={spec} />
+	</div>
 {:else if value && value["type"] == "matplotlib"}
 	<div class="output-image w-full flex justify-center items-center relative">
 		<!-- svelte-ignore a11y-missing-attribute -->
--- a/ui/packages/workbench/package.json
+++ b/ui/packages/workbench/package.json
@ -42,7 +42,8 @@
 		"@gradio/tabs": "workspace:^0.0.1",
 		"@gradio/theme": "workspace:^0.0.1",
 		"@gradio/upload": "workspace:^0.0.1",
+		"@gradio/uploadbutton": "workspace:^0.0.1",
 		"@gradio/video": "workspace:^0.0.1",
-		"@gradio/uploadbutton": "workspace:^0.0.1"
+		"svelte": ">=3.44.0 <4.0.0"
 	}
 }
--- a/ui/pnpm-lock.yaml
+++ b/ui/pnpm-lock.yaml
@ -1,4 +1,4 @@
-lockfileVersion: 5.3
+lockfileVersion: 5.4

 importers:

@ -43,7 +43,7 @@ importers:
      '@tailwindcss/forms': 0.5.0_tailwindcss@3.1.6
      '@testing-library/dom': 8.11.3
      '@testing-library/svelte': 3.1.0_svelte@3.49.0
-      '@testing-library/user-event': 13.5.0_@testing-library+dom@8.11.3
+      '@testing-library/user-event': 13.5.0_gzufz4q333be4gqfrvipwvqt6a
      autoprefixer: 10.4.4_postcss@8.4.6
      babylonjs: 5.18.0
      babylonjs-loaders: 5.18.0
@ -56,13 +56,13 @@ importers:
      postcss: 8.4.6
      postcss-nested: 5.0.6_postcss@8.4.6
      prettier: 2.6.2
-      prettier-plugin-svelte: 2.7.0_prettier@2.6.2+svelte@3.49.0
+      prettier-plugin-svelte: 2.7.0_3cyj5wbackxvw67rnaarcmbw7y
      sirv: 2.0.2
      sirv-cli: 2.0.2
      svelte: 3.49.0
-      svelte-check: 2.8.0_postcss@8.4.6+svelte@3.49.0
+      svelte-check: 2.8.0_mgmdnb6x5rpawk37gozc2sbtta
      svelte-i18n: 3.3.13_svelte@3.49.0
-      svelte-preprocess: 4.10.6_62d50a01257de5eec5be08cad9d3ed66
+      svelte-preprocess: 4.10.6_mlkquajfpxs65rn6bdfntu7nmy
      tailwindcss: 3.1.6
      tinyspy: 0.3.0
      typescript: 4.7.4
@ -105,6 +105,7 @@ importers:
      '@gradio/video': workspace:^0.0.1
      d3-dsv: ^3.0.1
      mime-types: ^2.1.34
+      svelte: ^3.25.1
      svelte-i18n: ^3.3.13
    dependencies:
      '@gradio/atoms': link:../atoms
@ -133,6 +134,7 @@ importers:
      '@gradio/video': link:../video
      d3-dsv: 3.0.1
      mime-types: 2.1.34
+      svelte: 3.49.0
      svelte-i18n: 3.3.13_svelte@3.49.0

  packages/atoms:
@ -279,11 +281,19 @@ importers:
    specifiers:
      '@gradio/icons': workspace:^0.0.1
      '@gradio/utils': workspace:^0.0.1
+      '@rollup/plugin-json': ^5.0.2
      plotly.js-dist-min: ^2.10.1
+      svelte-vega: ^1.2.0
+      vega: '>=5.21.0 <6.0.0'
+      vega-lite: '*'
    dependencies:
      '@gradio/icons': link:../icons
      '@gradio/utils': link:../utils
+      '@rollup/plugin-json': 5.0.2
      plotly.js-dist-min: 2.11.1
+      svelte-vega: 1.2.0_36sthfwhgi34qytpvkzggbhnle
+      vega: 5.22.1
+      vega-lite: 5.6.0_vega@5.22.1

  packages/table:
    specifiers:
@ -372,6 +382,7 @@ importers:
      autoprefixer: ^10.4.2
      postcss: ^8.4.5
      postcss-load-config: ^3.1.1
+      svelte: '>=3.44.0 <4.0.0'
      svelte-check: ^2.2.6
      svelte-preprocess: ^4.10.1
      tailwindcss: ^3.0.12
@ -400,14 +411,15 @@ importers:
      '@gradio/upload': link:../upload
      '@gradio/uploadbutton': link:../upload-button
      '@gradio/video': link:../video
+      svelte: 3.49.0
    devDependencies:
-      '@sveltejs/adapter-auto': 1.0.0-next.89
+      '@sveltejs/adapter-auto': 1.0.0-next.90
      '@sveltejs/kit': 1.0.0-next.318_svelte@3.49.0
      autoprefixer: 10.4.2_postcss@8.4.6
      postcss: 8.4.6
      postcss-load-config: 3.1.1
-      svelte-check: 2.4.1_736abba5ed1eb6f8ecf70b1d49ead14b
-      svelte-preprocess: 4.10.2_d50790bb30dd88cc44babe7efa52bace
+      svelte-check: 2.4.1_onvlxjpnd23pr3hxbmout2wrjm
+      svelte-preprocess: 4.10.2_2udzbozq3wemyrf2xz7puuv2zy
      tailwindcss: 3.0.23_autoprefixer@10.4.2
      tslib: 2.3.1
      typescript: 4.5.5
@ -546,6 +558,18 @@ packages:
    resolution: {integrity: sha512-a5Sab1C4/icpTZVzZc5Ghpz88yQtGOyNqYXcZgOssB2uuAr+wF/MvN6bgtW32q7HHrvBki+BsZ0OuNv6EV3K9g==}
    dev: false

+  /@rollup/plugin-json/5.0.2:
+    resolution: {integrity: sha512-D1CoOT2wPvadWLhVcmpkDnesTzjhNIQRWLsc3fA49IFOP2Y84cFOOJ+nKGYedvXHKUsPeq07HR4hXpBBr+CHlA==}
+    engines: {node: '>=14.0.0'}
+    peerDependencies:
+      rollup: ^1.20.0||^2.0.0||^3.0.0
+    peerDependenciesMeta:
+      rollup:
+        optional: true
+    dependencies:
+      '@rollup/pluginutils': 5.0.2
+    dev: false
+
  /@rollup/pluginutils/4.2.1:
    resolution: {integrity: sha512-iKnFXr7NkdZAIHiIWE+BX5ULi/ucVFYWD6TbAV+rZctiRTY2PL6tsIKhoIOaoskiWAkgu+VsbXgUVDNLHf+InQ==}
    engines: {node: '>= 8.0.0'}
@ -553,10 +577,24 @@ packages:
      estree-walker: 2.0.2
      picomatch: 2.3.1

-  /@sveltejs/adapter-auto/1.0.0-next.89:
-    resolution: {integrity: sha512-S+sASFX4sSZD1xEKmZ3zHxQh2DGxXBUpCGAtUakKkI2MRvFIm+zYIm+7GPekofMLd19FjdFDKkuOjBKPdmA8+w==}
+  /@rollup/pluginutils/5.0.2:
+    resolution: {integrity: sha512-pTd9rIsP92h+B6wWwFbW8RkZv4hiR/xKsqre4SIuAOaOEQRxi0lqLke9k2/7WegC85GgUs9pjmOjCUi3In4vwA==}
+    engines: {node: '>=14.0.0'}
+    peerDependencies:
+      rollup: ^1.20.0||^2.0.0||^3.0.0
+    peerDependenciesMeta:
+      rollup:
+        optional: true
    dependencies:
-      import-meta-resolve: 2.1.0
+      '@types/estree': 1.0.0
+      estree-walker: 2.0.2
+      picomatch: 2.3.1
+    dev: false
+
+  /@sveltejs/adapter-auto/1.0.0-next.90:
+    resolution: {integrity: sha512-qxH46Oqqn40998wTmnbffONI0HcW/kiZ3OIjZoysjONne+LU4uEsG425MZ2RHDxmR04zxhsdjCAsn6B4du8D7w==}
+    dependencies:
+      import-meta-resolve: 2.2.0
    dev: true

  /@sveltejs/kit/1.0.0-next.318_svelte@3.49.0:
@ -671,7 +709,7 @@ packages:
      svelte: 3.49.0
    dev: false

-  /@testing-library/user-event/13.5.0_@testing-library+dom@8.11.3:
+  /@testing-library/user-event/13.5.0_gzufz4q333be4gqfrvipwvqt6a:
    resolution: {integrity: sha512-5Kwtbo3Y/NowpkbRuSepbyMFkZmHgD+vPzYB/RJ4oxt5Gj/avFFBYjhw27cqSVPVw/3a67NK1PbiIr9k4Gwmdg==}
    engines: {node: '>=10', npm: '>=6'}
    peerDependencies:
@ -695,6 +733,10 @@ packages:
    resolution: {integrity: sha512-/zPMqDkzSZ8t3VtxOa4KPq7uzzW978M9Tvh+j7GHKuo6k6GTLxPJ4J5gE5cjfJ26pnXst0N5Hax8Sr0T2Mi9zQ==}
    dev: false

+  /@types/clone/2.1.1:
+    resolution: {integrity: sha512-BZIU34bSYye0j/BFcPraiDZ5ka6MJADjcDVELGf7glr9K+iE8NYVjFslJFVWzskSxkLLyCrSPScE82/UUoBSvg==}
+    dev: false
+
  /@types/concat-stream/1.6.1:
    resolution: {integrity: sha512-eHE4cQPoj6ngxBZMvVf6Hw7Mh4jMW4U9lpGmS5GBPB9RYxlFg+CHaVN7ErNY4W9XfLIEn20b4VDYaIrbq0q4uA==}
    dependencies:
@ -724,6 +766,14 @@ packages:
    resolution: {integrity: sha512-sZLCdHvBUcNby1cB6Fd3ZBrABbjz3v1Vm90nysCQ6Vt7vd6e/h9Lt7SiJUoEX0l4Dzc7P5llKyhqSi1ycSf1Hg==}
    dev: true

+  /@types/estree/0.0.50:
+    resolution: {integrity: sha512-C6N5s2ZFtuZRj54k2/zyRhNDjJwwcViAM3Nbm8zjBpbqAdZ00mr0CFxvSKeO8Y/e03WVFLpQMdHYVfUd6SB+Hw==}
+    dev: false
+
+  /@types/estree/1.0.0:
+    resolution: {integrity: sha512-WulqXMDUTYAXCjZnk6JtIHPigp55cVtDgDrO2gHRwhyJto21+1zbVCtOYB2L1F9w4qCQ0rOGWBnBe0FNTiEJIQ==}
+    dev: false
+
  /@types/form-data/0.0.33:
    resolution: {integrity: sha1-yayFsqX9GENbjIXZ7LUObWyJP/g=}
    dependencies:
@ -1072,6 +1122,20 @@ packages:
    optionalDependencies:
      fsevents: 2.3.2

+  /cliui/8.0.1:
+    resolution: {integrity: sha512-BSeNnyus75C4//NQ9gQt1/csTXyo/8Sb+afLAkzAptFuMsod9HFokGNudZpi/oQV73hnVK+sR+5PVRMd+Dr7YQ==}
+    engines: {node: '>=12'}
+    dependencies:
+      string-width: 4.2.3
+      strip-ansi: 6.0.1
+      wrap-ansi: 7.0.0
+    dev: false
+
+  /clone/2.1.2:
+    resolution: {integrity: sha512-3Pe/CF1Nn94hyhIYpjtiLhdCoEoz0DqQ+988E9gmeEdQZlojxnOb74wctFyuwWQHzqyf9X7C7MG8juUpqBJT8w==}
+    engines: {node: '>=0.8'}
+    dev: false
+
  /color-convert/1.9.3:
    resolution: {integrity: sha512-QfAUtd+vFdAtFQcC8CCyYt1fYWxSqAiK2cSD6zDB8N3cpsEBAvRxp9zOGg6G/SHHJYAT88/az/IuDGALsNVbGg==}
    dependencies:
@ -1096,6 +1160,10 @@ packages:
      delayed-stream: 1.0.0
    dev: false

+  /commander/2.20.3:
+    resolution: {integrity: sha512-GpVkmM8vF2vQUkj2LvZmD35JxeJOLCwJ9cUkugyk2nuhbv3+mJvpLYYt+0+USMxE+oj+ey/lJEnhZw75x/OMcQ==}
+    dev: false
+
  /commander/7.2.0:
    resolution: {integrity: sha512-QrWXB+ZQSVPmIWIhtEO9H+gwHaMGYiF5ChvoJ+K9ZGHG/sVsa6yiesAD1GC/x46sET00Xlwo1u49RVVVzvcSkw==}
    engines: {node: '>= 10'}
@ -1200,6 +1268,18 @@ packages:
    engines: {node: '>=12'}
    dev: false

+  /d3-delaunay/6.0.2:
+    resolution: {integrity: sha512-IMLNldruDQScrcfT+MWnazhHbDJhcRJyOEBAJfwQnHle1RPh6WDuLvxNArUju2VSMSUuKlY5BGHRJ2cYyoFLQQ==}
+    engines: {node: '>=12'}
+    dependencies:
+      delaunator: 5.0.0
+    dev: false
+
+  /d3-dispatch/3.0.1:
+    resolution: {integrity: sha512-rzUyPU/S7rwUflMyLc1ETDeBj0NRuHKKAcvukozwhshr6g6c5d8zh4c2gQjY2bZ0dXeGLWc1PF174P2tVvKhfg==}
+    engines: {node: '>=12'}
+    dev: false
+
  /d3-dsv/3.0.1:
    resolution: {integrity: sha512-UG6OvdI5afDIFP9w4G0mNq50dSOsXHJaRE8arAS5o9ApWnIElp8GZw1Dun8vP8OyHOZ/QJUKUJwxiiCCnUwm+Q==}
    engines: {node: '>=12'}
@ -1210,11 +1290,42 @@ packages:
      rw: 1.3.3
    dev: false

+  /d3-force/3.0.0:
+    resolution: {integrity: sha512-zxV/SsA+U4yte8051P4ECydjD/S+qeYtnaIyAs9tgHCqfguma/aAQDjo85A9Z6EKhBirHRJHXIgJUlffT4wdLg==}
+    engines: {node: '>=12'}
+    dependencies:
+      d3-dispatch: 3.0.1
+      d3-quadtree: 3.0.1
+      d3-timer: 3.0.1
+    dev: false
+
  /d3-format/3.1.0:
    resolution: {integrity: sha512-YyUI6AEuY/Wpt8KWLgZHsIU86atmikuoOmCfommt0LYHiQSPjvX2AcFc38PX0CBpr2RCyZhjex+NS/LPOv6YqA==}
    engines: {node: '>=12'}
    dev: false

+  /d3-geo-projection/4.0.0:
+    resolution: {integrity: sha512-p0bK60CEzph1iqmnxut7d/1kyTmm3UWtPlwdkM31AU+LW+BXazd5zJdoCn7VFxNCHXRngPHRnsNn5uGjLRGndg==}
+    engines: {node: '>=12'}
+    hasBin: true
+    dependencies:
+      commander: 7.2.0
+      d3-array: 3.1.1
+      d3-geo: 3.0.1
+    dev: false
+
+  /d3-geo/3.0.1:
+    resolution: {integrity: sha512-Wt23xBych5tSy9IYAM1FR2rWIBFWa52B/oF/GYe5zbdHrg08FU8+BuI6X4PvTwPDdqdAdq04fuWJpELtsaEjeA==}
+    engines: {node: '>=12'}
+    dependencies:
+      d3-array: 3.1.1
+    dev: false
+
+  /d3-hierarchy/3.1.2:
+    resolution: {integrity: sha512-FX/9frcub54beBdugHjDCdikxThEqjnR93Qt7PvQTOHxyiNCAlvMrHhclk3cD5VeAaq9fxmfRp+CnWw9rEMBuA==}
+    engines: {node: '>=12'}
+    dev: false
+
  /d3-interpolate/3.0.1:
    resolution: {integrity: sha512-3bYs1rOD33uo8aqJfKP3JWPAibgw8Zm2+L9vBKEHJ2Rg+viTR7o5Mmv5mZcieN+FRYaAOWX5SJATX6k1PWz72g==}
    engines: {node: '>=12'}
@ -1227,6 +1338,11 @@ packages:
    engines: {node: '>=12'}
    dev: false

+  /d3-quadtree/3.0.1:
+    resolution: {integrity: sha512-04xDrxQTDTCFwP5H6hRhsRcb9xxv2RzkcsygFzmkSIOJy3PeRJP7sNk3VRIbKXcog561P9oU0/rVH6vDROAgUw==}
+    engines: {node: '>=12'}
+    dev: false
+
  /d3-scale/4.0.2:
    resolution: {integrity: sha512-GZW464g1SH7ag3Y7hXjf8RoUuAFIqklOAq3MRl4OaWabTFJY9PN/E1YklhXLh+OQ3fM9yS2nOkCoS+WLZ6kvxQ==}
    engines: {node: '>=12'}
@ -1259,6 +1375,11 @@ packages:
      d3-array: 3.1.1
    dev: false

+  /d3-timer/3.0.1:
+    resolution: {integrity: sha512-ndfJ/JxxMd3nw31uyKoY2naivF+r29V+Lc0svZxe1JvvIRmi8hUsrMvdOwgS1o6uBHmiz91geQ0ylPP0aj1VUA==}
+    engines: {node: '>=12'}
+    dev: false
+
  /dashify/2.0.0:
    resolution: {integrity: sha512-hpA5C/YrPjucXypHPPc0oJ1l9Hf6wWbiOL7Ik42cxnsUOhWiCB/fylKbKqqJalW9FgkNQCw16YO8uW9Hs0Iy1A==}
    engines: {node: '>=4'}
@ -1296,6 +1417,12 @@ packages:
  /defined/1.0.0:
    resolution: {integrity: sha512-Y2caI5+ZwS5c3RiNDJ6u53VhQHv+hHKwhkI1iHvceKUHw9Df6EK2zRLfjejRgMuCuxK7PfSWIMwWecceVvThjQ==}

+  /delaunator/5.0.0:
+    resolution: {integrity: sha512-AyLvtyJdbv/U1GkiS6gUUzclRoAY4Gs75qkMygJJhU75LW4DNuSF2RMzpxs9jw9Oz1BobHjTdkG3zdP55VxAqw==}
+    dependencies:
+      robust-predicates: 3.0.1
+    dev: false
+
  /delayed-stream/1.0.0:
    resolution: {integrity: sha1-3zrhmayt+31ECqrgsp4icrJOxhk=}
    engines: {node: '>=0.4.0'}
@ -1375,6 +1502,10 @@ packages:
    resolution: {integrity: sha512-EVTZ+igi8x63pK4bPuA95PXIs2b2Cowi3WQwI9f9qManLiZJOD1Lash1J3W4TvvcUCcIR4o/rgi9o8UicXSO+w==}
    dev: false

+  /emoji-regex/8.0.0:
+    resolution: {integrity: sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A==}
+    dev: false
+
  /entities/2.2.0:
    resolution: {integrity: sha512-p92if5Nz619I0w+akJrLZH0MX0Pb5DX39XOwQTtXSdQQOaYH03S1uIQp4mhOZtAXrxq4ViO67YTiLBo2638o9A==}
    dev: false
@ -1658,6 +1789,10 @@ packages:
      tslib: 2.4.0
    dev: false

+  /fast-deep-equal/3.1.3:
+    resolution: {integrity: sha512-f3qQ9oQy9j2AhBe/H9VC91wLmKBCCU/gDOnKNAYG5hswO7BLKj09Hc5HYNz9cGI++xlpDCIgDaitVs03ATR84Q==}
+    dev: false
+
  /fast-glob/3.2.11:
    resolution: {integrity: sha512-xrO3+1bxSo3ZVHAnqzyuewYT6aMFHRAd4Kcs92MAonjwQZLsK9d0SF1IyQ3k5PoirxTW0Oe/RqFgMQ6TcNE5Ew==}
    engines: {node: '>=8.6.0'}
@ -1668,6 +1803,14 @@ packages:
      merge2: 1.4.1
      micromatch: 4.0.4

+  /fast-json-patch/3.1.1:
+    resolution: {integrity: sha512-vf6IHUX2SBcA+5/+4883dsIjpBTqmfBjmYiWK1savxQmFk4JfBMLa7ynTYOs1Rolp/T1betJxHiGD3g1Mn8lUQ==}
+    dev: false
+
+  /fast-json-stable-stringify/2.1.0:
+    resolution: {integrity: sha512-lhd/wF+Lk98HZoTCtlVraHtfh5XYijIjalXck7saUtuanSDyLMxnHhSXEDJqHxD7msR8D0uCmqlkwjCV8xvwHw==}
+    dev: false
+
  /fast-unique-numbers/6.0.21:
    resolution: {integrity: sha512-MW8UAAypyhNtbnMlSch9EiEAuiMo1y6O02WzI5mcHAzvirdIm/hXMVp4QH9ijWnU1xzW23GXk6Bf+5B1kv9hzw==}
    engines: {node: '>=12.20.1'}
@ -1717,6 +1860,11 @@ packages:
  /function-bind/1.1.1:
    resolution: {integrity: sha512-yIovAzMX49sF8Yl58fSCWJ5svSLuaibPxXQJFLmBObTuCr0Mf1KiPopGM9NiFjiYBCbfaa2Fh6breQ6ANVTI0A==}

+  /get-caller-file/2.0.5:
+    resolution: {integrity: sha512-DyFP3BM/3YHTQOCUL/w0OZHR0lpKeGrxotcHWcqNEdnltqFwXVfhEBQ94eIo34AfQpo0rGki4cyIiftY06h2Fg==}
+    engines: {node: 6.* || 8.* || >= 10.*}
+    dev: false
+
  /get-func-name/2.0.0:
    resolution: {integrity: sha1-6td0q+5y4gQJQzoGY2YCPdaIekE=}
    dev: false
@ -1865,8 +2013,8 @@ packages:
      parent-module: 1.0.1
      resolve-from: 4.0.0

-  /import-meta-resolve/2.1.0:
-    resolution: {integrity: sha512-yG9pxkWJVTy4cmRsNWE3ztFdtFuYIV8G4N+cbCkO8b+qngkLyIUhxQFuZ0qJm67+0nUOxjMPT7nfksPKza1v2g==}
+  /import-meta-resolve/2.2.0:
+    resolution: {integrity: sha512-CpPOtiCHxP9HdtDM5F45tNiAe66Cqlv3f5uHoJjt+KlaLrUh9/Wz9vepADZ78SlqEo62aDWZtj9ydMGXV+CPnw==}
    dev: true

  /indefinite-article/0.0.2:
@ -1955,6 +2103,11 @@ packages:
    resolution: {integrity: sha512-SbKbANkN603Vi4jEZv49LeVJMn4yGwsbzZworEoyEiutsN3nJYdbO36zfhGJ6QEDpOZIFkDtnq5JRxmvl3jsoQ==}
    engines: {node: '>=0.10.0'}

+  /is-fullwidth-code-point/3.0.0:
+    resolution: {integrity: sha512-zymm5+u+sCsSWyD9qNaejV3DFvhCKclKdizYaJUuHA83RLjb7nSuGnddCHGv0hk+KY7BMAlsWeK4Ueg6EV6XQg==}
+    engines: {node: '>=8'}
+    dev: false
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    dev: true

+  /json-stringify-pretty-compact/3.0.0:
+    resolution: {integrity: sha512-Rc2suX5meI0S3bfdZuA7JMFBGkJ875ApfVyq2WHELjBiiG22My/l7/8zPpH/CfFVQHuVLd8NLR0nv6vi0BYYKA==}
+    dev: false
+
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    engines: {node: '>=6'}
@ -2076,6 +2233,13 @@ packages:
      get-func-name: 2.0.0
    dev: false

+  /lru-cache/6.0.0:
+    resolution: {integrity: sha512-Jo6dJ04CmSjuznwJSS3pUeWmd/H0ffTlkXXgwZi+eq1UCmqQwCh+eLsYOYCwY991i2Fah4h1BEMCx4qThGbsiA==}
+    engines: {node: '>=10'}
+    dependencies:
+      yallist: 4.0.0
+    dev: false
+
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    hasBin: true
@ -2534,7 +2698,7 @@ packages:
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      source-map-js: 1.0.2

-  /prettier-plugin-svelte/2.7.0_prettier@2.6.2+svelte@3.49.0:
+  /prettier-plugin-svelte/2.7.0_3cyj5wbackxvw67rnaarcmbw7y:
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    peerDependencies:
      prettier: ^1.16.4 || ^2.0.0
@ -2657,6 +2821,11 @@ packages:
    engines: {node: '>=6'}
    dev: false

+  /require-directory/2.1.1:
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+    engines: {node: '>=0.10.0'}
+    dev: false
+
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    dev: false
@ -2692,6 +2861,10 @@ packages:
    dependencies:
      glob: 7.2.0

+  /robust-predicates/3.0.1:
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+    dev: false
+
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    engines: {node: '>=10.0.0'}
@ -2744,6 +2917,14 @@ packages:
    hasBin: true
    dev: false

+  /semver/7.3.8:
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+    engines: {node: '>=10'}
+    hasBin: true
+    dependencies:
+      lru-cache: 6.0.0
+    dev: false
+
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    engines: {node: '>=0.10.0'}
@ -2843,6 +3024,15 @@ packages:
      tslib: 2.4.0
    dev: false

+  /string-width/4.2.3:
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+    engines: {node: '>=8'}
+    dependencies:
+      emoji-regex: 8.0.0
+      is-fullwidth-code-point: 3.0.0
+      strip-ansi: 6.0.1
+    dev: false
+
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    engines: {node: '>= 0.4'}
@ -2872,6 +3062,13 @@ packages:
      safe-buffer: 5.1.2
    dev: false

+  /strip-ansi/6.0.1:
+    resolution: {integrity: sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A==}
+    engines: {node: '>=8'}
+    dependencies:
+      ansi-regex: 5.0.1
+    dev: false
+
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    resolution: {integrity: sha1-IzTBjpx1n3vdVv3vfprj1YjmjtM=}
    engines: {node: '>=4'}
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    engines: {node: '>= 0.4'}

-  /svelte-check/2.4.1_736abba5ed1eb6f8ecf70b1d49ead14b:
+  /svelte-check/2.4.1_onvlxjpnd23pr3hxbmout2wrjm:
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    peerDependencies:
@ -2921,7 +3118,7 @@ packages:
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      source-map: 0.7.3
      svelte: 3.49.0
-      svelte-preprocess: 4.10.2_d50790bb30dd88cc44babe7efa52bace
+      svelte-preprocess: 4.10.2_2udzbozq3wemyrf2xz7puuv2zy
      typescript: 4.5.5
    transitivePeerDependencies:
      - '@babel/core'
@ -2936,7 +3133,7 @@ packages:
      - sugarss
    dev: true

-  /svelte-check/2.8.0_postcss@8.4.6+svelte@3.49.0:
+  /svelte-check/2.8.0_mgmdnb6x5rpawk37gozc2sbtta:
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    hasBin: true
    peerDependencies:
@ -2949,7 +3146,7 @@ packages:
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      sade: 1.8.1
      svelte: 3.49.0
-      svelte-preprocess: 4.10.6_62d50a01257de5eec5be08cad9d3ed66
+      svelte-preprocess: 4.10.6_mlkquajfpxs65rn6bdfntu7nmy
      typescript: 4.7.4
    transitivePeerDependencies:
      - '@babel/core'
@ -2987,7 +3184,7 @@ packages:
      tiny-glob: 0.2.9
    dev: false

-  /svelte-preprocess/4.10.2_d50790bb30dd88cc44babe7efa52bace:
+  /svelte-preprocess/4.10.2_2udzbozq3wemyrf2xz7puuv2zy:
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    engines: {node: '>= 9.11.2'}
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@ -3040,7 +3237,7 @@ packages:
      typescript: 4.5.5
    dev: true

-  /svelte-preprocess/4.10.6_62d50a01257de5eec5be08cad9d3ed66:
+  /svelte-preprocess/4.10.6_mlkquajfpxs65rn6bdfntu7nmy:
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    dev: false

+  /svelte-vega/1.2.0_36sthfwhgi34qytpvkzggbhnle:
+    resolution: {integrity: sha512-MsDdO+l7o/d9d4mVkh8MBDhqZvJ45lpuprBaTj0V/ZilIG902QERHFQlam3ZFcR9C9OIKSpmPqINssWNPkDdcA==}
+    peerDependencies:
+      vega: '*'
+      vega-lite: '*'
+    dependencies:
+      fast-deep-equal: 3.1.3
+      vega: 5.22.1
+      vega-embed: 6.21.0_36sthfwhgi34qytpvkzggbhnle
+      vega-lite: 5.6.0_vega@5.22.1
+    dev: false
+
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    resolution: {integrity: sha512-+lmjic1pApJWDfPCpUUTc1m8azDqYCG1JN9YEngrx/hUyIcFJo6VZhj0A1Ai0wqoHcEIuQy+e9tk+4uDgdtsFA==}
    engines: {node: '>= 8'}
@ -3229,6 +3438,13 @@ packages:
    dependencies:
      is-number: 7.0.0

+  /topojson-client/3.1.0:
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+    hasBin: true
+    dependencies:
+      commander: 2.20.3
+    dev: false
+
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    engines: {node: '>=6'}
@ -3292,6 +3508,392 @@ packages:
      spdx-expression-parse: 3.0.1
    dev: false

+  /vega-canvas/1.2.6:
+    resolution: {integrity: sha512-rgeYUpslYn/amIfnuv3Sw6n4BGns94OjjZNtUc9IDji6b+K8LGS/kW+Lvay8JX/oFqtulBp8RLcHN6QjqPLA9Q==}
+    dev: false
+
+  /vega-crossfilter/4.1.0:
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+    dependencies:
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+      vega-dataflow: 5.7.4
+      vega-util: 1.17.0
+    transitivePeerDependencies:
+      - encoding
+    dev: false
+
+  /vega-dataflow/5.7.4:
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+    dependencies:
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+      vega-loader: 4.5.0
+      vega-util: 1.17.0
+    transitivePeerDependencies:
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+    dev: false
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+  /vega-embed/6.21.0_36sthfwhgi34qytpvkzggbhnle:
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+    peerDependencies:
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+      vega-lite: '*'
+    dependencies:
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+      json-stringify-pretty-compact: 3.0.0
+      semver: 7.3.8
+      tslib: 2.4.0
+      vega: 5.22.1
+      vega-interpreter: 1.0.4
+      vega-lite: 5.6.0_vega@5.22.1
+      vega-schema-url-parser: 2.2.0
+      vega-themes: 2.12.0_36sthfwhgi34qytpvkzggbhnle
+      vega-tooltip: 0.28.0
+    dev: false
+    bundledDependencies:
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+  /vega-encode/4.9.0:
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+      d3-interpolate: 3.0.1
+      vega-dataflow: 5.7.4
+      vega-scale: 7.2.0
+      vega-util: 1.17.0
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+    dev: false
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+  /vega-event-selector/3.0.0:
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+    dependencies:
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+    dev: false
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+  /vega-force/4.1.0:
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+  /vega-format/1.1.0:
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+      d3-format: 3.1.0
+      d3-time-format: 4.1.0
+      vega-time: 2.1.0
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+      d3-color: 3.0.1
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+      vega-expression: 5.0.0
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+      vega-scenegraph: 4.10.1
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+    engines: {node: '>=12'}
+    hasBin: true
+    peerDependencies:
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