Upload folder using huggingface_hub

requirements.txt

@@ -1,3 +1,3 @@
-gradio-client @ git+https://github.com/gradio-app/gradio@120198fe2da2ded9e8f27549b9dfd1cd81992ec4#subdirectory=client/python
-https://gradio-pypi-previews.s3.amazonaws.com/120198fe2da2ded9e8f27549b9dfd1cd81992ec4/gradio-5.4.0-py3-none-any.whl
+gradio-client @ git+https://github.com/gradio-app/gradio@d1cfe1e9defa06f927aec2671656fe77514dd0fa#subdirectory=client/python
+https://gradio-pypi-previews.s3.amazonaws.com/d1cfe1e9defa06f927aec2671656fe77514dd0fa/gradio-5.4.0-py3-none-any.whl
 vega_datasets

run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: scatterplot_component"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio vega_datasets"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from vega_datasets import data\n", "\n", "cars = data.cars()\n", "\n", "with gr.Blocks() as demo:\n", "    gr.ScatterPlot(\n", "        value=cars,\n", "        x=\"Horsepower\",\n", "        y=\"Miles_per_Gallon\",\n", "        color=\"Origin\",\n", "        tooltip=\"Name\",\n", "        title=\"Car Data\",\n", "        y_title=\"Miles per Gallon\",\n", "        color_legend_title=\"Origin of Car\",\n", "        container=False,\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: scatterplot_component"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio vega_datasets"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from vega_datasets import data\n", "\n", "cars = data.cars()\n", "\n", "with gr.Blocks() as demo:\n", "    gr.ScatterPlot(\n", "        value=cars,\n", "        x=\"Horsepower\",\n", "        y=\"Miles_per_Gallon\",\n", "        color=\"Origin\",\n", "        tooltip=[\"Name\"],\n", "        title=\"Car Data\",\n", "        y_title=\"Miles per Gallon\",\n", "        color_legend_title=\"Origin of Car\",\n", "        container=False,\n", "    )\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -9,7 +9,7 @@ with gr.Blocks() as demo:
         x="Horsepower",
         y="Miles_per_Gallon",
         color="Origin",
-        tooltip="Name",
+        tooltip=["Name"],
         title="Car Data",
         y_title="Miles per Gallon",
         color_legend_title="Origin of Car",