Upload folder using huggingface_hub

README.md

@@ -5,7 +5,7 @@ emoji: 🔥
 colorFrom: indigo
 colorTo: indigo
 sdk: gradio
-sdk_version: 5.45.0
+sdk_version: 5.46.0
 app_file: run.py
 pinned: false
 hf_oauth: true

run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: dataframe_events"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import pandas as pd\n", "import numpy as np\n", "\n", "def update_dataframe():\n", "    regular_df = pd.DataFrame(np.random.randint(1, 10, size=(5, 5)), columns=pd.Index([str(i) for i in range(5)]))\n", "    wide_df = pd.DataFrame([\n", "        [5, 22, 91, 17, 73, 38, 84, 46, 65, 10, 155, 122, 11, 144, 133],\n", "        [81, 42, 13, 97, 33, 77, 59, 100, 29, 61, 213, 195, 142, 118, 127],\n", "        [37, 71, 63, 102, 28, 94, 19, 55, 88, 44, 116, 139, 122, 150, 147],\n", "        [104, 52, 49, 26, 83, 67, 31, 92, 79, 18, 241, 115, 159, 123, 137],\n", "        [16, 95, 74, 68, 43, 101, 27, 85, 39, 57, 129, 148, 132, 111, 156]\n", "    ], columns=pd.Index([f\"col_{i}\" for i in range(15)]))\n", "    return regular_df, wide_df\n", "\n", "def clear_dataframes():\n", "    regular_empty_df = pd.DataFrame([], columns=pd.Index([str(i) for i in range(5)]))\n", "    wide_empty_df = pd.DataFrame([], columns=pd.Index([f\"col_{i}\" for i in range(15)]))\n", "    return regular_empty_df, wide_empty_df\n", "\n", "def increment_select_counter(evt: gr.SelectData, count):\n", "    count_val = 1 if count is None else count + 1\n", "    return count_val, evt.index, evt.value\n", "\n", "with gr.Blocks() as demo:\n", "    with gr.Row():\n", "        with gr.Column(scale=1):\n", "            initial_regular_df = pd.DataFrame(np.zeros((5, 5), dtype=int), columns=pd.Index([str(i) for i in range(5)]))\n", "\n", "            df = gr.Dataframe(\n", "                value=initial_regular_df,\n", "                interactive=True,\n", "                label=\"Interactive Dataframe\",\n", "                show_label=True,\n", "                elem_id=\"dataframe\",\n", "                show_search=\"filter\",\n", "                show_copy_button=True,\n", "                show_row_numbers=True,\n", "                static_columns=[4]\n", "            )\n", "\n", "        with gr.Column(scale=1):\n", "            initial_wide_df = pd.DataFrame(np.zeros((5, 15), dtype=int), columns=pd.Index([f\"col_{i}\" for i in range(15)]))\n", "\n", "            df_view = gr.Dataframe(\n", "                value=initial_wide_df,\n", "                interactive=False,\n", "                label=\"Non-Interactive View (Scroll Horizontally)\",\n", "                show_label=True,\n", "                show_search=\"search\",\n", "                elem_id=\"non-interactive-dataframe\",\n", "                show_copy_button=True,\n", "                show_row_numbers=True,\n", "                show_fullscreen_button=True,\n", "            )\n", "\n", "    tall_df_value = [\n", "        [\"DeepSeek Coder\", 79.3, True],\n", "        [\"Llama 3.3\", 68.9, True],\n", "        [\"Qwen 2.5\", 61.9, True],\n", "        [\"Gemma 2\", 59.5, False],\n", "        [\"GPT 2\", 18.3, False],\n", "    ]\n", "\n", "    def get_display_value(values):\n", "        display_values = []\n", "        medals = [\"\ud83e\udd47\", \"\ud83e\udd48\", \"\ud83e\udd49\"]\n", "        for i, row in enumerate(values):\n", "            if i < 3:\n", "                display_values.append([f\"{medals[i]} {row[0]}\", row[1]])\n", "            else:\n", "                display_values.append([row[0], row[1]])\n", "        return display_values\n", "\n", "    display_value = get_display_value(tall_df_value)\n", "\n", "    tall_df_value = {\n", "        \"data\": tall_df_value,\n", "        \"headers\": [\"Model\", \"% Correct (LeetCode Hard)\", \"Is Open Source\"],\n", "        \"metadata\": {\n", "            \"display_value\": display_value\n", "        }\n", "    }\n", "\n", "    with gr.Row():\n", "        with gr.Column():\n", "            df_tall = gr.Dataframe(\n", "                value=tall_df_value,\n", "                interactive=False,\n", "                label=\"Tall Dataframe (Scroll Vertically)\",\n", "                datatype=[\"str\", \"number\", \"bool\"],\n", "                max_height=200,\n", "                show_label=True,\n", "                elem_id=\"dataframe_tall\",\n", "                show_copy_button=True,\n", "                show_row_numbers=True,\n", "                show_search=\"search\",\n", "            )\n", "\n", "            df_tall_selected_cell_index = gr.Textbox(\n", "                label=\"Tall dataframe selected cell index\", elem_id=\"tall_selected_cell_index\"\n", "            )\n", "            df_tall_selected_cell_value = gr.Textbox(\n", "                label=\"Tall dataframe selected cell value\", elem_id=\"tall_selected_cell_value\"\n", "            )\n", "\n", "    with gr.Row():\n", "        with gr.Column():\n", "            update_btn = gr.Button(\"Update dataframe\", elem_id=\"update_btn\")\n", "            clear_btn = gr.Button(\"Clear dataframe\", elem_id=\"clear_btn\")\n", "\n", "    with gr.Row():\n", "        change_events = gr.Number(\n", "            value=0, label=\"Change events\", elem_id=\"change_events\"\n", "        )\n", "        input_events = gr.Number(value=0, label=\"Input events\", elem_id=\"input_events\")\n", "        select_events = gr.Number(\n", "            value=0, label=\"Select events\", elem_id=\"select_events\"\n", "        )\n", "\n", "    with gr.Row():\n", "        selected_cell_index = gr.Textbox(\n", "            label=\"Selected cell index\", elem_id=\"selected_cell_index\"\n", "        )\n", "        selected_cell_value = gr.Textbox(\n", "            label=\"Selected cell value\", elem_id=\"selected_cell_value\"\n", "        )\n", "\n", "    update_btn.click(fn=update_dataframe, outputs=[df, df_view])\n", "    clear_btn.click(fn=clear_dataframes, outputs=[df, df_view, df_tall])\n", "    df.change(fn=lambda x: x + 1, inputs=[change_events], outputs=[change_events])\n", "    df.input(fn=lambda x: x + 1, inputs=[input_events], outputs=[input_events])\n", "    df.select(\n", "        fn=increment_select_counter,\n", "        inputs=[select_events],\n", "        outputs=[select_events, selected_cell_index, selected_cell_value],\n", "    )\n", "\n", "    df_tall.select(\n", "        fn=increment_select_counter,\n", "        inputs=[select_events],\n", "        outputs=[select_events, df_tall_selected_cell_index, df_tall_selected_cell_value],\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: dataframe_events"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import pandas as pd\n", "import numpy as np\n", "\n", "def update_dataframe():\n", "    regular_df = pd.DataFrame(np.random.randint(1, 10, size=(5, 5)), columns=pd.Index([str(i) for i in range(5)]))\n", "    wide_df = pd.DataFrame([\n", "        [5, 22, 91, 17, 73, 38, 84, 46, 65, 10, 155, 122, 11, 144, 133],\n", "        [81, 42, 13, 97, 33, 77, 59, 100, 29, 61, 213, 195, 142, 118, 127],\n", "        [37, 71, 63, 102, 28, 94, 19, 55, 88, 44, 116, 139, 122, 150, 147],\n", "        [104, 52, 49, 26, 83, 67, 31, 92, 79, 18, 241, 115, 159, 123, 137],\n", "        [16, 95, 74, 68, 43, 101, 27, 85, 39, 57, 129, 148, 132, 111, 156]\n", "    ], columns=pd.Index([f\"col_{i}\" for i in range(15)]))\n", "    return regular_df, wide_df\n", "\n", "def clear_dataframes():\n", "    regular_empty_df = pd.DataFrame([], columns=pd.Index([str(i) for i in range(5)]))\n", "    wide_empty_df = pd.DataFrame([], columns=pd.Index([f\"col_{i}\" for i in range(15)]))\n", "    return regular_empty_df, wide_empty_df\n", "\n", "def increment_select_counter(evt: gr.SelectData, count):\n", "    count_val = 1 if count is None else count + 1\n", "    return count_val, evt.index, evt.value\n", "\n", "def edit_dataframe(evt: gr.EditData, count):\n", "    event_data = \", \".join([\n", "        f\"index: {evt.index}\",\n", "        f\"value: {evt.value}\",\n", "        f\"previous_value: {evt.previous_value}\",\n", "    ])\n", "    return event_data, count + 1\n", "\n", "with gr.Blocks() as demo:\n", "    with gr.Row():\n", "        with gr.Column(scale=1):\n", "            initial_regular_df = pd.DataFrame(np.zeros((5, 5), dtype=int), columns=pd.Index([str(i) for i in range(5)]))\n", "\n", "            df = gr.Dataframe(\n", "                value=initial_regular_df,\n", "                interactive=True,\n", "                label=\"Interactive Dataframe\",\n", "                show_label=True,\n", "                elem_id=\"dataframe\",\n", "                show_search=\"filter\",\n", "                show_copy_button=True,\n", "                show_row_numbers=True,\n", "                static_columns=[4]\n", "            )\n", "\n", "        with gr.Column(scale=1):\n", "            initial_wide_df = pd.DataFrame(np.zeros((5, 15), dtype=int), columns=pd.Index([f\"col_{i}\" for i in range(15)]))\n", "\n", "            df_view = gr.Dataframe(\n", "                value=initial_wide_df,\n", "                interactive=False,\n", "                label=\"Non-Interactive View (Scroll Horizontally)\",\n", "                show_label=True,\n", "                show_search=\"search\",\n", "                elem_id=\"non-interactive-dataframe\",\n", "                show_copy_button=True,\n", "                show_row_numbers=True,\n", "                show_fullscreen_button=True,\n", "            )\n", "\n", "    tall_df_value = [\n", "        [\"DeepSeek Coder\", 79.3, True],\n", "        [\"Llama 3.3\", 68.9, True],\n", "        [\"Qwen 2.5\", 61.9, True],\n", "        [\"Gemma 2\", 59.5, False],\n", "        [\"GPT 2\", 18.3, False],\n", "    ]\n", "\n", "    def get_display_value(values):\n", "        display_values = []\n", "        medals = [\"\ud83e\udd47\", \"\ud83e\udd48\", \"\ud83e\udd49\"]\n", "        for i, row in enumerate(values):\n", "            if i < 3:\n", "                display_values.append([f\"{medals[i]} {row[0]}\", row[1]])\n", "            else:\n", "                display_values.append([row[0], row[1]])\n", "        return display_values\n", "\n", "    display_value = get_display_value(tall_df_value)\n", "\n", "    tall_df_value = {\n", "        \"data\": tall_df_value,\n", "        \"headers\": [\"Model\", \"% Correct (LeetCode Hard)\", \"Is Open Source\"],\n", "        \"metadata\": {\n", "            \"display_value\": display_value\n", "        }\n", "    }\n", "\n", "    with gr.Row():\n", "        with gr.Column():\n", "            df_tall = gr.Dataframe(\n", "                value=tall_df_value,\n", "                interactive=False,\n", "                label=\"Tall Dataframe (Scroll Vertically)\",\n", "                datatype=[\"str\", \"number\", \"bool\"],\n", "                max_height=200,\n", "                show_label=True,\n", "                elem_id=\"dataframe_tall\",\n", "                show_copy_button=True,\n", "                show_row_numbers=True,\n", "                show_search=\"search\",\n", "            )\n", "\n", "            df_tall_selected_cell_index = gr.Textbox(\n", "                label=\"Tall dataframe selected cell index\", elem_id=\"tall_selected_cell_index\"\n", "            )\n", "            df_tall_selected_cell_value = gr.Textbox(\n", "                label=\"Tall dataframe selected cell value\", elem_id=\"tall_selected_cell_value\"\n", "            )\n", "\n", "    with gr.Row():\n", "        with gr.Column():\n", "            update_btn = gr.Button(\"Update dataframe\", elem_id=\"update_btn\")\n", "            clear_btn = gr.Button(\"Clear dataframe\", elem_id=\"clear_btn\")\n", "\n", "    with gr.Row():\n", "        change_events = gr.Number(\n", "            value=0, label=\"Change events\", elem_id=\"change_events\"\n", "        )\n", "        input_events = gr.Number(value=0, label=\"Input events\", elem_id=\"input_events\")\n", "        select_events = gr.Number(\n", "            value=0, label=\"Select events\", elem_id=\"select_events\"\n", "        )\n", "        edit_events = gr.Number(value=0, label=\"Edit events\", elem_id=\"edit_events\")\n", "\n", "    with gr.Row():\n", "        selected_cell_index = gr.Textbox(\n", "            label=\"Selected cell index\", elem_id=\"selected_cell_index\"\n", "        )\n", "        selected_cell_value = gr.Textbox(\n", "            label=\"Selected cell value\", elem_id=\"selected_cell_value\"\n", "        )\n", "        edit_data = gr.Textbox(\n", "            label=\"Edit event data\", elem_id=\"edit_data\"\n", "        )\n", "\n", "    update_btn.click(fn=update_dataframe, outputs=[df, df_view])\n", "    clear_btn.click(fn=clear_dataframes, outputs=[df, df_view, df_tall])\n", "    df.change(fn=lambda x: x + 1, inputs=[change_events], outputs=[change_events])\n", "    df.edit(edit_dataframe, inputs=[edit_events], outputs=[edit_data, edit_events])\n", "    df.input(fn=lambda x: x + 1, inputs=[input_events], outputs=[input_events])\n", "    df.select(\n", "        fn=increment_select_counter,\n", "        inputs=[select_events],\n", "        outputs=[select_events, selected_cell_index, selected_cell_value],\n", "    )\n", "\n", "    df_tall.select(\n", "        fn=increment_select_counter,\n", "        inputs=[select_events],\n", "        outputs=[select_events, df_tall_selected_cell_index, df_tall_selected_cell_value],\n", "    )\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -22,6 +22,14 @@ def increment_select_counter(evt: gr.SelectData, count):
     count_val = 1 if count is None else count + 1
     return count_val, evt.index, evt.value
 
+def edit_dataframe(evt: gr.EditData, count):
+    event_data = ", ".join([
+        f"index: {evt.index}",
+        f"value: {evt.value}",
+        f"previous_value: {evt.previous_value}",
+    ])
+    return event_data, count + 1
+
 with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column(scale=1):
@@ -117,6 +125,7 @@ with gr.Blocks() as demo:
         select_events = gr.Number(
             value=0, label="Select events", elem_id="select_events"
         )
+        edit_events = gr.Number(value=0, label="Edit events", elem_id="edit_events")
 
     with gr.Row():
         selected_cell_index = gr.Textbox(
@@ -125,10 +134,14 @@ with gr.Blocks() as demo:
         selected_cell_value = gr.Textbox(
             label="Selected cell value", elem_id="selected_cell_value"
         )
+        edit_data = gr.Textbox(
+            label="Edit event data", elem_id="edit_data"
+        )
 
     update_btn.click(fn=update_dataframe, outputs=[df, df_view])
     clear_btn.click(fn=clear_dataframes, outputs=[df, df_view, df_tall])
     df.change(fn=lambda x: x + 1, inputs=[change_events], outputs=[change_events])
+    df.edit(edit_dataframe, inputs=[edit_events], outputs=[edit_data, edit_events])
     df.input(fn=lambda x: x + 1, inputs=[input_events], outputs=[input_events])
     df.select(
         fn=increment_select_counter,