Fix

app.ipynb

@@ -7,7 +7,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# |export\n",
+    "#|export\n",
     "import gradio as gr\n",
     "import pandas as pd\n",
     "from huggingface_hub import list_models"
@@ -20,7 +20,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# |export\n",
+    "#|export\n",
     "def get_submissions(category):\n",
     "    submissions = list_models(filter=[\"dreambooth-hackathon\", category], full=True)\n",
     "    leaderboard_models = []\n",
@@ -86,7 +86,7 @@
     }
    ],
    "source": [
-    "# |export\n",
+    "#|export\n",
     "block = gr.Blocks()\n",
     "\n",
     "with block:\n",

app.py

@@ -1,9 +1,87 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
 
 # %% auto 0
-__all__ = []
+__all__ = ['block', 'get_submissions']
 
 # %% app.ipynb 0
 import gradio as gr
 import pandas as pd
 from huggingface_hub import list_models
+
+# %% app.ipynb 1
+def get_submissions(category):
+    submissions = list_models(filter=["dreambooth-hackathon", category], full=True)
+    leaderboard_models = []
+
+    for submission in submissions:
+        # user, model, likes
+        leaderboard_models.append(
+            (
+                submission.id.split("/")[0],
+                submission.id.split("/")[-1],
+                submission.likes,
+            )
+        )
+
+    df = pd.DataFrame(data=leaderboard_models, columns=["User", "Model", "Likes"])
+    df.sort_values(by=["Likes"], ascending=False, inplace=True)
+    df.insert(0, "Rank", list(range(1, len(df) + 1)))
+    return df
+
+# %% app.ipynb 2
+block = gr.Blocks()
+
+with block:
+    gr.Markdown("hi")
+    with gr.Tabs():
+        with gr.TabItem("Animal"):
+            with gr.Row():
+                animal_data = gr.outputs.Dataframe(type="pandas")
+            with gr.Row():
+                data_run = gr.Button("Refresh")
+                data_run.click(
+                    get_submissions, inputs=gr.Variable("Animal"), outputs=animal_data
+                )
+        with gr.TabItem("Science"):
+            with gr.Row():
+                science_data = gr.outputs.Dataframe(type="pandas")
+            with gr.Row():
+                data_run = gr.Button("Refresh")
+                data_run.click(
+                    get_submissions, inputs=gr.Variable("Animal"), outputs=science_data
+                )
+        with gr.TabItem("Food"):
+            with gr.Row():
+                food_data = gr.outputs.Dataframe(type="pandas")
+            with gr.Row():
+                data_run = gr.Button("Refresh")
+                data_run.click(
+                    get_submissions, inputs=gr.Variable("Food"), outputs=food_data
+                )
+        with gr.TabItem("Landscape"):
+            with gr.Row():
+                landscape_data = gr.outputs.Dataframe(type="pandas")
+            with gr.Row():
+                data_run = gr.Button("Refresh")
+                data_run.click(
+                    get_submissions, inputs=gr.Variable("Landscape"), outputs=data
+                )
+        with gr.TabItem("Wilcard"):
+            with gr.Row():
+                wildcard_data = gr.outputs.Dataframe(type="pandas")
+            with gr.Row():
+                data_run = gr.Button("Refresh")
+                data_run.click(
+                    get_submissions,
+                    inputs=gr.Variable("Wildcard"),
+                    outputs=wildcard_data,
+                )
+
+    block.load(get_submissions, inputs=gr.Variable("animal"), outputs=animal_data)
+    block.load(get_submissions, inputs=gr.Variable("science"), outputs=science_data)
+    block.load(get_submissions, inputs=gr.Variable("food"), outputs=food_data)
+    block.load(get_submissions, inputs=gr.Variable("landscape"), outputs=landscape_data)
+    block.load(get_submissions, inputs=gr.Variable("wildcard"), outputs=wildcard_data)
+
+
+block.launch()