Create app.py

app.py

@@ -0,0 +1,89 @@
+__all__ = ['block', 'make_clickable_repo', 'get_submissions']
+
+import gradio as gr
+import pandas as pd
+from huggingface_hub import HfApi
+
+def make_clickable_repo(name, repo_type):
+    if repo_type == "spaces":
+        link = "https://huggingface.co/" + "spaces/" + name
+    elif repo_type == "models":
+        link = "https://huggingface.co/"  + name
+    else:
+        link = "https://huggingface.co/" + "datasets/" + name
+    return f'<a target="_blank" href="{link}">{name.split("/")[-1]}</a>'
+
+def get_repo_ids(repo_type):
+    api = HfApi()
+    if repo_type == "spaces":
+        repos = api.list_spaces(author="somosnlp")
+        repos = [s for s in repos if s.id not in ["somosnlp", "somosnlp/likes_leaderboard"]]
+    elif repo_type == "models":
+        repos = api.list_models(author="somosnlp", full=True)
+    else:
+        repos = api.list_datasets(author="somosnlp")
+    return repos
+
+def get_submissions(repo_type):
+    submissions = get_repo_ids(repo_type)
+    leaderboard = []
+
+    for submission in submissions:
+        leaderboard.append(
+            (
+                make_clickable_repo(submission.id, repo_type),
+                submission.likes,
+            )
+        )
+
+    df = pd.DataFrame(data=leaderboard, columns=["Repo", "Likes"])
+    df.sort_values(by=["Likes"], ascending=False, inplace=True)
+    df.insert(0, "Rank", list(range(1, len(df) + 1)))
+    return df
+
+block = gr.Blocks()
+
+with block:
+    gr.Markdown(
+        """# Somos NLP ❤️ Leaderboard
+    """
+    )
+    with gr.Tabs():
+        with gr.TabItem("Spaces (ML apps)"):
+            with gr.Row():
+                spaces_data = gr.components.Dataframe(
+                    type="pandas", datatype=["number", "markdown", "number"]
+                )
+            with gr.Row():
+                data_run = gr.Button("Refresh")
+                data_run.click(
+                    get_submissions, inputs=gr.Variable("spaces"), outputs=spaces_data
+                )
+        with gr.TabItem("Models"):
+            with gr.Row():
+                models_data = gr.components.Dataframe(
+                    type="pandas", datatype=["number", "markdown", "number"]
+                )
+            with gr.Row():
+                data_run = gr.Button("Refresh")
+                data_run.click(
+                    get_submissions, inputs=gr.Variable("models"), outputs=models_data
+                )
+        with gr.TabItem("Datasets"):
+            with gr.Row():
+                datasets_data = gr.components.Dataframe(
+                    type="pandas", datatype=["number", "markdown", "number"]
+                )
+            with gr.Row():
+                data_run = gr.Button("Refresh")
+                data_run.click(
+                    get_submissions, inputs=gr.Variable("datasets"), outputs=datasets_data
+                )
+
+
+    block.load(get_submissions, inputs=gr.Variable("spaces"), outputs=spaces_data)
+    block.load(get_submissions, inputs=gr.Variable("models"), outputs=models_data)
+    block.load(get_submissions, inputs=gr.Variable("datasets"), outputs=datasets_data)
+
+
+block.launch(debug=True)