initial app demo

app.py

@@ -0,0 +1,69 @@
+import gradio as gr
+from gradio_leaderboard import Leaderboard, ColumnFilter
+import pandas as pd
+
+# dataset = load_dataset("your_dataset_name")
+
+
+from datetime import datetime
+
+
+
+def gradio_interface():
+    with gr.Blocks(title="OpenADMET ADMET Challenge") as demo:
+
+
+
+        # --- Welcome markdown message ---
+        welcome_md = """
+        # 🧪 OpenADMET + XXX  
+        ## Computational Blind Challenge in ADMET
+
+        Welcome to the **XXX**, hosted by **OpenADMET** in collaboration with **XXX**.
+
+        Your task is to develop and submit predictive models for key ADMET properties on a blinded test set of real world drug discovery data.
+
+
+        📅 **Timeline**:  
+        - TBD
+
+        ---
+
+        """
+
+        # --- Gradio Interface ---
+        with gr.Tabs(elem_classes="tab-buttons"):
+
+            with gr.TabItem("Welcome"):
+                gr.Markdown(welcome_md)
+
+            with gr.TabItem("Submit Predictions"):
+                gr.Markdown("Upload your prediction files here.")
+                filename = gr.State(value=None) 
+                eval_state = gr.State(value=None) 
+                user_state = gr.State(value=None)
+
+            with gr.TabItem("Leaderboard"):
+                gr.Markdown("View the leaderboard here.")
+                df = pd.DataFrame({
+                    "user": ["User1", "User2", "User3"],
+                    "Model": ["A", "B", "C"],
+                    "R2": [0.94, 0.92, 0.89],
+                    "Spearman R": [0.93, 0.91, 0.88],
+                })
+                Leaderboard(
+                    value=df,
+                    # Optionally configure columns:
+                    select_columns=["Model", "R2", "Spearman R"],
+                    # Additional options: search_columns, filter_columns, hide_columns, etc.
+                    search_columns=["Model", "user"],
+                )
+
+
+            with gr.TabItem("About"):
+                gr.Markdown("Learn more about the challenge and the organizers.")
+
+    return demo
+
+if __name__ == "__main__":
+    gradio_interface().launch()