Update app.py

app.py

@@ -60,11 +60,16 @@ def submit(model_name, model_id, challenge, submission_id, paper_link, architect
 abs_path = Path(__file__).parent
 
 # Any pandas-compatible data
-df = pd.read_json(str(abs_path / "leaderboard_data.json"))
+pinder_df = pd.read_json(str(abs_path / "leaderboard_pinder.json"))
+plinder_df = pd.read_json(str(abs_path / "leaderboard_plinder.json"))
 
 with gr.Blocks() as demo:
     gr.Markdown("""
     # MLSB 2024 Challenges
+
+    Please find more details about the challenge on [mlsb.io/#challenge](https://www.mlsb.io/#challenge).
+
+    This competition is run together with VantAI, NVidia, Huggingface & University of Basel.
     """)
 
 
@@ -73,7 +78,7 @@ with gr.Blocks() as demo:
                 Evaluating Protein-Protein interaction prediction
                 """)
         Leaderboard(
-        value=df,
+        value=pinder_df,
         select_columns=["Arch", "Model", "L_rms", "I_rms",
             "F_nat", "DOCKQ", "CAPRI"],
         search_columns=["model_name_for_query"],
@@ -85,9 +90,9 @@ with gr.Blocks() as demo:
                 Evaluating Protein-Ligand prediction
                 """)
         Leaderboard(
-        value=df,
-        select_columns=["Arch", "Model", "L_rms", "I_rms",
-            "F_nat", "DOCKQ", "CAPRI"],
+        value=plinder_df,
+        select_columns=["Arch", "Model", "Mean lDDT-PLI", "Median RMSD",
+            "Success Rate (% lDDT-PLI >= 0.7)"],
         search_columns=["model_name_for_query"],
         hide_columns=["model_name_for_query",],
         filter_columns=["Arch"],