Publish CardioSafe Gradio demo

app.py

@@ -48,6 +48,28 @@ import gradio as gr
 import pandas as pd
 import torch
 
+
+def _ensure_torch_scatter() -> None:
+    """MolGpKa loads `torch_scatter` at module import. The matching wheel
+    URL is torch-version-specific (PyG hosts them at data.pyg.org), so we
+    install it at boot rather than in requirements.txt."""
+    try:
+        import torch_scatter  # noqa: F401
+        return
+    except ImportError:
+        pass
+    torch_ver = torch.__version__.split("+")[0]
+    wheel_index = f"https://data.pyg.org/whl/torch-{torch_ver}+cpu.html"
+    print(f"  installing torch_scatter for torch=={torch_ver} from {wheel_index}")
+    subprocess.run(
+        [sys.executable, "-m", "pip", "install", "--quiet",
+         "torch_scatter", "-f", wheel_index],
+        check=True,
+    )
+
+
+_ensure_torch_scatter()
+
 from inference.ensemble import load_ensemble, load_l1000_encoder, predict  # noqa: E402
 from inference.featurize import featurize_batch  # noqa: E402
 from model.chemberta_encoder import ChemBERTaEncoder  # noqa: E402