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app.py

@@ -106,17 +106,25 @@ def scan_grid():
             m = re.match(r"t=([\d.]+)_ALL_FIELDS\.csv", fname)
             if m:
                 thresholds.add(m.group(1))
-    # Discover fields from a sample ALL_FIELDS file
-    sample = next(iter(
+    # Discover fields from sample ALL_FIELDS files — try until one succeeds
+    _FALLBACK_FIELDS = [
+        "desalting_process", "elution_buffer", "enzyme_name", "expression_strain",
+        "inducer", "induction_temperature", "lysis_buffer", "medium_name",
+        "molecular_weight", "organism_source", "plasmid", "source_key", "strain",
+    ]
+    for sample in (
         glob.glob(os.path.join(GRID_BASE, "model=*", "min=*", "t=*_ALL_FIELDS.csv.gz")) +
         glob.glob(os.path.join(GRID_BASE, "model=*", "min=*", "t=*_ALL_FIELDS.csv"))
-    ), None)
-    if sample:
+    ):
         try:
-            ext = ".gz" if sample.endswith(".gz") else None
-            fields = set(pd.read_csv(sample, compression="gzip" if ext else None, usecols=["field"])["field"].unique())
+            compression = "gzip" if sample.endswith(".gz") else None
+            fields = set(pd.read_csv(sample, compression=compression, usecols=["field"])["field"].unique())
+            if fields:
+                break
         except Exception:
-            pass
+            continue
+    if not fields:
+        fields = set(_FALLBACK_FIELDS)
     return (
         sorted(models),
         sorted(mins, key=float),
@@ -2347,7 +2355,6 @@ def download_csv(_, table_data):
 @app.callback(
     Output("eval-classif-graph", "figure"),
     Input("classif-group", "value"),
-    prevent_initial_call=True,
 )
 def update_classif_chart(group):
     if CLASSIF_DF.empty or not group: