Update app.py

app.py

@@ -8,38 +8,6 @@ import importlib
 import sentry_sdk
 import wandb
 from contextlib import redirect_stdout, redirect_stderr
-from sentry_sdk import capture_exception
-from sentry_sdk.integrations.logging import LoggingIntegration
-from sentry_sdk.integrations.starlette import StarletteIntegration
-from sentry_sdk.integrations.fastapi import FastApiIntegration
-import spaces
-dsn = os.getenv("SENTRY_DSN")
-if not dsn:
-    print("WARNING: SENTRY_DSN not set – Sentry disabled")
-else:
-
-    sentry_sdk.init(
-        dsn=dsn,
-        traces_sample_rate=0.1,
-        integrations=[
-            StarletteIntegration(
-                failed_request_status_codes={
-                    400,
-                    422,
-                    *range(500, 599),
-                },  # also log 4xx from Gradio
-            ),
-            LoggingIntegration(
-                level=logging.INFO,  # breadcrumb level
-                event_level=logging.ERROR,
-            ),
-            FastApiIntegration(),
-        ],
-        release=os.getenv("HF_SPACE_VERSION", "dev"),
-        environment="hf_space",
-    )
-
-sentry_sdk.capture_message("🎉 Sentry is wired up!")
 
 USE_WANDB = "WANDB_API_KEY" in os.environ
 if USE_WANDB:
@@ -310,17 +278,46 @@ initial_df = pd.DataFrame(initial_filament_data)
 
 if os.path.exists(DEFAULT_MATERIALS_CSV):
     try:
-        initial_df = pd.read_csv(DEFAULT_MATERIALS_CSV)
+        # Load what the user already has
+        loaded_df = pd.read_csv(DEFAULT_MATERIALS_CSV)
+
+        # Make sure the columns we need are present
         for col in ["Brand", " Name", " TD", " Color"]:
-            if col not in initial_df.columns:
-                initial_df[col] = None
-        initial_df = initial_df[["Brand", " Name", " TD", " Color"]].astype(
+            if col not in loaded_df.columns:
+                # keep it simple, create empty column
+                loaded_df[col] = "" if col != " TD" else 0.0
+
+        # Cast to the types we expect
+        loaded_df = loaded_df[["Brand", " Name", " TD", " Color"]].astype(
             {" TD": float, " Color": str}
         )
+
+        # Keep a DataFrame version for the rest of the app
+        initial_df = loaded_df
+
+        # Important part:
+        # also update the in memory initial_filament_data so later fallbacks
+        # do not go back to the hardcoded 6 Generic rows
+        initial_filament_data = {
+            "Brand": initial_df["Brand"].tolist(),
+            " Name": initial_df[" Name"].tolist(),
+            " TD": initial_df[" TD"].tolist(),
+            " Color": initial_df[" Color"].tolist(),
+        }
+        # If you want to keep " Owned" around even when CSV did not have it,
+        # you can add a default here
+        if " Owned" not in initial_df.columns:
+            # fill with false by default
+            initial_filament_data[" Owned"] = ["false"] * len(initial_df)
+        else:
+            initial_filament_data[" Owned"] = initial_df[" Owned"].astype(str).tolist()
+
     except Exception as e:
         print(f"Warning: Could not load {DEFAULT_MATERIALS_CSV}: {e}. Using default.")
         initial_df = pd.DataFrame(initial_filament_data)
 else:
+    # CSV does not exist yet, create it from the hardcoded defaults
+    initial_df = pd.DataFrame(initial_filament_data)
     initial_df.to_csv(DEFAULT_MATERIALS_CSV, index=False)