Update app.py

app.py

@@ -159,33 +159,45 @@ def download_test_set() -> Tuple[str, str]:
         error_msg = f"❌ Error creating test set download: {str(e)}"
         return None, error_msg
 
+
 def validate_submission(file, model_name: str, author: str, description: str) -> Tuple[str, Optional[pd.DataFrame]]:
-    """Validate uploaded prediction file, handling both file-like and NamedString inputs."""
+    """Validate uploaded prediction file, supporting str paths, bytes, and Gradio wrappers."""
     try:
         if file is None:
             return "❌ Please upload a predictions file", None
         if not model_name.strip():
             return "❌ Please provide a model name", None
 
-        # Read raw bytes from the upload
-        try:
-            file_content = file.read()
-        except AttributeError:
-            # Fallback for Gradio NamedString
-            data = getattr(file, "data", None) or getattr(file, "value", None)
-            if data is None:
-                return "❌ Could not read uploaded file", None
-            file_content = data.encode("utf-8") if isinstance(data, str) else data
+        # 1) Determine raw bytes
+        if isinstance(file, bytes):
+            file_content = file
+        elif isinstance(file, str):
+            # could be a path or raw text
+            if os.path.exists(file):
+                with open(file, "rb") as f:
+                    file_content = f.read()
+            else:
+                file_content = file.encode("utf-8")
+        elif hasattr(file, "name") and os.path.exists(file.name):
+            # tempfile._TemporaryFileWrapper from Gradio
+            with open(file.name, "rb") as f:
+                file_content = f.read()
+        else:
+            return "❌ Could not read uploaded file", None
 
-        # Determine filename
-        filename = getattr(file, "name", None) or getattr(file, "filename", None) or "uploaded_file"
+        # 2) Infer filename for format-sniffing
+        filename = (
+            getattr(file, "name", None)
+            or getattr(file, "filename", None)
+            or "predictions.csv"
+        )
 
-        # Load complete test set
+        # 3) Load test set if needed
         global complete_test_set
         if complete_test_set is None:
             complete_test_set = get_complete_test_set()
 
-        # Run validation
+        # 4) Run existing validation pipeline
         validation_result = validate_submission_complete(
             file_content, filename, complete_test_set, model_name
         )
@@ -196,11 +208,11 @@ def validate_submission(file, model_name: str, author: str, description: str) ->
             return validation_result["report"], None
 
     except Exception as e:
-        error_msg = (
-            f"❌ Validation error: {str(e)}\n\nTraceback:\n"
-            + traceback.format_exc()
+        return (
+            f"❌ Validation error: {e}\n\nTraceback:\n{traceback.format_exc()}",
+            None,
         )
-        return error_msg, None
+
 
 
 def evaluate_submission(