Update app.py

app.py

@@ -114,8 +114,8 @@ def load_eeg_data(file_path, default_sfreq=256.0, time_col='time'):
     return raw
 
 def analyze_eeg(file, default_sfreq, time_col):
-    if file is None:
-        return "No file uploaded."
+    if time_col == "(No time column)":
+        time_col = None
     raw = load_eeg_data(file.name, default_sfreq=float(default_sfreq), time_col=time_col)
 
     psd, freqs = mne.time_frequency.psd_welch(raw, fmin=1, fmax=40)
@@ -147,8 +147,20 @@ Provide a concise, user-friendly interpretation of these findings in simple term
 # Step 1: Inspect file
 def preview_file(file):
     msg, cols, preview = inspect_file(file)
-    # Instead of gr.Dropdown.update(...)
-    return msg, {"choices": cols, "value": None}, preview
+
+    # Add a placeholder choice for no selection
+    # This ensures the user can explicitly say "no time column"
+    if len(cols) > 0:
+        cols = ["(No time column)"] + cols
+        default_value = "(No time column)"
+    else:
+        # If no columns detected, just leave empty
+        cols = []
+        default_value = None
+
+    # Return a dictionary for the Dropdown output
+    return msg, {"choices": cols, "value": default_value}, preview
+
 
 with gr.Blocks() as demo:
     gr.Markdown("# NeuroNarrative-Lite: EEG Summary with Flexible Preprocessing")