Update app.py

app.py

@@ -3,29 +3,32 @@ import gradio as gr
 
 # Core conversion logic
 def convert_schedule(file_path, direction):
-    # Read the uploaded Excel file (first sheet) with first column as index
+    # Read the uploaded Excel file with first column as index
     df = pd.read_excel(file_path, index_col=0)
 
-    if direction == "A to B":
+    # Clean up any extraneous columns (e.g., blank/Unnamed or hyperlink rows)
+    drop_cols = [col for col in df.columns if isinstance(col, str) and (col.startswith('Unnamed') or col.startswith('http'))]
+    if drop_cols:
+        df = df.drop(columns=drop_cols)
+
+    if direction == 'A to B':
         # Models in rows → Texters as rows
-        df_reset = df.reset_index().rename(columns={df.index.name or df.columns[0]: "Model"})
-        df_melt = df_reset.melt(id_vars=["Model"], var_name="Header", value_name="Texter")
-        df_melt = df_melt.dropna(subset=["Texter"])
-        # Use pivot_table to handle duplicate entries gracefully
+        df_reset = df.reset_index().rename(columns={df.index.name or df.columns[0]: 'Model'})
+        df_melt = df_reset.melt(id_vars=['Model'], var_name='Header', value_name='Texter')
+        df_melt = df_melt.dropna(subset=['Texter'])
         pivot = df_melt.pivot_table(
-            index="Texter", columns="Header", values="Model", aggfunc="first"
+            index='Texter', columns='Header', values='Model', aggfunc='first'
         )
-        result = pivot.reindex(columns=df.columns).fillna("")
+        result = pivot.reindex(columns=df.columns).fillna('')
     else:
         # Texters in rows → Models as rows
-        df_reset = df.reset_index().rename(columns={df.index.name or df.columns[0]: "Texter"})
-        df_melt = df_reset.melt(id_vars=["Texter"], var_name="Header", value_name="Model")
-        df_melt = df_melt.dropna(subset=["Model"])
-        # Use pivot_table to handle duplicate entries gracefully
+        df_reset = df.reset_index().rename(columns={df.index.name or df.columns[0]: 'Texter'})
+        df_melt = df_reset.melt(id_vars=['Texter'], var_name='Header', value_name='Model')
+        df_melt = df_melt.dropna(subset=['Model'])
         pivot = df_melt.pivot_table(
-            index="Model", columns="Header", values="Texter", aggfunc="first"
+            index='Model', columns='Header', values='Texter', aggfunc='first'
         )
-        result = pivot.reindex(columns=df.columns).fillna("")
+        result = pivot.reindex(columns=df.columns).fillna('')
 
     return result
 
@@ -34,15 +37,16 @@ def main():
     iface = gr.Interface(
         fn=convert_schedule,
         inputs=[
-            gr.File(label="Upload Schedule (.xlsx)", file_count="single", type="filepath"),
-            gr.Radio(["A to B", "B to A"], label="Conversion Direction")
+            gr.File(label='Upload Schedule (.xlsx)', file_count='single', type='filepath'),
+            gr.Radio(['A to B', 'B to A'], label='Conversion Direction')
         ],
-        outputs=gr.Dataframe(label="Converted Schedule"),
-        title="Dynamic Schedule Converter",
-        description="Upload an Excel file in Format A or B and convert between models-as-rows ↔ texters-as-rows."
+        outputs=gr.Dataframe(label='Converted Schedule'),
+        title='Dynamic Schedule Converter',
+        description=('Upload an Excel file in Format A or B, '
+                     'auto-clean blank/merged header rows, and convert between models-as-rows ↔ texters-as-rows.')
     )
     # Listen on all interfaces for Hugging Face Spaces
-    iface.launch(server_name="0.0.0.0", server_port=7860)
+    iface.launch(server_name='0.0.0.0', server_port=7860)
 
-if __name__ == "__main__":
+if __name__ == '__main__':
     main()