Update app.py

app.py

@@ -150,6 +150,37 @@ with tab1:
         st.dataframe(df_sorted)
         st.download_button("Download Ascending Order CSV", df_sorted.to_csv(index=False), "text_binary_labels_ascending.csv")
 
+        # === Robot Preparation Script Generation ===
+        st.subheader("Robot Preparation Script")
+        robot_template = pd.read_csv("Robot.csv", skiprows=3)
+        robot_template.columns = ['Labware', 'Source', 'Labware_2', 'Destination', 'Volume', 'Tool', 'Name']
+
+        # Add Sample numbers for well referencing
+        df_sorted.insert(0, 'Sample', range(1, len(df_sorted)+1))
+
+        # Step 1: Count the number of edited sites per row
+        df_sorted['# donors'] = df_sorted.iloc[:, 1:].sum(axis=1)
+
+        # Step 2: Calculate volume per donor (32 / # donors)
+        df_sorted['volume donors (µl)'] = 32 / df_sorted['# donors']
+
+        # Step 3: Generate the robot script
+        robot_script = []
+        source_wells = robot_template['Source'].unique().tolist()[:32]
+
+        for i, col in enumerate(df_sorted.columns[1:33]):
+            for row_idx, sample in df_sorted.iterrows():
+                if sample[col] == 1:
+                    source = source_wells[i]
+                    dest = f"A{sample['Sample']}"
+                    vol = round(sample['volume donors (µl)'], 2)
+                    robot_script.append({'Source': source, 'Destination': dest, 'Volume': vol})
+
+        robot_script_df = pd.DataFrame(robot_script)
+        st.dataframe(robot_script_df)
+        st.download_button("Download Robot Script CSV", robot_script_df.to_csv(index=False), "robot_script.csv")
+
+
 # Tab 2: EF → Binary
 with tab2:
     st.write("Upload an Editing Frequency CSV or enter manually:")