fixed app.py

app.py

@@ -4,6 +4,7 @@ import cas9on
 import cas9off
 import pandas as pd
 import streamlit as st
+import numpy as np
 from pathlib import Path
 from igv_component import igv_component
 
@@ -105,13 +106,14 @@ if selected_model == 'Cas9':
             st.session_state['full_on_target_results'] = predictions
 
         if 'on_target_results' in st.session_state and st.session_state['on_target_results']:
-            df = pd.DataFrame(st.session_state['on_target_results'],
-                              columns=["Gene ID", "Start Pos", "End Pos", "Strand", "gRNA", "Prediction"])
-            st.write('On-target predictions:')
-            st.dataframe(df)
-
-            # Pass the gene symbol, genome reference, and predictions to IGV Component
-            igv_component(crispr_results=st.session_state['on_target_results'],
+            # Convert non-serializable types (like numpy float32) to Python native types
+            crispr_results_serializable = [
+                [item if not isinstance(item, np.floating) else float(item) for item in row]
+                for row in st.session_state['on_target_results']
+            ]
+
+            # Pass the serializable results to the IGV component
+            igv_component(crispr_results=crispr_results_serializable,
                           genome_reference=genome_reference,
                           gene_symbol=gene_symbol,
                           key="igv_viewer")