Update src/streamlit_app.py

src/streamlit_app.py

@@ -8,32 +8,41 @@ from sklearn.model_selection import train_test_split
 from sklearn.preprocessing import StandardScaler
 from sklearn.metrics import accuracy_score, classification_report, roc_curve, roc_auc_score, confusion_matrix
 
+os.environ["STREAMLIT_BROWSER_GATHER_USAGE_STATS"] = "false"
+os.environ["STREAMLIT_METRICS_ENABLED"] = "false"
+os.environ["HOME"] = "/tmp"
+os.environ["XDG_CONFIG_HOME"] = "/tmp"
+
 def data():
     uploaded_data = st.file_uploader('📂 Upload Data File', type=['csv', 'txt', 'xlsx'])
     if uploaded_data is not None:
-        try:
-            if uploaded_data.type == 'text/plain':
-                delimiter = st.radio('Select delimiter (separator)', [',', '\t', '|', ' ', 'Auto Detect'])
-                if delimiter == 'Auto Detect':
+        file_type = uploaded_data.type
+    
+        if file_type == 'text/plain':
+            delimiter = st.radio('Select delimiter (separator)', [',', '\t', '|', ' ', 'Auto Detect'])
+            if delimiter == 'Auto Detect':
+                try:
                     df = pd.read_csv(uploaded_data, sep=None, engine='python')
-                else:
-                    df = pd.read_csv(uploaded_data, sep=delimiter)
-                st.write('### 🔍 Dataset Preview')
-                st.dataframe(df.head())
-                return df
-            elif uploaded_data.type == 'text/csv':
-                df = pd.read_csv(uploaded_data)
-                st.write('### 🔍 Dataset Preview')
-                st.dataframe(df.head())
-                return df
-            elif uploaded_data.type == 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet':
-                df = pd.read_excel(uploaded_data)
-                st.write('### 🔍 Dataset Preview')
-                st.dataframe(df.head())
-                return df
-        except Exception as e:
-            st.error(f"Error loading file: {str(e)}")
+                except Exception:
+                    st.error("Could not auto-detect delimiter (separator), try selecting one manually.")
+                    return None
+            else:
+                df = pd.read_csv(uploaded_data, sep=delimiter)
+    
+        elif file_type == 'text/csv':
+            df = pd.read_csv(uploaded_data)
+    
+        elif file_type == 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet':
+            df = pd.read_excel(uploaded_data)
+        
+        else:
+            st.error("Unsupported file type.")
             return None
+    
+        st.write('### 🔍 Dataset Preview')
+        st.dataframe(df.head())
+        return df
+
     return None
 
 @st.cache_data