Update app.py

app.py

@@ -52,10 +52,8 @@ elif model_choice == "GPT-4o":
 if "df" not in st.session_state:
     st.session_state.df = None
 
-# Dataset Input
 # Dataset Input
 input_option = st.radio("Select Dataset Input:", ["Use Hugging Face Dataset", "Upload CSV File"])
-
 if input_option == "Use Hugging Face Dataset":
     dataset_name = st.text_input("Enter Hugging Face Dataset Name:", value="Einstellung/demo-salaries")
     if st.button("Load Dataset"):
@@ -64,24 +62,16 @@ if input_option == "Use Hugging Face Dataset":
                 dataset = load_dataset(dataset_name, split="train")
                 st.session_state.df = pd.DataFrame(dataset)
                 st.success(f"Dataset '{dataset_name}' loaded successfully!")
+                st.dataframe(st.session_state.df.head())
         except Exception as e:
             st.error(f"Error: {e}")
-
 elif input_option == "Upload CSV File":
     uploaded_file = st.file_uploader("Upload CSV File:", type=["csv"])
-    if uploaded_file is not None:
-        try:
-            st.session_state.df = pd.read_csv(uploaded_file)
-            st.success("File uploaded successfully!")
-        except Exception as e:
-            st.error(f"Error loading file: {e}")
-
-# Show dataset preview only after loading (for both Hugging Face and CSV)
-if st.session_state.df is not None:
-    with st.expander("📂 View Dataset Preview", expanded=True):
+    if uploaded_file:
+        st.session_state.df = pd.read_csv(uploaded_file)
+        st.success("File uploaded successfully!")
         st.dataframe(st.session_state.df.head())
 
-
 # SQL-RAG Analysis
 if st.session_state.df is not None:
     temp_dir = tempfile.TemporaryDirectory()