diff --git a/bertrend/demos/topic_analysis/demo_pages/explore_topics.py b/bertrend/demos/topic_analysis/demo_pages/explore_topics.py
index 5af2993..dc716e1 100644
--- a/bertrend/demos/topic_analysis/demo_pages/explore_topics.py
+++ b/bertrend/demos/topic_analysis/demo_pages/explore_topics.py
@@ -283,6 +283,27 @@ def create_topic_documents(
     return folder_name, documents
 
 
+def _display_topic_description(filtered_df):
+    # GPT description button
+    if st.button(
+        "Generate a short description of the topic",
+        type="primary",
+        use_container_width=True,
+    ):
+        with st.spinner("Génération de la description en cours..."):
+            language_code = (
+                "fr" if SessionStateManager.get("language") == "French" else "en"
+            )
+            gpt_description = generate_topic_description(
+                st.session_state["topic_model"],
+                st.session_state["selected_topic_number"],
+                filtered_df,
+                language_code=language_code,
+            )
+        with st.container(border=True):
+            st.markdown(gpt_description)
+
+
 def main():
     """Main function to run the Streamlit topic_analysis."""
     check_model_and_prepare_topics()
@@ -291,8 +312,11 @@ def main():
     if "selected_topic_number" not in st.session_state:
         st.stop()
 
-    display_topic_info()
-    plot_topic_over_time()
+    col1, col2 = st.columns([0.4, 0.6])
+    with col1:
+        display_topic_info()
+    with col2:
+        plot_topic_over_time()
 
     st.divider()
 
@@ -322,18 +346,8 @@ def main():
         default=["All"],
     )
 
-    """
-    # Filter the dataframe based on selected sources
-    if "All" not in selected_sources:
-        filtered_df = representative_df[
-            representative_df[URL_COLUMN].apply(get_website_name).isin(selected_sources)
-        ]
-    else:
-        filtered_df = representative_df
-    """
-
     # Create two columns
-    col1, col2 = st.columns([0.5, 0.5])
+    col1, col2 = st.columns([0.4, 0.6])
 
     with col1:
         # Pass the full representative_df to display_source_distribution
@@ -355,24 +369,8 @@ def main():
 
     st.divider()
 
-    # GPT description button
-    if st.button(
-        "Generate a short description of the topic",
-        type="primary",
-        use_container_width=True,
-    ):
-        with st.spinner("Génération de la description en cours..."):
-            language_code = (
-                "fr" if SessionStateManager.get("language") == "French" else "en"
-            )
-            gpt_description = generate_topic_description(
-                st.session_state["topic_model"],
-                st.session_state["selected_topic_number"],
-                filtered_df,
-                language_code=language_code,
-            )
-        with st.container(border=True):
-            st.markdown(gpt_description)
+    # GPT generated topic description
+    _display_topic_description(filtered_df)
 
     st.divider()