Update src/streamlit_app.py

src/streamlit_app.py

@@ -88,7 +88,7 @@ Results are presented in easy-to-read tables, visualized in an interactive tree
 For any errors or inquiries, please contact us at info@nlpblogs.com""")
 
 with st.sidebar:
-    st.write("Use the following code to embed the EntityFinance web app on your website. Feel free to adjust the width and height values to fit your page.")
+    st.write("Use the following code to embed the MediExtract web app on your website. Feel free to adjust the width and height values to fit your page.")
     code = '''
     <iframe
 	src="https://aiecosystem-mediextract.hf.space"
@@ -245,7 +245,7 @@ if st.button("Results"):
                 # Tree map
                 st.subheader("Tree map", divider = "gray")
                 fig_treemap = px.treemap(df, path=[px.Constant("all"), 'category', 'label', 'text'], values='score', color='category')
-                fig_treemap.update_layout(margin=dict(t=50, l=25, r=25, b=25), paper_bgcolor='#E8F5E9', plot_bgcolor='#E8F5E9')
+                fig_treemap.update_layout(margin=dict(t=50, l=25, r=25, b=25), paper_bgcolor='#F5F5F5', plot_bgcolor='#F5F5F5')
                 st.plotly_chart(fig_treemap)
                 
                 # Pie and Bar charts
@@ -258,8 +258,8 @@ if st.button("Results"):
                     fig_pie = px.pie(grouped_counts, values='count', names='category', hover_data=['count'], labels={'count': 'count'}, title='Percentage of predicted categories')
                     fig_pie.update_traces(textposition='inside', textinfo='percent+label')
                     fig_pie.update_layout(
-                        paper_bgcolor='#E8F5E9',
-                        plot_bgcolor='#E8F5E9'
+                        paper_bgcolor='#F5F5F5',
+                        plot_bgcolor='#F5F5F5'
                     )
                     st.plotly_chart(fig_pie)
                 
@@ -270,8 +270,8 @@ if st.button("Results"):
                     st.subheader("Bar chart", divider = "gray")
                     fig_bar = px.bar(grouped_counts, x="count", y="category", color="category", text_auto=True, title='Occurrences of predicted categories')
                     fig_bar.update_layout(  # Changed from fig_pie to fig_bar
-                        paper_bgcolor='#E8F5E9',
-                        plot_bgcolor='#E8F5E9'
+                        paper_bgcolor='#F5F5F5',
+                        plot_bgcolor='#F5F5F5'
                     )
                     st.plotly_chart(fig_bar)
                 
@@ -284,8 +284,8 @@ if st.button("Results"):
                     st.dataframe(repeating_entities, use_container_width=True)
                     fig_repeating_bar = px.bar(repeating_entities, x='Entity', y='Count', color='Entity')
                     fig_repeating_bar.update_layout(xaxis={'categoryorder': 'total descending'},
-                        paper_bgcolor='#E8F5E9',
-                        plot_bgcolor='#E8F5E9')
+                        paper_bgcolor='#F5F5F5',
+                        plot_bgcolor='#F5F5F5')
                     st.plotly_chart(fig_repeating_bar)
                 else:
                     st.warning("No entities were found that occur more than once.")