Update src/streamlit_app.py

src/streamlit_app.py

@@ -79,18 +79,28 @@ st.markdown(
 expander = st.expander("**Important notes**")
 expander.write(""" 
 **How to Use the HR.ai web app:** 
+
 1. Type or paste your text into the text area, then press Ctrl + Enter.
 2. Click the 'Results' button to extract and tag entities in your text data. 
+
 Results are presented in easy-to-read tables, visualized in an interactive tree map, pie chart and bar chart, and are available for download along with a Glossary of tags.      
+
 **How to Use the Question-Answering feature:**
+
 1. Type or paste your text into the text area, then press Ctrl + Enter. 
 2. Click the 'Add Question' button to add your question to the Record of Questions. You can manage your questions by deleting them one by one.
 3. Click the 'Extract Answers' button to extract the answer to your question.
+
 Results are presented in an easy-to-read table, visualized in an interactive tree map, and is available for download.   
+
 **Entities:** "Email", "Phone_number", "Street_address", "City", "Country", "Date_of_birth", "Marital_status", "Person", "Full_time", "Part_time", "Contract", "Terminated", "Retired", "Job_title", "Date", "Organization", "Role", "Performance_score", "Leave_of_absence", "Retirement_plan", "Bonus", "Stock_options", "Health_insurance", "Pay_rate", "Annual_salary", "Tax", "Deductions", "Interview_type", "Applicant", "Referral", "Job_board", "Recruiter", "Offer_letter", "Agreement", "Certification", "Skill"
+
 **Usage Limits:** You can request results unlimited times for one (1) month.      
+
 **Supported Languages:** English     
+
 **Technical issues:** If your connection times out, please refresh the page or reopen the app's URL. 
+
 For any errors or inquiries, please contact us at info@nlpblogs.com""")
 
 
@@ -342,6 +352,7 @@ with tab2:
                         df = df2.rename(columns={'label': 'question', 'text': 'answer'})
                         
                         st.subheader("Extracted Answers", divider="green")
+                        st.write("To download the data, simply hover your cursor over the table. A download icon will appear on the right side.")
                         st.dataframe(df, use_container_width=True)
 
                         st.subheader("Tree map", divider="green")
@@ -351,14 +362,7 @@ with tab2:
                         fig_treemap.update_layout(margin=dict(t=50, l=25, r=25, b=25), paper_bgcolor='#F3E5F5', plot_bgcolor='#F3E5F5')
                         st.plotly_chart(fig_treemap)
 
-                        csv_data = df.to_csv(index=False).encode('utf-8')
-                        st.download_button(
-                            label="Download CSV",
-                            data=csv_data,
-                            file_name="nlpblogs_questions_answers.csv",
-                            mime="text/csv",
-                        )
-
+                       
                         if comet_initialized:
                             experiment.log_metric("processing_time_seconds", elapsed_time)
                             experiment.log_table("predicted_entities", df)