Add feedback acknowledgment messages in create_interface function

app.py

@@ -492,6 +492,7 @@ def create_interface():
                             paper_expert = gr.Checkbox(label="I am an expert in this field", value=False)
                             paper_comment = gr.Textbox(label="Additional feedback on this match (optional)")
                             flag_paper_btn = gr.Button("Submit Paper Feedback")
+                            paper_feedback_ack = gr.Markdown(visible=False, value="", key="paper_feedback_ack")
 
                     with gr.Column(scale=1):
                         analysis_output = gr.Markdown(
@@ -520,6 +521,7 @@ def create_interface():
                             analysis_expert = gr.Checkbox(label="I am an expert in this field", value=False)
                             analysis_comment = gr.Textbox(label="Additional feedback on the analysis (optional)")
                             flag_analysis_btn = gr.Button("Submit Analysis Feedback")
+                            analysis_feedback_ack = gr.Markdown(visible=False, value="", key="analysis_feedback_ack")
 
                 # Hidden UI elements for API endpoint
                 abstract_input_hidden = gr.Textbox(visible=False, label="Abstract Input", key="abstract_hidden")
@@ -627,15 +629,24 @@ def create_interface():
                 )
 
                 # Add flagging handlers
+                def handle_paper_feedback(*args):
+                    paper_match_logger.flag(list(args))
+                    return gr.update(visible=True, value="Thank you for your feedback!")
+
+                def handle_analysis_feedback(*args):
+                    analysis_logger.flag(list(args))
+                    return gr.update(visible=True, value="Thank you for your feedback!")
+
                 flag_paper_btn.click(
-                    lambda *args: paper_match_logger.flag(list(args)),
+                    handle_paper_feedback,
                     inputs=[abstract_input, paper_details_output, paper_feedback, paper_expert, paper_comment],
+                    outputs=[paper_feedback_ack],
                     preprocess=False,
                     api_name=False,
                 )
 
                 flag_analysis_btn.click(
-                    lambda *args: analysis_logger.flag(list(args)),
+                    handle_analysis_feedback,
                     inputs=[
                         abstract_input,
                         paper_details_output,
@@ -644,6 +655,7 @@ def create_interface():
                         analysis_expert,
                         analysis_comment,
                     ],
+                    outputs=[analysis_feedback_ack],
                     preprocess=False,
                     api_name=False,
                 )