Refactor feedback components into accordions for improved organization and user experience

app.py

@@ -590,18 +590,19 @@ def create_interface():
                     key="paper_details",
                 )
                 analyze_btn = gr.Button("Analyze Connections", variant="primary", visible=False)
-                gr.Markdown(
-                    """
-                    Please provide feedback on the paper match and analysis to improve the model.
-                    """
-                )
-                # Add thumbs up/down for paper match
-                paper_feedback = gr.Radio(
-                    ["👍 Good Match", "👎 Poor Match"], label="Is this paper a good match?", visible=False
-                )
-                paper_expert = gr.Checkbox(label="I am an expert in this field", value=False, visible=False)
-                paper_comment = gr.Textbox(label="Additional feedback on this paper match (optional)", visible=False)
-                flag_paper_btn = gr.Button("Submit Paper Feedback", visible=False)
+                with gr.Accordion(label="Feedback and Flagging", open=True, visible=False) as paper_feedback_accordion:
+                    gr.Markdown(
+                        """
+                        Please provide feedback on the paper match and analysis to improve the model.
+                        """
+                    )
+                    # Add thumbs up/down for paper match
+                    paper_feedback = gr.Radio(
+                        ["👍 Good Match", "👎 Poor Match"], label="Is this paper a good match?",
+                    )
+                    paper_expert = gr.Checkbox(label="I am an expert in this field", value=False)
+                    paper_comment = gr.Textbox(label="Additional feedback on this paper match (optional)")
+                    flag_paper_btn = gr.Button("Submit Paper Feedback")
 
             with gr.Column(scale=1):
                 analysis_output = gr.Markdown(
@@ -611,12 +612,20 @@ def create_interface():
                     show_copy_button=True,
                     key="analysis_output",
                 )
-                # Add thumbs up/down for analysis
-                analysis_feedback = gr.Radio(
-                    ["👍 Helpful", "👎 Not Helpful"], label="Was this analysis helpful?", visible=False
-                )
-                analysis_comment = gr.Textbox(label="Additional feedback on analysis (optional)", visible=False)
-                flag_analysis_btn = gr.Button("Submit Analysis Feedback", visible=False)
+                with gr.Accordion(label="Feedback and Flagging", open=True, visible=False) as analysis_feedback_accordion:
+                    gr.Markdown(
+                        """
+                        The analysis is generated by an AI model and may not be perfect.
+                        If you find any errors or have suggestions for improvement, please let us know.
+                        Your feedback is valuable and will be used to improve the model and prompt.
+                        """
+                    )
+                    # Add thumbs up/down for analysis
+                    analysis_feedback = gr.Radio(
+                        ["👍 Helpful", "👎 Not Helpful"], label="Was this analysis helpful?", visible=False
+                    )
+                    analysis_comment = gr.Textbox(label="Additional feedback on analysis (optional)", visible=False)
+                    flag_analysis_btn = gr.Button("Submit Analysis Feedback", visible=False)
 
         # Set up logging directories
         data_path = "/data" if persistent_storage else "./data"
@@ -629,18 +638,10 @@ def create_interface():
             data_path + "/flagged_paper_matches",
         )
         analysis_logger.setup(
-            [paper_details_output, analysis_output, analysis_feedback, analysis_comment],
+            [abstract_input, paper_details_output, analysis_output, analysis_feedback, analysis_comment],
             data_path + "/flagged_analyses",
         )
 
-        # Show feedback component
-        def show_feedback():
-            return gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
-
-        # Hide feedback component
-        def hide_feedback():
-            return gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
-
         # Display paper details when row is selected
         def on_select(evt: gr.SelectData, papers, query):
             selected_index = evt.index[0]  # Get the row index
@@ -687,7 +688,7 @@ def create_interface():
             outputs=[analyze_btn],
             api_name=False,
         ).then(
-            show_feedback,
+            lambda: gr.update(visible=True), gr.update(visible=True), gr.update(visible=True),  # Show feedback options
             outputs=[paper_feedback, paper_comment, flag_paper_btn],
             api_name=False,
         )