feat: Update feedback handling to use highlighted text with categories

app.py

@@ -1,4 +1,3 @@
-import re
 import gradio as gr
 
 from src.constants import FULL_QUESTIONS
@@ -25,11 +24,11 @@ def handle_question_change(history, selected_question, conversation_mode):
 
     if conversation_mode == 'Interviewer':
         updated_label = f"Conversation turns: {current_turns}"
-        feedback_box_state = gr.update(interactive=False, placeholder="Feedback for each conversation turn, as well as an overall feedback for the entire conversation, will be displayed here", value="")
+        feedback_box = gr.update(value=None)
         
     else:
         updated_label = "Multimodal Coach Agent"
-        feedback_box_state = gr.update(interactive=False, placeholder="Coach mode does not provide feedback", value="")
+        feedback_box = gr.update(value=None, show_legend=False)
 
     if len(history) > 1:
         first_question_selected = True
@@ -39,7 +38,7 @@ def handle_question_change(history, selected_question, conversation_mode):
 
         transition_message = f"Alright, let's move on to the next question:\n\n{selected_question}"
 
-        return [("I'm ready for the next question now.", transition_message)], gr.update(interactive=False), gr.update(interactive=True), gr.update(label=updated_label), feedback_box_state
+        return [("I'm ready for the next question now.", transition_message)], gr.update(interactive=False), gr.update(interactive=True), gr.update(label=updated_label), feedback_box
     else:
         if selected_question:
             last_question = f"Great start! Here's your first question:\n\n{selected_question}"
@@ -48,7 +47,7 @@ def handle_question_change(history, selected_question, conversation_mode):
 
         new_history = history + [("One moment...", last_question)]
 
-        return [entry for entry in new_history if entry[1] is not None], gr.update(interactive=False), gr.update(interactive=True), gr.update(label=updated_label), feedback_box_state
+        return [entry for entry in new_history if entry[1] is not None], gr.update(interactive=False), gr.update(interactive=True), gr.update(label=updated_label), feedback_box
 
 def reset_interface(conversation_mode):
     global session_id, first_question_selected, current_turns, interview_data_with_feedback
@@ -69,9 +68,8 @@ def reset_interface(conversation_mode):
         )
         slider_state = gr.update(interactive=True)
 
-        feedback_box_state = gr.update(interactive=False, placeholder="Feedback for each conversation turn, as well as an overall feedback for the entire conversation, will be displayed here", value="")
+        feedback_box = gr.update(value=None)
         feedback_type_state = gr.update(interactive=True, value="Standard")
-
     else:
         chatbot_label = "Multimodal Coach Agent"
         session_id = generate_session_id()
@@ -85,7 +83,7 @@ def reset_interface(conversation_mode):
         )
         slider_state = gr.update(interactive=False)
 
-        feedback_box_state = gr.update(interactive=False, placeholder="Coach mode does not provide feedback", value="")
+        feedback_box = gr.update(value=None, show_legend=False)
         feedback_type_state = gr.update(interactive=False, value=" ")
 
     return (
@@ -94,10 +92,15 @@ def reset_interface(conversation_mode):
         "",  
         gr.update(value="Send", interactive=False),
         slider_state,
-        feedback_box_state,
+        feedback_box,
         feedback_type_state
     )
 
+def highlight_feedback(feedback_output):
+    if not feedback_output["feedback_by_category"]:
+        return False, [(feedback_output["feedback_text"], None)]
+    return True, [(item["text"], item["category"]) for item in feedback_output["feedback_by_category"]]
+
 # Gradio interface
 def create_demo():
     with gr.Blocks() as demo:
@@ -127,9 +130,15 @@ def create_demo():
                     interactive=False,
                     allow_custom_value=True
                 )
-
+    
         chatbot = gr.Chatbot(label="""The Multimodal Chatbot will be ready once you select a mode""")
-        feedback_box = gr.Textbox(label="Conversation feedback", placeholder="Feedback for each conversation turn, as well as an overall feedback for the entire conversation, will be displayed here", interactive=False)
+        # feedback_box = gr.Textbox(label="Conversation feedback", placeholder="Feedback for each conversation turn, as well as an overall feedback for the entire conversation, will be displayed here", interactive=False)
+
+        feedback_box = gr.HighlightedText(
+            label="Conversation feedback",
+            show_legend=True,
+            color_map={"Strength": "green", "Area for Improvement": "orange", "Action Item": "blue"}
+        )
 
         msg = gr.Textbox(label="Type your answer here")
         send_btn = gr.Button(value="Send", variant="primary", interactive=False)  
@@ -142,7 +151,8 @@ def create_demo():
         def respond(message, history, conversation_mode, selected_question, conversation_turns_limit, feedback_type, include_company_name, include_resume_text):
             global session_id, current_turns, interview_data_with_feedback
 
-            feedback = ""
+            feedback_value = None
+            feedback_show_legend = False
 
             if not message.strip():  
                 return history, message  
@@ -158,17 +168,22 @@ def create_demo():
 
             if conversation_end_flag:
                 if conversation_mode == 'Interviewer':
-                    feedback = (
-                        f"Whole conversation feedback\n\n"
-                        f"{remove_html_tags(conversation_feedback_api_call(chat_memory['messages'], feedback_type.lower(), include_resume_text)).strip()}"
-                    )
+                    feedback_output = conversation_feedback_api_call(chat_memory['messages'], feedback_type.lower(), include_resume_text)
+                    
+                    feedback_show_legend, highlighted_feedback = highlight_feedback(feedback_output)
+                    feedback_value = [("Whole conversation feedback\n\n", None)] + highlighted_feedback
+
+                    print()
+                    print(feedback_output)
+                    print()
+                    print(highlighted_feedback)
                 return (
                     history + [(message, bot_message)],
                     "",
                     gr.update(interactive=False),
                     gr.update(interactive=False),
                     gr.update(label=updated_label),
-                    feedback,
+                    gr.update(value=feedback_value, show_legend=feedback_show_legend)
                 )
 
             if conversation_mode == 'Interviewer':
@@ -176,11 +191,20 @@ def create_demo():
                 interview_data = chat_memory['messages'][:-1]
                 print(f"{interview_data=}\n")
                 
-                raw_feedback = feedback_api_call(interview_data, feedback_type.lower(), include_resume_text)
-                feedback = f"{current_turns}º conversation turn feedback\n\n{remove_html_tags(raw_feedback).strip()}"
+                feedback_output = feedback_api_call(interview_data, feedback_type.lower(), include_resume_text)
+
+                feedback_show_legend, highlighted_feedback = highlight_feedback(feedback_output)
+                feedback_value = [(f"{current_turns}º conversation turn feedback\n\n", None)] + highlighted_feedback
+
+                print()
+                print(feedback_output)
+                print()
+                print(highlighted_feedback)
+
+                # feedback = f"{current_turns}º conversation turn feedback\n\n{remove_html_tags(feedback_output).strip()}"
                 
                 interview_data_with_feedback.extend(interview_data)
-                interview_data_with_feedback.append({"type": "feedback", "content": raw_feedback})
+                interview_data_with_feedback.append({"type": "feedback", "content": feedback_output["feedback_text"]})
 
                 print(f"{interview_data_with_feedback=}\n")
                 
@@ -201,7 +225,7 @@ def create_demo():
                 gr.update(interactive=True),
                 gr.update(interactive=True),
                 gr.update(label=updated_label),
-                feedback,
+                gr.update(value=feedback_value, show_legend=feedback_show_legend)
             )
 
         conversation_mode.change(fn=reset_interface, inputs=conversation_mode, outputs=[chatbot, question_dropdown, msg, send_btn, conversation_turns_limit, feedback_box, feedback_type_dropdown])

src/api_calls.py

@@ -1,3 +1,5 @@
+import json
+
 from .constants import (
     JOB_DESCRIPTION,
     RESUME_TEXT
@@ -51,7 +53,8 @@ def feedback_api_call(interview_data, feedback_type, include_resume_text):
     response = api_call(QUESTION_RELATED_FEEDBACK_API_ENDPOINT, data)
 
     if response.status_code == 200:
-        return response.text
+        print(response.text)
+        return json.loads(response.text)
     else:
         return f"Error: Received status code {response.status_code} from the API"
 
@@ -85,6 +88,6 @@ def conversation_feedback_api_call(interview_data, feedback_type, include_resume
     response = api_call(CONVERSATIONAL_MODEL_FEEDBACK_API_ENDPOINT, data)
 
     if response.status_code == 200:
-        return response.text
+        return json.loads(response.text)
     else:
         return f"Error: Received status code {response.status_code} from the API"