Update researchsimulation/InteractiveInterviewChatbot.py

researchsimulation/InteractiveInterviewChatbot.py

@@ -286,7 +286,7 @@ def generate_generic_answer(agent_name, agent_question, respondent_agent):
     return result
 
 
-def tailor_answer_to_profile(agent_name, generic_answer, agent_question, user_profile, respondent_agent):
+def tailor_answer_to_profile(agent_name, generic_answer, agent_question, user_profile, respondent_agent, feedback=None):
     """
     Enhances the generic answer to match the respondent's communication profile and personality traits.
     """
@@ -362,6 +362,8 @@ def tailor_answer_to_profile(agent_name, generic_answer, agent_question, user_pr
         - If the question is factual: return this answer exactly → **"{generic_answer}"**
         - If not: return a single paragraph answer that matches the respondent’s tone and style, while strictly preserving the original meaning and personal voice from this answer.
         """
+        if feedback:
+            task_description += f"\n---\n### Feedback from previous attempt:\n{feedback}\nPlease address this feedback in your rewrite.\n"
 
         logging.debug(f"[tailor_answer_to_profile] Task description preview: {task_description[:300]}...")
         logging.info("[tailor_answer_to_profile] Initialising Task and Crew objects")
@@ -416,21 +418,22 @@ def validate_generic_answer(agent_name, agent_question, generic_answer, user_pro
 def validate_styled_answer(agent_name, agent_question, styled_answer, user_profile, processor_llm):
     """
     Validates whether the styled answer matches the user's typical speaking style using communication profile.
-    Returns True if stylistically aligned, False otherwise.
+    Returns (True, explanation) if stylistically aligned, (False, explanation) otherwise.
     """
     logging.info("[validate_styled_answer] Entry")
     try:
-        is_valid = matches_user_speaking_style(
+        is_valid, explanation = matches_user_speaking_style(
             answer=styled_answer,
             processor_llm=processor_llm,
             user_profile=user_profile,
-            agent_question=agent_question
+            agent_question=agent_question,
+            return_explanation=True
         )
-        logging.info(f"[validate_styled_answer] Style validation result: {is_valid}")
-        return is_valid
+        logging.info(f"[validate_styled_answer] Style validation result: {is_valid}, explanation: {explanation}")
+        return is_valid, explanation
     except Exception as e:
         logging.exception("[validate_styled_answer] Exception during style validation")
-        return False
+        return False, "Exception during style validation"
 
 
 # --- Updated ask_interview_question Function ---
@@ -481,25 +484,29 @@ def ask_interview_question(respondent_agents_dict, last_active_agent, question,
                 responses.append(f"**PreData Moderator**: Please ask {agent_name} again.")
                 continue
 
-            def generator():
-                return tailor_answer_to_profile(agent_name, generic_answer, agent_question, user_profile, respondent_agent)
-
             tailored_attempts = 0
             max_tailored_attempts = 3
             tailored_answer = None
+            feedback = None
 
             while tailored_attempts < max_tailored_attempts:
-                styled = generator()
+                styled = tailor_answer_to_profile(
+                    agent_name, generic_answer, agent_question, user_profile, respondent_agent, feedback=feedback
+                )
 
                 if len(styled) > 2000:
                     logging.warning(f"[ask_interview_question] Styled answer too long (len={len(styled)}), retrying...")
                     tailored_attempts += 1
                     continue
 
-                if validate_styled_answer(agent_name, agent_question, styled, user_profile, processor_llm):
+                is_valid, explanation = validate_styled_answer(
+                    agent_name, agent_question, styled, user_profile, processor_llm
+                )
+                if is_valid:
                     tailored_answer = styled
                     break
 
+                feedback = explanation  # Pass explanation as feedback for next attempt
                 tailored_attempts += 1
 
             if tailored_answer: