Update researchsimulation/InteractiveInterviewChatbot.py

researchsimulation/InteractiveInterviewChatbot.py

@@ -240,6 +240,7 @@ def generate_generic_answer(agent_name, agent_question, respondent_agent, respon
             - Do **not** speak as an individual or use "I", "my", or "me".
             - Avoid personal anecdotes—focus on shared behaviours, preferences, or perceptions.
             - If there is diversity of opinion, include it naturally (e.g., "some of us...", "others felt...").
+            - If the group does not have **direct experience** with the topic, acknowledge that honestly. Do not fabricate experiences. It's okay to say "none of us have ..., but we’ve heard..." or "we can’t comment from experience."
             """
         else:
             persona_description = f"You are {agent_name}. You represent an individual user with a unique point of view."
@@ -440,24 +441,26 @@ def validate_generic_answer(agent_name, agent_question, generic_answer, user_pro
         logging.exception("[validate_generic_answer] Exception during validation")
         return False, "Exception during validation"
 
-def validate_styled_answer(agent_name, agent_question, styled_answer, user_profile, processor_llm):
+def validate_styled_answer(agent_name, agent_question, styled_answer, user_profile, processor_llm, respondent_type):
     """
-    Validates whether the styled answer matches the user's typical speaking style using communication profile.
-    Returns (True, explanation) if stylistically aligned, (False, explanation) otherwise.
+    Validates whether the styled answer matches the user's speaking style (individual or focus group).
+    Returns (True, explanation) if aligned, (False, explanation) otherwise.
     """
     logging.info("[validate_styled_answer] Entry")
+
     try:
         is_valid, explanation = matches_user_speaking_style(
             answer=styled_answer,
             processor_llm=processor_llm,
             user_profile=user_profile,
             agent_question=agent_question,
+            respondent_type=respondent_type,
             return_explanation=True
         )
-        logging.info(f"[validate_styled_answer] Style validation result: {is_valid}, explanation: {explanation}")
+        logging.info(f"[validate_styled_answer] Validation result: {is_valid}, explanation: {explanation}")
         return is_valid, explanation
     except Exception as e:
-        logging.exception("[validate_styled_answer] Exception during style validation")
+        logging.exception("[validate_styled_answer] Exception during validation")
         return False, "Exception during style validation"
 
 
@@ -537,7 +540,7 @@ def ask_interview_question(respondent_agents_dict, last_active_agent, question,
                     continue
 
                 is_valid, style_feedback = validate_styled_answer(
-                    agent_name, agent_question, styled, user_profile, processor_llm
+                    agent_name, agent_question, styled, user_profile, processor_llm, respondent_type
                 )
                 if is_valid:
                     tailored_answer = styled