Update common/ResponseValidation.py

common/ResponseValidation.py

@@ -34,44 +34,84 @@ First Person: No
         return False
 
 
-def matches_user_speaking_style(answer, transcript_text, processor_llm):
+def matches_user_speaking_style(answer, transcript_text, processor_llm, user_profile, agent_question):
     """
     Uses the LLM to determine if the answer matches the tone and style of the user's prior speaking style in the transcript.
     Returns True if similar, False otherwise.
+    Incorporates logic to skip style matching for factual questions and uses profile-based criteria.
     """
-    prompt = f"""
-You are a writing style and tone analyst.
-Given a new response and a prior interview transcript, determine whether the tone, language, and style of the new response matches the user’s typical speaking style.
+    logging.info("[Style Match Check] Entry")
+    
+    try:
+        # Get communication profile
+        style = user_profile.get_field("Communication", "Style")
+        tone = user_profile.get_field("Communication", "Tone")
+        length = user_profile.get_field("Communication", "Length")
+        topics = user_profile.get_field("Communication", "Topics")
 
-Transcript (how the user usually talks):
-\"\"\"{transcript_text}\"\"\"
+        # Identify factual-type question
+        factual_keywords = [
+            "name", "age", "where are you from", "where do you live", "occupation",
+            "birthplace", "what do you do", "how old", "which city", "which country"
+        ]
+        lower_q = agent_question.strip().lower()
+        is_factual = any(kw in lower_q for kw in factual_keywords)
 
-New Response:
-\"\"\"{answer}\"\"\"
+        if is_factual:
+            logging.info("[Style Match Check] Question is factual — skipping style comparison")
+            return True
 
-Does the new response sound like it could have come from the same person, in terms of tone, phrasing, and writing style?
+        prompt = f"""
+        You are a writing style and tone analyst.
+        
+        Your job is to assess whether a new response sounds like it was written by the same person who spoke in the interview transcript — considering phrasing, vocabulary, tone, and sentence structure.
+        
+        ---
+        ### Prior Interview Transcript (how the user usually talks):
+        \"\"\"{transcript_text}\"\"\"
+        
+        ---
+        ### New Response:
+        \"\"\"{answer}\"\"\"
+        
+        ---
+        ### Style Profile Reference:
+        - Style: {style}
+        - Tone: {tone}
+        - Preferred Length: {length}
+        - Topics: {topics}
+        
+        ---
+        ### Instructions:
+        - Check if the *tone*, *style*, and *language* of the new response align with the transcript.
+        - Use the style profile for reference.
+        - Focus on phrasing, formality, sentence structure, expressiveness, and personal flair.
+        - Ignore topic similarity — you’re assessing delivery style.
+        - Reply only with one of the following:
+        
+        Style Match: Yes  
+        or  
+        Style Match: No
+                """
 
-Answer only:
-Style Match: Yes
-or
-Style Match: No
-"""
-    try:
-        logging.info("[Style Match Check] Invoking LLM to compare tone and style with prior transcript")
+        logging.info("[Style Match Check] Invoking LLM with style comparison prompt")
         response = processor_llm.invoke(prompt)
         result = response.content.strip().lower()
+
         if "style match: yes" in result:
+            logging.info("[Style Match Check] Match confirmed")
             return True
         elif "style match: no" in result:
+            logging.info("[Style Match Check] Style mismatch detected")
             return False
         else:
-            logging.warning(f"Unexpected output format in style match check: {result}")
+            logging.warning(f"[Style Match Check] Unexpected response format: {result}")
             return False
+
     except Exception as e:
-        logging.error(f"LLM failed during style match check: {e}")
+        logging.error(f"[Style Match Check] LLM failed during comparison: {e}")
         return False
 
-
 def validate_response(question, answer, user_profile_str, fast_facts_str, interview_transcript_text, respondent_type, ai_evaluator_agent, processor_llm):
     llm_mode_prompt = f"""
     You are an expert in market research interview analysis. Given the following question, determine if it is:
@@ -131,9 +171,6 @@ def validate_response(question, answer, user_profile_str, fast_facts_str, interv
                 if not is_first_person(answer, processor_llm):
                     logging.warning("Did not pass style due to 3rd person use")
                     return False
-                #if not matches_user_speaking_style(answer, interview_transcript_text, processor_llm):
-                    #logging.warning("Did not match user's speaking style from transcript")
-                    #return False
                 return True
         return False
     else:
@@ -166,8 +203,5 @@ def validate_response(question, answer, user_profile_str, fast_facts_str, interv
                 if not is_first_person(answer, processor_llm):
                     logging.warning("Did not pass style due to 3rd person use")
                     return False
-                #if not matches_user_speaking_style(answer, interview_transcript_text, processor_llm):
-                    #logging.warning("Did not match user's speaking style from transcript")
-                    #return False
                 return True
         return False