Update common/ResponseValidation.py

common/ResponseValidation.py

@@ -21,10 +21,8 @@ You are an expert in analysing writing style and narrative perspective.
 Determine whether the following response is written from a first-person point of view.
 A first-person response includes pronouns like "I", "me", "my", "mine", "we", "our", or "us".
 Say "First Person: Yes" only if clearly first-person, else say "First Person: No".
-
 Response:
 \"\"\"{answer}\"\"\"
-
 Output format:
 First Person: Yes
 or
@@ -56,25 +54,20 @@ First Person: No
         # --- Step 4: Style validation prompt ---
         style_check_prompt = f"""
 You are a communication coach and writing style analyst.
-
 Evaluate whether the following response aligns with the given communication profile.
-
 ---
 ### Response:
 \"\"\"{answer}\"\"\"
-
 ### Communication Profile:
 - Style: {style}
 - Tone: {tone}
 - Preferred Length: {length}
 - Common Topics: {topics}
-
 ---
 ### Instructions:
 - Does the writing match the tone, style, and sentence structure described?
 - Is the language aligned in formality, expressiveness, and delivery?
 - Respond only with one of the following:
-
 Style Match: Yes  
 or  
 Style Match: No
@@ -87,7 +80,27 @@ Style Match: No
             logging.info("[Style Match Check] Match confirmed")
             return True
         elif "style match: no" in style_result:
-            logging.info("[Style Match Check] Style mismatch detected")
+            # --- New: Ask LLM for explanation on mismatch ---
+            explanation_prompt = f"""
+You are a communication coach and writing style analyst.
+The following response was evaluated as NOT matching the given communication profile.
+Please provide a concise reason why the style does not match.
+
+---
+### Response:
+\"\"\"{answer}\"\"\"
+### Communication Profile:
+- Style: {style}
+- Tone: {tone}
+- Preferred Length: {length}
+- Common Topics: {topics}
+
+---
+### Please provide a short reason for style mismatch:
+"""
+            explanation_response = processor_llm.invoke(explanation_prompt)
+            explanation = explanation_response.content.strip()
+            logging.info(f"[Style Match Check] Style mismatch detected: {explanation}")
             return False
         else:
             logging.warning(f"[Style Match Check] Unexpected output format: {style_result}")
@@ -99,6 +112,7 @@ Style Match: No
 
 
 
+
 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: