Update common/validation_utils.py

common/validation_utils.py

@@ -7,17 +7,40 @@ from RespondentAgent import *
 from langchain_groq import ChatGroq
 
 
-def is_first_person(answer):
+def is_first_person_llm(answer, processor_llm):
     """
-    Checks if the answer is written in first person.
-    Returns True if first person pronouns are found and third person references are not dominant.
+    Uses LLM to determine whether the response is written in first person.
+    Returns True if the LLM determines the response is first-person, else False.
     """
-    logging.debug(f"Checking if answer is first person: {answer}")
-    # Look for first person pronouns
-    first_person = re.search(r'\b(I|my|me|mine|we|our|us|ours)\b', answer, re.IGNORECASE)
-    # Look for third person references (e.g., "he", "she", "they", or a capitalized name at the start)
-    third_person = re.search(r'\b(he|she|they|his|her|their|him|them)\b', answer, re.IGNORECASE)
-    return bool(first_person) and not bool(third_person)
+    prompt = f"""
+You are an expert in analyzing 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 such as "I", "me", "my", "mine", "we", "our", or "us" and is written from the perspective of the speaker.
+
+Do not guess. Only say "Yes" if the writing is clearly in first person. Otherwise, say "No".
+
+Response:
+\"\"\"{answer}\"\"\"
+
+Output strictly in the following format:
+First Person: Yes
+or
+First Person: No
+"""
+    try:
+        response = processor_llm.invoke(prompt)
+        content = response.content.strip().lower()
+        if "first person: yes" in content:
+            return True
+        elif "first person: no" in content:
+            return False
+        else:
+            logging.warning(f"Unexpected output format from LLM for first person check: {content}")
+            return False
+    except Exception as e:
+        logging.error(f"LLM failed during first person check: {e}")
+        return False
 
 
 def validate_response(question, answer, user_profile_str, fast_facts_str, interview_transcript_text, respondent_type, ai_evaluator_agent, processor_llm):