Update interview.py

interview.py

@@ -11,10 +11,10 @@ class Interview:
     def __init__(self):
         self.question_count = 0
         self.history: List[tuple] = []
-        self.general_impression: str = ""
-        self.interview_instructions = load_interview_instructions()
+        self.general_impression: str = ""  # This will be set from the previous analysis
 
     def set_general_impression(self, impression: str):
+        # This method will be called with the general_impression from processing.py or app.py
         self.general_impression = impression
 
     def process_message(self, message: str) -> str:
@@ -24,21 +24,20 @@ class Interview:
         # Generate next question or final report
         if self.question_count < 10:
             prompt = f"""
-            Your are a Psychologist or a Psychiatrist and conducting a clinical interview.
-            
+            You are a Psychologist or a Psychiatrist conducting a clinical interview about the speaker analyzed in the video.
             Use the following information to generate the next question:
             
-            General Impression: {self.general_impression}
+            General Impression from previous analysis: {self.general_impression}
             Context from knowledge base: {relevant_docs}
             Full conversation history:
             {self._format_history()}
             Current answer: {message}
             Question count: {self.question_count + 1}/10
 
-            Based on all this information, generate the next appropriate question for the clinical interview.
-            Important: Your question MUST be a direct follow-up to the most recent answer, while also considering 
-            the entire conversation history. Ensure that your question builds upon the information just provided 
-            and explores it further or shifts to a related topic based on what was just said.
+            Based on all this information, generate the next appropriate question for the clinical interview about the speaker.
+            Important: Your question MUST be a direct follow-up to the most recent answer, while also considering
+            the entire conversation history and the initial general impression. Ensure that your question builds upon 
+            the information just provided and explores it further or shifts to a related topic based on what was just said.
             """
             response = llm.invoke(prompt)
             self.question_count += 1
@@ -46,14 +45,16 @@ class Interview:
             return response.content
         else:
             prompt = f"""
-            Based on the following information, generate a comprehensive clinical report (also make use of technical clinical terms from the provided documents or knowledge base):
-            General Impression: {self.general_impression}
+            Based on the following information, generate a comprehensive clinical report about the speaker 
+            (also make use of technical clinical terms from the provided documents or knowledge base):
+            General Impression from previous analysis: {self.general_impression}
             Context from knowledge base: {relevant_docs}
             Full conversation:
             {self._format_history()}
             Final answer: {message}
 
-            Provide a detailed clinical analysis based on the entire interview.
+            Provide a detailed clinical analysis of the speaker based on the initial general impression and the entire interview.
+            Compare and contrast the insights gained from the interview with the initial general impression.
             """
             response = llm.invoke(prompt)
             self.question_count = 0  # Reset for next interview
@@ -63,14 +64,13 @@ class Interview:
 
     def start_interview(self) -> str:
         prompt = f"""
-        Your are a Psychologist or a Psychiatrist and starting a clinical interview.
-        
+        You are a Psychologist or a Psychiatrist starting a clinical interview about the speaker analyzed in the video.
         Based on the following information, generate an appropriate opening question:
         
-        General Impression: {self.general_impression}
-        Interview Instructions: {self.interview_instructions}
+        General Impression from previous analysis: {self.general_impression}
 
-        Provide a warm, engaging opening question that sets the tone for the clinical interview and encourages the individual to start sharing about themselves.
+        Provide a warm, engaging opening question that sets the tone for the clinical interview and encourages 
+        discussion about the speaker, based on the general impression provided from the previous analysis.
         """
         response = llm.invoke(prompt)
         return response.content