Update app.py

app.py

@@ -16,39 +16,41 @@ class ContextAwareResponseGenerator:
         self.llm = llm
         self.response_prompt = PromptTemplate(
             input_variables=['context', 'query', 'chat_history'],
-            template="""Analyze the context, query, and chat history to generate an optimal response:
+            template="""Based on the context, query, and chat history, generate a clear, concise, and helpful response.
 
 Context: {context}
 Query: {query}
 Chat History: {chat_history}
 
-Response Structure Selection Criteria:
+Response Structure Selection Criteria (internal):
 1. Technical academic breakdown
 2. Concise summary with key points
 3. Markdown with hierarchical insights
 4. Narrative explanation
 5. Comparative analysis
 
-Choose the most appropriate response structure (1-5) and generate the response accordingly:"""
+Generate the response based on the appropriate structure, but do not display structure selection to the user. Only show the final response."""  # This internal prompt generates the response.
         )
         self.response_chain = LLMChain(llm=self.llm, prompt=self.response_prompt)
 
     def generate_response(self, context, query, chat_history=''):
         try:
-            # Generate structured response
-            full_response = self.response_chain.run({
+            # Generate structured response internally
+            response = self.response_chain.run({
                 'context': context,
                 'query': query,
                 'chat_history': chat_history or "No previous context"
             })
             
-            # Extract only the actual response content (after the structure selection)
-            response_content = full_response[1:].strip()
-            
-            return response_content
+            # Optionally process response internally (e.g., format it based on structure) 
+            # but only return the final formatted response.
+            return response.strip()
         except Exception as e:
             logging.error(f"Response generation error: {e}")
-            return f"I couldn't generate a response for: {query}"
+            return self._default_response(query)
+
+    def _default_response(self, query):
+        return f"I couldn't generate a response for: {query}"
 
 class AdvancedPdfChatbot:
     def __init__(self, openai_api_key):
@@ -135,4 +137,4 @@ with gr.Blocks() as demo:
     msg.submit(respond, inputs=[msg, chatbot_interface], outputs=[msg, chatbot_interface])
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()