Update app.py

app.py

@@ -68,8 +68,21 @@ class AdvancedPdfChatbot:
         )
         self.overall_chain = self.CustomChain(refinement_chain=refinement_chain, qa_chain=qa_chain)
 
+        def setup_conversation_chain(self):
+        refinement_chain = LLMChain(
+            llm=self.refinement_llm,
+            prompt=self.refinement_prompt,
+            output_key='refined_query'
+        )
+        qa_chain = ConversationalRetrievalChain.from_llm(
+            self.llm,
+            retriever=self.db.as_retriever(),
+            memory=self.memory,
+            combine_docs_chain_kwargs={"prompt": self.prompt}
+        )
+        self.overall_chain = self.CustomChain(refinement_chain=refinement_chain, qa_chain=qa_chain)
+
     class CustomChain(Chain):
-        
         def __init__(self, refinement_chain, qa_chain):
             super().__init__()
             self.refinement_chain = refinement_chain
@@ -87,34 +100,13 @@ class AdvancedPdfChatbot:
             query = inputs['query']
             chat_history = inputs.get('chat_history', [])
             
-            # Run the refinement chain to refine the query
             refined_query = self.refinement_chain.run({'query': query, 'chat_history': chat_history})
-            
-            # Run the QA chain using the refined query and the chat history
             response = self.qa_chain({'question': refined_query, 'chat_history': chat_history})
             
-            # Return the answer
             return {"answer": response['answer']}
 
 
 
-    def setup_conversation_chain(self):
-        if not self.db:
-            raise ValueError("Database not initialized. Please upload a PDF first.")
-            
-        refinement_chain = LLMChain(
-            llm=self.refinement_llm,
-            prompt=self.refinement_prompt,
-            output_key='refined_query'
-        )
-        qa_chain = ConversationalRetrievalChain.from_llm(
-            self.llm,
-            retriever=self.db.as_retriever(),
-            memory=self.memory,
-            combine_docs_chain_kwargs={"prompt": self.prompt}
-        )
-        self.overall_chain = CustomChain(refinement_chain=refinement_chain, qa_chain=qa_chain)
-
 
     def chat(self, query):
         if not self.overall_chain: