update 4

app.py

@@ -68,16 +68,7 @@ def app():
             ('General Medicine', 'RespiratoryFishman', 'RespiratoryMurray', 'MedMRCP2', 'OldMedicine')
         )
 
-        # Define the chain using LCEL
-        condense_question_chain = RunnableLambda(lambda x: {"chat_history": chistory, "question": x}) | CONDENSE_QUESTION_PROMPT | llmc
-        retriever_chain = RunnableLambda(lambda x: {"standalone_question": x}) | retriever | _combine_documents
-        answer_chain = ANSWER_PROMPT | llm
-        
-        conversational_qa_chain = RunnableParallel(
-            condense_question=condense_question_chain,
-            retrieve=retriever_chain,
-            generate_answer=answer_chain
-        )
+
         
         # Define retrievers based on option
         persist_directory = {
@@ -98,6 +89,18 @@ def app():
         
         vectordb = Chroma(persist_directory=persist_directory, embedding_function=embedding_function, collection_name=collection_name)
         retriever = vectordb.as_retriever(search_kwargs={"k": 5})
+
+
+    # Define the chain using LCEL
+    condense_question_chain = RunnableLambda(lambda x: {"chat_history": chistory, "question": x}) | CONDENSE_QUESTION_PROMPT | llmc
+    retriever_chain = RunnableLambda(lambda x: {"standalone_question": x}) | retriever | _combine_documents
+    answer_chain = ANSWER_PROMPT | llm
+        
+    conversational_qa_chain = RunnableParallel(
+        condense_question=condense_question_chain,
+        retrieve=retriever_chain,
+        generate_answer=answer_chain
+    )    
     
     if "messages" not in st.session_state:
         st.session_state.messages = [{"role": "assistant", "content": "How may I help you?"}]