Update app.py

app.py

@@ -8,6 +8,13 @@ from langchain.embeddings import OpenAIEmbeddings
 from langchain.chains import RetrievalQA
 from langchain.chat_models import ChatOpenAI
 
+dataset_names = ["zelros/pj-ca", "zelros/pj-ce", "zelros/pj-da", 
+                 "zelros/pj-groupama", "zelros/pj-sg", "zelros/pj-lbp"]
+
+insurers = ["Crédit Agricole","Caisse d'Epargne","Direct Assurance","Groupama","Société Générale","La Banque Postale"]
+
+db_dict = {}
+
 def llm_response(insurer1, insurer2, question):
     qa_chain1 = RetrievalQA.from_chain_type(llm1, retriever=db_dict[insurer1].as_retriever(search_kwargs={'k': 15}))
     qa_chain2 = RetrievalQA.from_chain_type(llm2, retriever=db_dict[insurer2].as_retriever(search_kwargs={'k': 15}))
@@ -20,13 +27,6 @@ examples = [
     [None, None, "Comment résilier le contrat ?"]
 ]
 
-dataset_names = ["zelros/pj-ca", "zelros/pj-ce", "zelros/pj-da", 
-                 "zelros/pj-groupama", "zelros/pj-sg", "zelros/pj-lbp"]
-
-insurers = ["Crédit Agricole","Caisse d'Epargne","Direct Assurance","Groupama","Société Générale","La Banque Postale"]
-
-db_dict = {}
-
 for i, name in enumerate(dataset_names):
     dataset = load_dataset(name)