Update app.py

app.py

@@ -24,10 +24,10 @@ OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
 daysoff_assistant_template = """
 You are a customer support assistant (’kundeservice AI assistent’) for Daysoff.no
 By default, you respond in Norwegian language, using a warm, direct and professional tone. 
-You can provide information associated with a given booking ID, answer frequently asked questions (FAQ) about DaysOff firmahytteordning for 
-employees: {ansatte_faq_data} and for employers:{utleiere_faq_data}.
-To understand how best to answer queries about privacy policy, 
-refer to {help2} and {personvernspolicy_data}
+You are equipped to assist users by providing detailed information linked to specific 
+booking IDs (bestillingskode), offering general insights about DaysOff's services, addressing 
+questions related to the company's privacy policy (personvernspolicy), and answering frequently 
+asked questions about DaysOff's firmahytteordning.
 Chat History: {chat_history}
 Question: {question}
 Answer:
@@ -59,12 +59,6 @@ and focusing on delivering the answer with clarity and conciseness,
 as if a human customer service agent is providing this information.
 Summary:
 """
-## --"default"
-#Please provide an summary (in Norwegian) that directly addresses the user's question,
-#and focusing on delivering the answer with clarity and conciseness,
-#as if a human customer service agent is providing this information.
-#Summary:
-
 
 api_response_prompt = PromptTemplate(
     input_variables=['api_docs', 'question', 'api_url', 'api_response'],
@@ -126,7 +120,13 @@ async def handle_message(message: cl.Message):
               
             },
             callbacks=[cl.AsyncLangchainCallbackHandler()])
+
+    elif any(keyword in user_message for keyword in ["firmahytteordning", "personvernspolicy",
+                                                   "faq_ansatte", "faq_utleiere"]): 
         
+        response = await api_chain.acall(user_message,
+                                         callbacks=[cl.AsyncLangchainCallbackHandler()])
+    
     else:    
         response = await llm_chain.acall(user_message, callbacks=[cl.AsyncLangchainCallbackHandler()])