Update app.py

app.py

@@ -21,10 +21,32 @@ from langchain.memory.buffer import ConversationBufferMemory
 
 
 HUGGINGFACEHUB_API_TOKEN = os.environ.get("HUGGINGFACEHUB_API_TOKEN")
+BOOKING_ID = r'\b[A-Z]{6}\d{6}\b'
+BOOKING_KEYWORDS = [
+    "booking",
+    "bestillingsnummer",
+    "bookingen",
+    "ordrenummer",
+    "reservation",
+    "rezerwacji",
+    "bookingreferanse",
+    "rezerwacja",
+    "logg inn",
+    "booket",
+    "reservation number",
+    "bestilling",
+    "order number",
+    "booking ID",
+    "identyfikacyjny płatności"
+]
+
 
 daysoff_assistant_booking_template = """
-You are a customer support assistant for Daysoff.no. Your expertise is
-retrieving booking information for a given booking ID."
+You are a Norwegian customer support AI assistant for Daysoff.no. By default, 
+you respond in Norwegian to user question: {question}. In all other cases,
+adapt to user's language and respond accordingly. 
+You can retrieving booking information for a given booking ID and provide 
+general helpful info about Daysoff's services."
 Chat History: {chat_history}
 Question: {question}
 Answer:
@@ -41,19 +63,20 @@ Your task is to construct the most efficient API URL to answer
 the user's question, ensuring the
 call is optimized to include only the necessary information.
 Question: {question}
+API URL:
 """
 api_url_prompt = PromptTemplate(input_variables=['api_docs', 'question'],
                                 template=api_url_template)
 
 api_response_template = """
 With the API Documentation for Daysoff's official API: {api_docs}
-and the specific user question: {question} in mind,
+in mind, and IF {question} contains keywords from:{BOOKING_KEYWORDS},
 and given this API URL: {api_url} for querying, here is the
 response from Daysoff's API: {api_response}.
-Please provide user with their booking information,
-focusing on delivering the answer with clarity and conciseness,
-as if a human customer service agent is providing this information.
-Adapt to user's language. By default, you speak Norwegian.
+Please provide a summary that directly addresses the user's question, 
+omitting technical details like response format, and 
+focusing on delivering the answer with clarity and conciseness, 
+as if Daysoff's kundeservice is providing this information themselves.
 Booking Info:
 """
 
@@ -62,11 +85,9 @@ api_response_prompt = PromptTemplate(
     template=api_response_template
 )
 
-
 @cl.on_chat_start
 def setup_multiple_chains():
-    #llm = HuggingFaceEndpoint(repo_id="google/gemma-2-2b-it")
-
+    
     llm = HuggingFaceEndpoint(
     repo_id="google/gemma-2-2b-it", 
     huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN, 
@@ -97,46 +118,47 @@ def setup_multiple_chains():
 
 
     cl.user_session.set("api_chain", api_chain)
+    
+import re
 
-BOOKING_ID = r'\b[A-Z]{6}\d{6}\b'
-
-BOOKING_KEYWORDS = [
-    "booking",
-    "bestillingsnummer",
-    "bookingen",
-    "ordrenummer",
-    "reservation",
-    "rezerwacji",
-    "bookingreferanse",
-    "rezerwacja",
-    "logg inn",
-    "booket",
-    "reservation number",
-    "bestilling",
-    "order number",
-    "booking ID",
-    "identyfikacyjny płatności"
-]
-
+def extract_booking_id(user_message):
+# Extract booking ID from user message
+    match = re.search(r'\b[A-Z]{6}\d{6}\b', user_message) 
+    return match.group(0) if match else None
+    
 @cl.on_message
 async def handle_message(message: cl.Message):
     user_message = message.content.lower()
     llm_chain = cl.user_session.get("llm_chain")
     api_chain = cl.user_session.get("api_chain")
 
-    is_booking_query = any(
-        re.search(keyword, user_message, re.IGNORECASE) # re.search(keyword, r'\b[A-Z]{6}\d{6}\b', user_message, re.IGNORECASE)
-        for keyword in BOOKING_KEYWORDS + [BOOKING_ID]
-    )
-
+    # booking_id = extract_booking_id(user_message)
+
+    
+    #is_booking_query = any(
+        #re.search(keyword, user_message, re.IGNORECASE) # re.search(keyword, r'\b[A-Z]{6}\d{6}\b', user_message, re.IGNORECASE)
+        #for keyword in BOOKING_KEYWORDS + [BOOKING_ID]
+    #)
+    if any(keyword in user_message for keyword in ["BOOKING_KEYWORDS"]): # could be(?): if any(keyword in user_message for keyword in BOOKING_KEYWORDS + [BOOKING_ID]
+            
+        # <f any of the keywords are in user_message>,  use api_chain
+        response = await api_chain.acall(user_message, 
+                                         callbacks=[cl.AsyncLangchainCallbackHandler()])
 
-    if is_booking_query:
-        response = await api_chain.acall(user_message,
+    elif 
+        # <or if the booking_id regex format is discovered in user message>, use api_chain
+        re.search(keyword, r'\b[A-Z]{6}\d{6}\b', user_message, re.IGNORECASE):  
+            response = await api_chain.acall(user_message, 
                                          callbacks=[cl.AsyncLangchainCallbackHandler()])
+
     else:
+        
         response = await llm_chain.acall(user_message,
                                          callbacks=[cl.AsyncLangchainCallbackHandler()])
 
     response_key = "output" if "output" in response else "text"
     await cl.Message(response.get(response_key, "")).send()
-    return message.content
+    return message.content
+    
+# await cl.Message(response.get(response_key, "")).send()
+# content=f"Her er informasjonen for bestillingsnummer {booking_id}:\n{booking_info}").send()