Update app.py

app.py

@@ -17,9 +17,9 @@ from langchain_core.prompts import PromptTemplate
 from langchain.memory.buffer import ConversationBufferMemory
 
 # ---------------------------------------------------for backend looks, example file:----------------------------------
-with open('/home/user/.local/lib/python3.10/site-packages/socketio/async_server.py', 'r') as file:
-    content = file.read()
-    print("see line 640:", content)
+#with open('/home/user/.local/lib/python3.10/site-packages/socketio/async_server.py', 'r') as file:
+    #content = file.read()
+    #print("see line 640:", content)
 # ------------------------------------------------------the end--------------------------------------------------------
 
 load_dotenv()
@@ -31,6 +31,7 @@ API_URL = "https://aivisions.no/data/daysoff/api/v1/booking/"
 #If booking information is requested, and with
 #retrieved booking information: {table} in mind, provide a conversational answer.
 #If no booking information is requested, provide a conversational answer.
+#combined_message = f"### Informasjon for Bestillingskode:\n\n{table}" 
 
 daysoff_assistant_template = """
 You are a customer support assistant for Daysoff kundeservice and help users retrieve booking information associated with their booking IDs.
@@ -50,7 +51,6 @@ daysoff_assistant_prompt = PromptTemplate(
     template=daysoff_assistant_template,
 )
 
-# -- async wrapper for requests.post
 async def async_post_request(url, headers, data):
     return await asyncio.to_thread(requests.post, url, headers=headers, json=data)
 
@@ -97,19 +97,17 @@ def setup_multiple_chains():
         return_messages=True
     )
 
-    #llm_chain = LLMChain(
-        #llm=llm,
-        #prompt=daysoff_assistant_prompt,
-        #memory=conversation_memory,
-    #)
-    llm_chain = daysoff_assistant_prompt | llm | conversation_memory
-
+    llm_chain = daysoff_assistant_prompt | llm
+    memory = conversation_memory
     cl.user_session.set("llm_chain", llm_chain)
-
+    cl.user_session.set("memory", memory)
+    
 @cl.on_message
 async def handle_message(message: cl.Message):
+    
     user_message = message.content
     llm_chain = cl.user_session.get("llm_chain")
+    memory = cl.user_session.get("memory")
 
     booking_pattern = r'\b[A-Z]{6}\d{6}\b'
     match = re.search(booking_pattern, user_message)
@@ -123,38 +121,16 @@ async def handle_message(message: cl.Message):
         payload = {"booking_id": bestillingskode}
 
         try:
-            # --async POST request
             response = await async_post_request(API_URL, headers, payload)
             response.raise_for_status()
             booking_data = response.json()
 
             if "booking_id" in booking_data:
                 try:
-                    # --markdown_table
-                    #table = (
-                        #"| 𝑭𝒊𝒆𝒍𝒅      | 𝗜𝗻𝗳𝗼                |\n"
-                        #"|:-----------|:---------------------|\n"
-                        #f"| 𝙱𝚎𝚜𝚝𝚒𝚕𝚕𝚒𝚗𝚐𝚜𝚔𝚘𝚍𝚎 | {booking_data.get('booking_id', 'N/A')} |\n"
-                        #f"| 𝙁𝙪𝙡𝙡 𝙉𝙖𝙢𝙚  | {booking_data.get('full_name', 'N/A')} |\n"
-                        #f"| 𝘼𝙢𝙤𝙪𝙣𝙩     | {booking_data.get('amount', 0)} kr |\n"
-                        #f"| 𝘾𝙝𝙚𝙘𝙠-𝙞𝙣   | {booking_data.get('checkin', 'N/A')} |\n"
-                        #f"| 𝘾𝙝𝙚𝙘𝙠-𝙤𝙪𝙩  | {booking_data.get('checkout', 'N/A')} |\n"
-                        #f"| 𝘼𝙙𝙙𝙧𝙚𝙨𝙨    | {booking_data.get('address', 'N/A')} |\n"
-                        #f"| 𝙐𝙨𝙚𝙧 𝙄𝘿    | {booking_data.get('user_id', 0)} |\n"
-                        #f"| 𝙄𝙣𝙛𝙤 𝙏𝙚𝙭𝙩  | {booking_data.get('infotext', 'N/A')} |\n"
-                        #f"| 𝙄𝙣𝙘𝙡𝙪𝙙𝙚𝙙   | {booking_data.get('included', 'N/A')} |"
-                    #)
-
-                    # --invoke LLM w/ table + user_message
                     response = await llm_chain.arun({
-                        #"table": table,
-                        #"booking_data": booking_data,
                         "question": user_message,
-                        "chat_history": ""
+                        "chat_history": memory
                     }, callbacks=[cl.AsyncLangchainCallbackHandler()])
-
-                    # --send both as combined_message
-                    #combined_message = f"### Informasjon for Bestillingskode:\n\n{table}" 
                     await cl.Message(content=combined_message).send()
 
                 except Exception as e:
@@ -168,17 +144,12 @@ async def handle_message(message: cl.Message):
 
     else:
         try:
-            # --invoke LLM w/ user_message
             response = await llm_chain.arun({
                 "question": user_message,
                 "chat_history": ""
             }, callbacks=[cl.AsyncLangchainCallbackHandler()])
 
-            # Send the LLM response as a message
-            #await cl.Message(content=response.get("text")).send()
             await cl.Message(content=response["text"]).send()
 
         except Exception as e:
             await cl.Message(content=f"Error: {str(e)}").send()
-
-