Update app.py

app.py

@@ -28,16 +28,14 @@ from frequently_asked_questions import instruction_text_faq, faq
 OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
 
 class LLMChainConfig(BaseModel):
-    model_config = ConfigDict(extra='allow')  
-    instruction_text_faq: str
-    faq: dict
-    instruction_text_priv: str
-    personvernspolicy_data: dict
+    model_config = ConfigDict(extra='allow')
 
-    instruction_text_faq = instruction_text_faq
-    faq = faq
-    instruction_text_priv = instruction_text_priv
-    personvernspolicy_data = personvernspolicy_data
+    instruction_text_faq: str = instruction_text_faq
+    faq: dict = faq
+    instruction_text_priv: str = instruction_text_priv
+    personvernspolicy_data: dict = personvernspolicy_data
+
+     
 
 daysoff_assistant_template = """
 You are a customer support assistant (’kundeservice AI assistent’) for Daysoff. 
@@ -88,62 +86,93 @@ api_response_prompt = PromptTemplate(
     template=api_response_template
 )
 
+
 @cl.on_chat_start
 def setup_multiple_chains():
-    try:
-        llm_chain = LLMChain(
-            llm=llm,
-            prompt=daysoff_assistant_prompt,
-            memory=conversation_memory,
-            **LLMChainConfig(
-                instruction_text_faq=instruction_text_faq,
-                faq=faq,
-                instruction_text_priv=instruction_text_priv,
-                personvernspolicy_data=personvernspolicy_data
-            ).model_dump()
-        )
-        cl.user_session.set("llm_chain", llm_chain)
-    except Exception as e:
-        print(f"Error setting LLMChain: {e}")
+
+    llm = OpenAI(
+        model='gpt-3.5-turbo-instruct',
+        temperature=0.7, 
+        openai_api_key=OPENAI_API_KEY,
+        max_tokens=2048, 
+        top_p=0.9,  
+        frequency_penalty=0.1,
+        presence_penalty=0.1   
+    )
+
+    # --ConversationBufferMemory
+    conversation_memory = ConversationBufferMemory(memory_key="chat_history", 
+                                                   max_len=30,  # --retains only the last 30 exchanges
+                                                   return_messages=True,
+    )
+    
+    # --ConversationTokenBufferMemory
+    #conversation_memory = ConversationTokenBufferMemory(memory_key="chat_history",
+                                                        #max_token_limit=1318,
+                                                        #return_messages=True,
+    #)
+
+    # --ConversationSummaryMemory
+    #conversation_memory = ConversationSummaryMemory(memory_key="chat_history",
+                                                    #return_messages=True,
+    #)
+
+    llm_chain = LLMChain(
+        llm=llm,
+        prompt=daysoff_assistant_prompt,
+        memory=conversation_memory,
+        instruction_text_faq=instruction_text_faq,
+        faq=faq,
+        instruction_text_priv=instruction_text_priv,
+        personvernspolicy_data=personvernspolicy_data
+    )
+
+    
+#**LLMChainConfig(
+                #instruction_text_faq=instruction_text_faq,
+                #faq=faq,
+                #instruction_text_priv=instruction_text_priv,
+                #personvernspolicy_data=personvernspolicy_data
+           #).model_dump()
+            
     
-    try:
-        api_chain = APIChain.from_llm_and_api_docs(
-            llm=llm,
-            api_docs=api_docs_str,
-            api_url_prompt=api_url_prompt,
-            api_response_prompt=api_response_prompt,
-            verbose=True,
-            limit_to_domains=None
-        )
-        cl.user_session.set("api_chain", api_chain)
-    except Exception as e:
-        print(f"Error setting APIChain: {e}")
+    cl.user_session.set("llm_chain", llm_chain)
+
+    api_chain = APIChain.from_llm_and_api_docs(
+        llm=llm,
+        api_docs=api_docs_str,
+        api_url_prompt=api_url_prompt,
+        api_response_prompt=api_response_prompt,
+        verbose=True,
+        limit_to_domains=None 
+    )
+
+    cl.user_session.set("api_chain", api_chain)
 
 @cl.on_message
 async def handle_message(message: cl.Message):
-    user_message = message.content
+    user_message = message.content #.lower()
     llm_chain = cl.user_session.get("llm_chain")
     api_chain = cl.user_session.get("api_chain")
-
-    if llm_chain is None or api_chain is None:
-        await cl.Message("Error: LLMChain or APIChain not initialized properly.").send()
-        return
-
-    booking_pattern = r'\b[A-Z]{6}\d{6}\b'
+    
+    booking_pattern = r'\b[A-Z]{6}\d{6}\b' 
     endpoint_url = "https://670dccd0073307b4ee447f2f.mockapi.io/daysoff/api/V1/booking"
 
-    try:
-        if re.search(booking_pattern, user_message):
-            bestillingskode = re.search(booking_pattern, user_message).group(0)
-            question = f"Retrieve information for booking ID {endpoint_url}?search={bestillingskode}"
-            response = await api_chain.acall(
-                {"bestillingskode": bestillingskode, "question": question},
-                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()
-    except Exception as e:
-        await cl.Message(f"Error during message handling: {e}").send()
+    if re.search(booking_pattern, user_message):  
+        bestillingskode = re.search(booking_pattern, user_message).group(0)  
+        question = f"Retrieve information for booking ID {endpoint_url}?search={bestillingskode}"
+   
+        response = await api_chain.acall(
+            {
+                "bestillingskode": bestillingskode,
+                "question": question
+              
+            },
+            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