Update app.py

app.py

@@ -24,6 +24,8 @@ import chainlit as cl
 
 #from tiktoken import encoding_for_model
 
+from pydantic import BaseModel, ConfigDict
+
 from langchain import hub
 from langchain_openai import OpenAI
 from langchain.chains import LLMChain, APIChain
@@ -33,15 +35,12 @@ from langchain.memory import ConversationTokenBufferMemory
 from langchain.memory import ConversationSummaryMemory
 
 from api_docs_mck import api_docs_str 
-from frequently_asked_questions import instruction_text, frequently_asked_questions
 from personvernspolicy import instruction_text_priv, personvernspolicy_data
 from frequently_asked_questions import instruction_text_faq, faq 
 
 
 OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
 
-
-
 # If you don't know the answer, just say that you don't know, don't try to make up an answer.
 daysoff_assistant_template = """
 You are a customer support assistant (’kundeservice AI assistent’) for Daysoff. 
@@ -136,21 +135,32 @@ def setup_multiple_chains():
     #conversation_memory = ConversationSummaryMemory(memory_key="chat_history",
                                                     #return_messages=True,
     #)
-                                                        
-    llm_chain = LLMChain(llm=llm,
-                         prompt=daysoff_assistant_prompt,
-                         memory=conversation_memory
-                        )
 
+
+class LLMChainConfig(BaseModel):
+    model_config = ConfigDict(extra='allow')  
+    instruction_text_faq: str 
+    faq: dict  
+    instruction_text_priv: str
+    personvernspolicy_data: dict
+
+    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)
 
     api_chain = APIChain.from_llm_and_api_docs(
         llm=llm,
         api_docs=api_docs_str,
-        instruction_text_faq=instruction_text_faq, 
-        faq=faq, 
-        instruction_text_priv=instruction_text_priv, 
-        personvernspolicy_data=personvernspolicy_data,
         api_url_prompt=api_url_prompt,
         api_response_prompt=api_response_prompt,
         verbose=True,