Update app.py

app.py

@@ -3,6 +3,7 @@
 
 import asyncio
 import os
+import re
 import time
 import json
 import torch
@@ -10,8 +11,6 @@ import torch
 from api_docs_mck import daysoff_api_docs
 
 import chainlit as cl
-#from chainlit import LLMSettings # hmm..
-#from chainlit.config import config # hmm...
 
 from langchain import hub
 from langchain.chains import LLMChain, APIChain
@@ -19,16 +18,6 @@ from langchain_core.prompts import PromptTemplate
 from langchain_community.llms import HuggingFaceHub
 from langchain.memory.buffer import ConversationBufferMemory
 
-
-HUGGINGFACEHUB_API_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN")
-LANGCHAIN_API_KEY = os.environ.get("LANGCHAIN_API_KEY")
-HF_TOKEN = os.environ.get("HF_TOKEN")
-
-#os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:true"
-
-dtype = torch.float16
-device = torch.device("cuda")
-
 daysoff_assistant_booking_template = """
 You are a customer support assistant for Daysoff.no. Your expertise is
 retrieving booking information for a given booking ID."
@@ -69,15 +58,10 @@ api_response_prompt = PromptTemplate(input_variables=['api_docs_mck',
                                                       'api_response'],
                                      template=api_response_template)
 
-
-# --model, memory object, and llm_chain
 @cl.on_chat_start
 def setup_multiple_chains():
-    llm = HuggingFaceHub(repo_id="google/gemma-2-2b-it") #,
-                         #temperature=0.7,
-                         #huggingface_api_token=HUGGINGFACEHUB_API_TOKEN,
-                         #device=device)
-
+    llm = HuggingFaceHub(repo_id="google/gemma-2-2b-it") 
+                    
     conversation_memory = ConversationBufferMemory(memory_key="chat_history",
                                                    max_len=200,
                                                    return_messages=True,
@@ -99,11 +83,8 @@ def setup_multiple_chains():
 
     cl.user_session.set("api_chain", api_chain)
 
+BOOKING_ID = r'\b[A-Z]{6}\d{6}\b' 
 
-# --regex for alphanum. "LLLLLLxxxxxx", i.e. booking_id  |==> 308.9 trillion unique possibilities
-BOOKING_ID = r'\b[A-Z]{6}\d{6}\b'
-
-# --keywords based from email-data
 BOOKING_KEYWORDS = [
     "booking",
     "bestillingsnummer",
@@ -122,7 +103,6 @@ BOOKING_KEYWORDS = [
     "identyfikacyjny płatności"  
 ]
 
-# --wrapper function around the @cl.on_message decorator; chain trigger(s)
 @cl.on_message
 async def handle_message(message: cl.Message):
     user_message = message.content.lower()