Added redis streams listener fix

app.py

@@ -17,55 +17,6 @@ from langchain_core.runnables.history import RunnableWithMessageHistory
 from langchain_core.chat_history import BaseChatMessageHistory
 from langchain.chains import RetrievalQA
 import nest_asyncio
-import pymongo
-import logging
-from langchain.docstore.document import Document
-import redis
-import threading
-
-# config
-nest_asyncio.apply()
-logging.basicConfig(level=logging.INFO)
-database = "AlertSimAndRemediation"
-collection = "alert_embed"
-index_name = "alert_index"
-stream_name = "alerts"
-redis_port = 16652
-
-# embedding model
-embedding_args = {
-    "model_name" : "BAAI/bge-large-en-v1.5",
-    "model_kwargs" : {"device": "cpu"},
-    "encode_kwargs" : {"normalize_embeddings": True}
-}
-embedding_model = HuggingFaceEmbeddings(**embedding_args)
-
-# Mongo Connection
-connection = pymongo.MongoClient(os.environ["MONGO_URI"])
-alert_collection = connection[database][collection]
-
-# redis connection
-r = redis.Redis(host=os.environ['REDIS_HOST'], password=os.environ['REDIS_PWD'], port=port)
-
-Sure, here's the entire code with the Streamlit app and the Redis stream listener combined:
-pythonCopy codeimport streamlit as st
-import os
-from collections.abc import Collection
-from langchain.memory import ChatMessageHistory
-from langchain_community.chat_message_histories import (
-    StreamlitChatMessageHistory,
-)
-from langchain_groq import ChatGroq
-from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
-from langchain_community.vectorstores import MongoDBAtlasVectorSearch
-from langchain_community.embeddings import HuggingFaceEmbeddings
-from langchain.chains import create_history_aware_retriever, create_retrieval_chain
-from langchain.chains.combine_documents import create_stuff_documents_chain
-from langchain.output_parsers import ResponseSchema, StructuredOutputParser
-from langchain_core.runnables.history import RunnableWithMessageHistory
-from langchain_core.chat_history import BaseChatMessageHistory
-from langchain.chains import RetrievalQA
-import nest_asyncio
 nest_asyncio.apply()
 
 import pymongo