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__import__('pysqlite3')
import sys
sys.modules['sqlite3'] = sys.modules.pop('pysqlite3')
from langchain.document_loaders import PyPDFLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.vectorstores import Chroma
from langchain.embeddings import OpenAIEmbeddings
from langchain.chat_models import ChatOpenAI
from langchain.chains import RetrievalQA
__import__('pysqlite3')
import sys
sys.modules['sqlite3'] = sys.modules.pop('pysqlite3')
from langchain.document_loaders import PyPDFLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.vectorstores import Chroma
from langchain.embeddings import OpenAIEmbeddings
from langchain.chat_models import ChatOpenAI
from langchain.chains import RetrievalQA
from dotenv import load_dotenv
load_dotenv()
from langchain.document_loaders import PyPDFLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.vectorstores import Chroma
from langchain.embeddings import OpenAIEmbeddings
from langchain.chat_models import ChatOpenAI
from langchain.retrievers.multi_query import MultiQueryRetriever
from langchain.chains import RetrievalQA
import streamlit as st
from dotenv import load_dotenv
load_dotenv()
from langchain.document_loaders import PyPDFLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.vectorstores import Chroma
from langchain.embeddings import OpenAIEmbeddings
from langchain.chat_models import ChatOpenAI
from langchain.retrievers.multi_query import MultiQueryRetriever
from langchain.chains import RetrievalQA
import streamlit as st
from dotenv import load_dotenv
load_dotenv()
from langchain.document_loaders import PyPDFLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.vectorstores import Chroma
from langchain.embeddings import OpenAIEmbeddings
from langchain.chat_models import ChatOpenAI
from langchain.retrievers.multi_query import MultiQueryRetriever
from langchain.chains import RetrievalQA
from dotenv import load_dotenv
load_dotenv()
from langchain.document_loaders import PyPDFLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
#Loader
loader = PyPDFLoader("unsu.pdf")
pages = loader.load_and_split()
#Split
import streamlit as st
from langchain.llms import CTransformers
llm = CTransformers(
model="llama-2-7b-chat.ggmlv3.q2_K.bin",
model_type="llama"
)
st.title('인공지능 시인')
from dotenv import load_dotenv
load_dotenv()
import streamlit as st
from langchain.chat_models import ChatOpenAI
chat_model = ChatOpenAI()
st.title('인공지능 시인')
content = st.text_input('시의 주제를 제시해주세요.')
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>운세보는 챗도지</title>
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.3.0/css/all.min.css"
integrity="sha512-SzlrxWUlpfuzQ+pcUCosxcglQRNAq/DZjVsC0lE40xsADsfeQoEypE+enwcOiGjk/bSuGGKHEyjSoQ1zVisanQ=="
crossorigin="anonymous" referrerpolicy="no-referrer" />
<style>
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>운세보는 챗도지</title>
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.3.0/css/all.min.css"
integrity="sha512-SzlrxWUlpfuzQ+pcUCosxcglQRNAq/DZjVsC0lE40xsADsfeQoEypE+enwcOiGjk/bSuGGKHEyjSoQ1zVisanQ=="
crossorigin="anonymous" referrerpolicy="no-referrer" />
<style>