Update app.py

app.py

@@ -2,16 +2,11 @@ import streamlit as st
 import os
 
 from groq import Groq
-from PyPDF2 import PdfReader
 from datetime import datetime
-from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain_community.embeddings import HuggingFaceEmbeddings 
-#from langchain.vectorstores import FAISS
-from langchain_community.vectorstores import FAISS
 from langchain_groq import ChatGroq
-#from langchain.chat_models import ChatOpenAI
-from langchain.chains.question_answering import load_qa_chain
 from langchain.chains import RetrievalQA
+from langchain_pinecone import PineconeVectorStore
 
 st.set_page_config('Opositor')
 st.header("Pregunta al trebep")
@@ -26,6 +21,7 @@ model_name = 'intfloat/multilingual-e5-small'
 embedding = HuggingFaceEmbeddings(model_name=model_name)
 
 # CARGAMOS EL VECTORSTORE DE PINECONE
+os.environ["PINECONE_API_KEY"] ='4bf0b4cf-4ced-4f70-8977-d60bb8ae405a'
 index_name = "boe-intfloat-multilingual-e5-base"
 namespace = "trebep"
 vectorstore = PineconeVectorStore(index_name=index_name, namespace=names, embedding=embedding)