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import streamlit as st
import os
from PyPDF2 import PdfReader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.embeddings import HuggingFaceHubEmbeddings # Cambiado desde HuggingFaceEmbeddings
from langchain.vectorstores import FAISS
from langchain.chat_models import ChatOpenAI
from langchain.chains.question_answering import load_qa_chain
st.set_page_config(page_title='preguntaDOC')
st.header("Pregunta a tu PDF")
OPENAI_API_KEY = st.text_input('OpenAI API Key', type='password')
HUGGINGFACE_API_KEY = st.text_input('Hugging Face API Key', type='password') # Añadido para la API de Hugging Face
pdf_obj = st.file_uploader("Carga tu documento", type="pdf", on_change=st.cache_resource.clear)
@st.cache_resource
def create_embeddings(pdf, hf_api_key):
os.environ["HUGGINGFACEHUB_API_TOKEN"] = hf_api_key # Configurar token de HF
pdf_reader = PdfReader(pdf)
text = ""
for page in pdf_reader.pages:
text += page.extract_text()
text_splitter = RecursiveCharacterTextSplitter(
chunk_size=800,
chunk_overlap=100,
length_function=len
)
chunks = text_splitter.split_text(text)
# Usar HuggingFaceHubEmbeddings en lugar de HuggingFaceEmbeddings
embeddings = HuggingFaceHubEmbeddings(
repo_id="sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",
huggingfacehub_api_token=hf_api_key
)
knowledge_base = FAISS.from_texts(chunks, embeddings)
return knowledge_base
if pdf_obj and HUGGINGFACE_API_KEY:
knowledge_base = create_embeddings(pdf_obj, HUGGINGFACE_API_KEY)
user_question = st.text_input("Haz una pregunta sobre tu PDF:")
if user_question and OPENAI_API_KEY:
os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
docs = knowledge_base.similarity_search(user_question, 3)
llm = ChatOpenAI(model_name='gpt-3.5-turbo')
chain = load_qa_chain(llm, chain_type="stuff")
with st.spinner("Procesando tu pregunta..."):
try:
respuesta = chain.run(input_documents=docs, question=user_question)
st.write(respuesta)
except Exception as e:
st.error(f"Error: {str(e)}")
elif pdf_obj and not HUGGINGFACE_API_KEY:
st.warning("Por favor, introduce una clave API de Hugging Face para procesar el documento.") |