Create app.py
Browse files
app.py
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import streamlit as st
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import os
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from groq import Groq
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from PyPDF2 import PdfReader
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from datetime import datetime
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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from langchain_community.embeddings import HuggingFaceEmbeddings
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#from langchain.vectorstores import FAISS
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from langchain_community.vectorstores import FAISS
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from langchain_groq import ChatGroq
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#from langchain.chat_models import ChatOpenAI
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from langchain.chains.question_answering import load_qa_chain
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from langchain.chains import RetrievalQA
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st.set_page_config('Opositor')
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st.header("Pregunta al trebep")
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# CARGAMOS LLM
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os.environ["GROQ_API_KEY"] = "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"
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model = 'llama3-8b-8192'
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llm = ChatGroq(model = model)
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# CARGAMOS MODELO DE EMBEDDING
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model_name = 'intfloat/multilingual-e5-small'
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embedding = HuggingFaceEmbeddings(model_name=model_name)
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# CARGAMOS EL VECTORSTORE DE PINECONE
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index_name = "boe-intfloat-multilingual-e5-base"
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namespace = "trebep"
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vectorstore = PineconeVectorStore(index_name=index_name, namespace=names, embedding=embedding)
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# CREAMOS EL RETRIEVAL
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qa = RetrievalQA.from_chain_type(
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llm=llm,
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chain_type="stuff",
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retriever=vectorstore.as_retriever(),
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#return_source_documents=True,
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#verbose=True
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)
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# Función para mostrar logs
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def mostrar_logs(logs,hints):
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# Crear un contenedor desplegable
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with st.expander("Chunks"):
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for hint in hints:
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st.write(hint.page_content)
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st.write("-" * 30)
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st.sidebar.header("Registro de preguntas")
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for entry in logs:
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st.sidebar.write(f"**Pregunta: {entry['Pregunta']}**")
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st.sidebar.write(f"Respuesta: {entry['Respuesta']}")
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# Lista para almacenar preguntas y respuestas
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logs = []
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if pdf_obj:
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user_question = st.text_input("¡A jugar! Haz una pregunta sobre tu PDF:")
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if user_question:
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# Obtenemos la respuesta
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respuesta = qa.invoke(user_question)
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# Mostrar la variable en color verde
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st.subheader("Respuesta")
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st.write(f":green[{str(respuesta)}]")
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# Guardar pregunta y respuesta en los logs
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logs.append({"Pregunta": user_question, "Respuesta": respuesta})
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# Mostrar logs actualizados
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mostrar_logs(logs,docs)
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