Text_RAG / app.py
sapatevaibhav
simplify document loading
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import streamlit as st
from utils.rag_chain import build_rag_chain
from dotenv import load_dotenv
import os
load_dotenv()
st.set_page_config(page_title="RAG Chatbot")
st.title("Ask about Shivaji Maharaj")
api_key = os.getenv("GOOGLE_API_KEY")
qa_chain = build_rag_chain(api_key)
query = st.text_input("Ask something about your documents")
if query:
answer, retrieved_docs = qa_chain(query)
st.markdown(f"**Answer:** {answer}")
with st.expander("Show supporting context"):
for doc in retrieved_docs:
st.write(doc)