import streamlit as st
from generator import generate_response_from_document
from retrieval import retrieve_documents
from evaluation import calculate_metrics
from data_processing import load_data_from_faiss, ragbench

# Page Title
st.title("RAG7 - Real World RAG System")

@st.cache_data
def load_data():
    load_data_from_faiss()

data_status = load_data()

# Question Section
st.subheader("Hi, What do you want to know today?")
question = st.text_area("Enter your question:", placeholder="Type your question here...", height=100)

# Submit Button
if st.button("Submit"):
    retrieved_documents = retrieve_documents(question, 5)  
    response = generate_response_from_document(question, retrieved_documents)
else:
    response = ""

# Response Section
st.subheader("Response")
st.text_area("Generated Response:", value=response, height=150, disabled=True)

# Metrics Section
st.subheader("Metrics")

col1, col2 = st.columns([1, 3])  # Creating two columns for button and metrics display

with col1:
    if st.button("Calculate Metrics"):
        metrics = calculate_metrics(question, response, retrieved_documents, ragbench)
    else:
        metrics = ""

with col2:
    st.text_area("Metrics:", value=metrics, height=100, disabled=True)