import streamlit as st
from generator import generate_response_from_document
from retrieval import retrieve_documents_hybrid
from evaluation import calculate_metrics
#from data_processing import load_data_from_faiss
import time

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

global retrieved_documents
retrieved_documents = []

global response 
response = ""

global time_taken_for_response
time_taken_for_response = 'N/A'

# @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"):
    start_time = time.time()
    retrieved_documents = retrieve_documents_hybrid(question, 10)  
    response = generate_response_from_document(question, retrieved_documents)
    end_time = time.time()
    time_taken_for_response = end_time-start_time
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, time_taken_for_response)
    else:
        metrics = ""

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