app.py

import streamlit as st
import time

# FIRST: Set page config before ANY other Streamlit command
st.set_page_config(page_title="Spirituality Q&A")

# Initialize ALL session state variables right at the beginning
if 'initialized' not in st.session_state:
    st.session_state.initialized = False
if 'model' not in st.session_state:
    st.session_state.model = None
if 'tokenizer' not in st.session_state:
    st.session_state.tokenizer = None
if 'last_query' not in st.session_state:
    st.session_state.last_query = ""
if 'submit_clicked' not in st.session_state:
    st.session_state.submit_clicked = False
if 'init_time' not in st.session_state:
    st.session_state.init_time = None
if 'form_key' not in st.session_state:
    st.session_state.form_key = 0  # This will help us reset the form
# New variable for debouncing: whether processing is in progress
if 'is_processing' not in st.session_state:
    st.session_state.is_processing = False
# Store the answer so that it persists on screen
if 'last_answer' not in st.session_state:
    st.session_state.last_answer = None

# THEN: Import your modules
from rag_engine import process_query, load_model, cached_load_data_files
from utils import setup_all_auth

# Preload resources during initialization
init_message = st.empty()
if not st.session_state.initialized:
    init_message.info("Hang in there! We are setting the system up for you. 😊")
    try:
        # Setup authentication and preload heavy resources
        setup_all_auth()
        load_model()  # This uses cached_load_model via alias
        cached_load_data_files()  # Preload FAISS index, text chunks, and metadata
        st.session_state.initialized = True
        st.session_state.init_time = time.time()
        init_message.success("System initialized successfully!")
        time.sleep(2)
        init_message.empty()
    except Exception as e:
        init_message.error(f"Error initializing: {str(e)}")
elif st.session_state.init_time is not None:
    elapsed_time = time.time() - st.session_state.init_time
    if elapsed_time >= 2.0:
        init_message.empty()
        st.session_state.init_time = None

# Custom styling (pure CSS)
st.markdown("""
<style>
.main-title {
    font-size: 2.5rem;
    color: #c0392b;
    text-align: center;
    margin-bottom: 1rem;
}
/* Button styling */
.stButton>button {
    background-color: #fff0f0 !important;
    color: #3f51b5 !important;
    border: 1px solid #e1e4f2 !important;
    border-radius: 20px !important;
    padding: 8px 16px !important;
    box-shadow: 0 1px 2px rgba(0,0,0,0.03) !important;
    white-space: nowrap !important;
    overflow: hidden !important;
    text-overflow: ellipsis !important;
}
/* Form submit button specific styling */
button[type="submit"], 
.stFormSubmit>button, 
[data-testid="stFormSubmitButton"]>button {
    background-color: #fff0f0 !important;
    color: #3f51b5 !important;
    border: 1px solid #e1e4f2 !important;
    border-radius: 8px !important;
}
.stButton>button:hover {
    background-color: #fafbff !important;
    border-color: #c5cae9 !important;
}
/* Input field styling */
div[data-baseweb="input"] {
    border: 1px solid #fff0f0 !important;
    border-radius: 8px !important;
    background-color: #ffffff !important;
}
div[data-baseweb="input"]:focus-within {
    border: 1px solid #3f51b5 !important;
}
div[data-baseweb="input"]:active {
    border: 1px solid #fff0f0 !important;
}
/* Style the st.info boxes */
div.stInfo {
    background-color: #f8faff !important;
    color: #3f51b5 !important;
    border: 1px solid #e1e4f2 !important;
    border-radius: 8px !important;
}
/* COMBINED SCROLL CONTAINER */
.questions-scroll-container {
    width: 100%;
    overflow-x: auto;
    scrollbar-width: none; /* Firefox */
    -ms-overflow-style: none; /* IE and Edge */
}
/* Hide scrollbar for Chrome, Safari and Opera */
.questions-scroll-container::-webkit-scrollbar {
    display: none;
}
/* Inner content that holds both rows */
.questions-content {
    display: inline-flex;
    flex-direction: column;
    min-width: max-content;
    gap: 10px;
    padding: 5px 0;
}
/* Individual rows */
.questions-row {
    display: flex;
    flex-direction: row;
    gap: 10px;
}
/* Placeholder for buttons */
.button-placeholder {
    min-height: 38px;
    min-width: 120px;
    margin: 0 5px;
}
</style>
<div class="main-title">Spirituality Q&A</div>
""", unsafe_allow_html=True)

# Function to handle query selection from the common questions buttons
def set_query(query):
    # If already processing, ignore further input
    if st.session_state.is_processing:
        return
    st.session_state.last_query = query
    st.session_state.submit_clicked = True
    st.session_state.is_processing = True
    st.experimental_rerun()

# Function to group questions into rows based on length
def group_buttons(questions, max_chars_per_row=100):
    rows = []
    current_row = []
    current_length = 0
    for q in questions:
        # Add some buffer for button padding/margins
        q_length = len(q) + 5
        if current_length + q_length > max_chars_per_row and current_row:
            rows.append(current_row)
            current_row = [q]
            current_length = q_length
        else:
            current_row.append(q)
            current_length += q_length
    if current_row:
        rows.append(current_row)
    return rows

# All common questions in a single list
common_questions = [
    "What is the Atman or the soul?",
    "Are there rebirths?",
    "What is Karma?",
    "What is the ultimate truth?",
    "What is Swami Vivekananda's opinion about the SELF?",
    "Explain moksha or salvation. Is that for real?",
    "Destiny or free will?",
    "What is the ultimate goal of human life?",
    "Do we really die?",
    "How can you attain self-realization?"
]

# Display heading for common questions
st.markdown("### Common questions to try:")

# Group questions into rows and create buttons (disabled if processing)
question_rows = group_buttons(common_questions, max_chars_per_row=80)
for row_idx, row in enumerate(question_rows):
    cols = st.columns(len(row))
    for i, (col, q) in enumerate(zip(cols, row)):
        with col:
            if st.button(q, key=f"r{row_idx}_q{i}", use_container_width=True, disabled=st.session_state.is_processing):
                set_query(q)

# Function to handle form submission
def handle_form_submit():
    # If already processing, ignore further input
    if st.session_state.is_processing:
        return
    if st.session_state.query_input and st.session_state.query_input.strip():
        st.session_state.last_query = st.session_state.query_input.strip()
        st.session_state.submit_clicked = True
        st.session_state.is_processing = True
        # Increment the form key to force a reset
        st.session_state.form_key += 1

# Create a form with a dynamic key (to allow resetting)
with st.form(key=f"query_form_{st.session_state.form_key}"):
    query = st.text_input("Ask your question:", key="query_input", 
                          placeholder="Press enter to submit your question", disabled=st.session_state.is_processing)
    submit_button = st.form_submit_button("Get Answer", on_click=handle_form_submit, disabled=st.session_state.is_processing)

# Display the current question if available
if st.session_state.last_query:
    st.markdown("### Current Question:")
    st.info(st.session_state.last_query)

# Sliders for customization
col1, col2 = st.columns(2)
with col1:
    top_k = st.slider("Number of sources:", 3, 10, 5)
with col2:
    word_limit = st.slider("Word limit:", 50, 500, 200)

# Process the query only if it has been explicitly submitted
if st.session_state.submit_clicked and st.session_state.last_query:
    st.session_state.submit_clicked = False
    with st.spinner("Processing your question..."):
        try:
            result = process_query(st.session_state.last_query, top_k=top_k, word_limit=word_limit)
            st.session_state.last_answer = result  # Store result in session state
        except Exception as e:
            st.session_state.last_answer = {"answer_with_rag": f"Error processing query: {str(e)}", "citations": ""}
    # Reset debouncing after processing and force a rerun to re-enable buttons
    st.session_state.is_processing = False
    st.experimental_rerun()

# Display the answer if available
if st.session_state.last_answer is not None:
    st.subheader("Answer:")
    st.write(st.session_state.last_answer["answer_with_rag"])
    st.subheader("Sources:")
    for citation in st.session_state.last_answer["citations"].split("\n"):
        st.write(citation)

# Add helpful information
st.markdown("---")
st.markdown("""
### About this app
This application uses a Retrieval-Augmented Generation (RAG) system to answer questions about Indian spiritual texts.
It searches through a database of texts to find relevant passages and generates answers based on those passages.
""")