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import streamlit as st
import time
import streamlit.components.v1 as components
# FIRST: Set page config before ANY other Streamlit command
st.set_page_config(page_title="Spirituality Q&A", page_icon="🕉️")
# 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
# Add new session state for showing/hiding acknowledgment
if 'show_acknowledgment' not in st.session_state:
st.session_state.show_acknowledgment = False
# Add page change detection
if 'page_loaded' not in st.session_state:
st.session_state.page_loaded = True
# Reset query state when returning to home page
st.session_state.last_query = ""
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
# Function to toggle acknowledgment visibility
def toggle_acknowledgment():
st.session_state.show_acknowledgment = not st.session_state.show_acknowledgment
# Custom HTML/JS to navigate to sources page
def navigate_to_sources():
components.html(
"""
<script>
// Wait for the page to fully load
document.addEventListener('DOMContentLoaded', (event) => {
// This selects the nav item for the Sources page in the sidebar
const sourcesLink = Array.from(document.querySelectorAll('a.css-z5fcl4')).find(el => el.innerText === 'Sources');
if (sourcesLink) {
sourcesLink.click();
}
});
</script>
""",
height=0,
)
# Custom styling (pure CSS)
st.markdown("""
<style>
/* 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;
}
/* Special styling for thank you button */
.thank-you-button > button {
background-color: #f8e6ff !important;
border-radius: 8px !important;
padding: 10px 20px !important;
font-weight: normal !important;
box-shadow: 0 2px 4px rgba(0,0,0,0.1) !important;
transition: all 0.3s ease !important;
border: 1px solid #d8b9ff !important;
color: #6a1b9a !important;
}
.thank-you-button > button:hover {
background-color: #f0d6ff !important;
transform: translateY(-1px) !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;
}
/* Acknowledgment section styling - fully fixed */
.acknowledgment-container {
background-color: #f8f5ff;
border: 1px solid #e0d6fe;
border-radius: 8px;
padding: 15px;
margin: 20px 0;
box-shadow: 0 2px 5px rgba(0,0,0,0.05);
}
.acknowledgment-header {
color: #6a1b9a;
font-size: 1.3rem;
margin-bottom: 10px;
text-align: center;
}
.more-info-link {
text-align: center;
margin-top: 10px;
font-style: italic;
}
.citation-note {
font-size: 0.8rem;
font-style: italic;
color: #666;
padding: 10px;
border-top: 1px solid #eee;
margin-top: 30px;
}
/* Center align title */
.main-title {
font-size: 2.5rem;
color: #c0392b;
text-align: center;
margin-bottom: 1rem;
}
/* Button container for centering */
.center-container {
display: flex;
justify-content: center;
margin: 0 auto;
width: 100%;
}
/* Source link styling */
.source-link {
color: #3f51b5;
font-weight: bold;
text-decoration: underline;
cursor: pointer;
}
.source-link:hover {
color: #6a1b9a;
}
</style>
<div class="main-title">Spirituality Q&A</div>
""", unsafe_allow_html=True)
# Centered button layout without columns
_, center_col, _ = st.columns([1, 2, 1])
with center_col:
if st.session_state.show_acknowledgment:
st.markdown('<div class="thank-you-button">', unsafe_allow_html=True)
if st.button("Hide Thank You Note", on_click=toggle_acknowledgment, disabled=st.session_state.is_processing, use_container_width=True):
pass
st.markdown('</div>', unsafe_allow_html=True)
else:
st.markdown('<div class="thank-you-button">', unsafe_allow_html=True)
if st.button("Show Thank You Note", on_click=toggle_acknowledgment, disabled=st.session_state.is_processing, use_container_width=True):
pass
st.markdown('</div>', unsafe_allow_html=True)
# 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_all_auth()
load_model() # 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
if st.session_state.show_acknowledgment:
st.markdown('<div class="acknowledgment-container">', unsafe_allow_html=True)
st.markdown('<div class="acknowledgment-header">A Heartfelt Thank You</div>', unsafe_allow_html=True)
st.markdown("""
It is believed that one cannot be in a spiritual path without the will of the Lord. One need not be a believer or a non-believer, merely proceeding to thoughtlessness and observation is enough to evolve and shape perspectives. But that happens through grace. It is believed that without the will of the Lord, one cannot be blessed by real saints, and without the will of the saints, one cannot get close to them or God.
Therefore, with deepest reverence, we express our gratitude to:
**The Saints, Sages, Siddhas, Yogis, and Spiritual Masters** whose timeless wisdom illuminates this application. From ancient sages to modern masters, their selfless dedication to uplift humanity through selfless love and spiritual knowledge continues to guide seekers on the path.
**The Sacred Texts** that have preserved the eternal truths across millennia, offering light in times of darkness and clarity in times of confusion.
**The Publishers** who have diligently preserved and disseminated these precious teachings, making them accessible to spiritual aspirants worldwide. Their work ensures these wisdom traditions endure for future generations.
**The Authors** who have dedicated their lives to interpreting and explaining complex spiritual concepts, making them accessible to modern readers.
This application is merely a humble vessel for the ocean of wisdom they have shared with the world. We claim no ownership of these teachings - only profound gratitude for the opportunity to help make them more accessible.
""")
st.markdown('<div class="more-info-link">', unsafe_allow_html=True)
st.write("For detailed information about our sources, please visit the *Sources* page in the navigation menu.")
st.markdown('</div>', unsafe_allow_html=True)
st.markdown('</div>', unsafe_allow_html=True)
# Function to handle query selection from the common questions buttons
def set_query(query):
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
# No explicit rerun here; widget interaction already triggers a re-run
# 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:
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
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?"
]
st.markdown("### Few questions to try:")
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 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
st.session_state.form_key += 1
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)
if st.session_state.last_query:
st.markdown("### Current Question:")
st.info(st.session_state.last_query)
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)
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
except Exception as e:
st.session_state.last_answer = {"answer_with_rag": f"Error processing query: {str(e)}", "citations": ""}
st.session_state.is_processing = False # Reset processing flag
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)
st.markdown("---")
st.markdown("""
### About this app
This application uses a Retrieval-Augmented Generation (RAG) system to answer questions about spirituality based on insights from Indian spiritual texts. It searches through a database of texts to find relevant passages and generates answers based on those passages.
**Important to note:**
- This is not a general chatbot. It is specifically designed to answer spiritual questions based on referenced texts, not to generate historical information or reproduce stories of saints or spiritual leaders.
- You may receive slightly different answers when asking the same question multiple times. This variation is intentional and reflects the nuanced nature of spiritual teachings across different traditions.
- While you can select a specific number of citations and word limit, the actual response may contain fewer citations based on relevance and availability of information. Similarly, explanations may be shorter than the selected word limit if the retrieved information is concise.
- We apologize for any inconsistencies or misinterpretations that may occur. This application is educational in nature and continuously improving.
We value your feedback to enhance this application. Please visit the *Contacts* page to share your suggestions or report any issues.
For more information about the source texts used, see *Sources* in the navigation menu.
""")
st.markdown('<div class="citation-note">', unsafe_allow_html=True)
st.markdown("""
The answers presented in this application are re-presented summaries of relevant passages from the listed citations.
For the original works in their complete and authentic form, users are respectfully encouraged to purchase
the original print or digital works from their respective publishers. Your purchase helps support these publishers
who have brought the world closer to such important spiritual works.
""")
st.markdown('</div>', unsafe_allow_html=True) |