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import streamlit as st
from transformers import pipeline
from nltk.tokenize import sent_tokenize
import base64
import torch
import nltk
import os
import tempfile
@st.cache_resource
def init_nltk():
# β
Use a writable temp directory, not /app
nltk_data_dir = os.path.join(tempfile.gettempdir(), "nltk_data")
os.makedirs(nltk_data_dir, exist_ok=True)
# β
Register this directory for nltk
if nltk_data_dir not in nltk.data.path:
nltk.data.path.insert(0, nltk_data_dir)
# β
Download only required packages
for pkg in ["punkt"]:
try:
nltk.data.find(f"tokenizers/{pkg}")
except LookupError:
nltk.download(pkg, download_dir=nltk_data_dir, quiet=True)
return True
# β
Run it once at startup
init_nltk()
# Device detection
DEVICE = 0 if torch.cuda.is_available() else -1
# Lazy model loading
def get_summarizer():
if 'summarizer' not in st.session_state:
with st.spinner("π§ Loading AI Brain..."):
st.session_state.summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", device=DEVICE)
return st.session_state.summarizer
def get_qa():
if 'qa' not in st.session_state:
with st.spinner("π§ Loading AI Brain..."):
st.session_state.qa = pipeline("question-answering", model="distilbert-base-uncased-distilled-squad", device=DEVICE)
return st.session_state.qa
def get_classifier():
if 'classifier' not in st.session_state:
with st.spinner("π§ Loading AI Brain..."):
st.session_state.classifier = pipeline("zero-shot-classification", model="typeform/distilbert-base-uncased-mnli", device=DEVICE)
return st.session_state.classifier
@st.cache_resource
def load_translator(model_name):
return pipeline("translation", model=model_name, device=DEVICE)
def truncate_text(text, max_words=400):
words = text.split()
return (" ".join(words[:max_words]), len(words) > max_words)
# ULTRA PREMIUM CSS - Glassmorphism + Animations - FIXED HEADER
st.markdown("""
<style>
@import url('https://fonts.googleapis.com/css2?family=Poppins:wght@300;400;600;700;900&display=swap');
* {
font-family: 'Poppins', sans-serif;
}
.stApp {
background: linear-gradient(135deg, #667eea 0%, #764ba2 25%, #f093fb 50%, #4facfe 75%, #00f2fe 100%);
background-size: 400% 400%;
animation: gradientShift 15s ease infinite;
}
@keyframes gradientShift {
0% { background-position: 0% 50%; }
50% { background-position: 100% 50%; }
100% { background-position: 0% 50%; }
}
/* NEW HEADER - Simple and Visible */
.hero-header {
background: linear-gradient(135deg, #1e1e3f 0%, #2d2d5f 100%);
padding: 3rem 2rem;
border-radius: 25px;
margin-bottom: 2rem;
text-align: center;
box-shadow: 0 20px 60px rgba(0, 0, 0, 0.5);
border: 2px solid #667eea;
}
.hero-title {
font-size: 3.5rem;
font-weight: 900;
color: #ffffff;
margin: 0 0 1rem 0;
text-shadow: 2px 2px 8px rgba(0, 0, 0, 0.5);
}
.hero-subtitle {
font-size: 1.3rem;
color: #ffffff;
margin: 0;
font-weight: 400;
opacity: 0.95;
}
/* Premium Tabs */
.stTabs [data-baseweb="tab-list"] {
gap: 12px;
background: rgba(255, 255, 255, 0.1);
padding: 12px;
border-radius: 20px;
backdrop-filter: blur(10px);
border: 1px solid rgba(255, 255, 255, 0.2);
}
.stTabs [data-baseweb="tab"] {
background: rgba(255, 255, 255, 0.15);
border-radius: 15px;
color: white;
font-weight: 600;
font-size: 1.1rem;
padding: 12px 24px;
border: 1px solid rgba(255, 255, 255, 0.25);
transition: all 0.3s ease;
text-shadow: 0 2px 4px rgba(0, 0, 0, 0.2);
}
.stTabs [data-baseweb="tab"]:hover {
background: rgba(255, 255, 255, 0.25);
transform: translateY(-2px);
box-shadow: 0 4px 12px rgba(0, 0, 0, 0.2);
}
.stTabs [aria-selected="true"] {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
border-color: rgba(255, 255, 255, 0.4);
box-shadow: 0 8px 24px rgba(102, 126, 234, 0.4);
}
/* Premium Buttons */
.stButton > button {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
color: white;
font-weight: 700;
font-size: 1.1rem;
padding: 16px 40px;
border-radius: 16px;
border: none;
box-shadow: 0 8px 24px rgba(102, 126, 234, 0.4);
transition: all 0.3s ease;
width: 100%;
text-shadow: 0 2px 4px rgba(0, 0, 0, 0.2);
}
.stButton > button:hover {
transform: translateY(-3px);
box-shadow: 0 12px 36px rgba(102, 126, 234, 0.6);
background: linear-gradient(135deg, #764ba2 0%, #667eea 100%);
}
/* Input Fields */
.stTextArea textarea, .stTextInput input {
background: rgba(255, 255, 255, 0.2) !important;
backdrop-filter: blur(10px);
border: 2px solid rgba(255, 255, 255, 0.3) !important;
border-radius: 16px !important;
color: white !important;
font-size: 1rem !important;
padding: 16px !important;
text-shadow: 0 1px 2px rgba(0, 0, 0, 0.2);
}
.stTextArea textarea::placeholder, .stTextInput input::placeholder {
color: rgba(255, 255, 255, 0.7) !important;
}
.stTextArea textarea:focus, .stTextInput input:focus {
border-color: rgba(255, 255, 255, 0.6) !important;
box-shadow: 0 0 20px rgba(255, 255, 255, 0.3) !important;
background: rgba(255, 255, 255, 0.25) !important;
}
/* Result Cards */
.result-card {
background: rgba(255, 255, 255, 0.95);
color: #1a1a1a;
padding: 2rem;
border-radius: 20px;
margin: 1rem 0;
box-shadow: 0 8px 32px rgba(0, 0, 0, 0.2);
animation: fadeIn 0.5s ease;
border-left: 5px solid #667eea;
}
.result-card p {
word-break: break-word;
overflow-wrap: break-word;
max-height: 300px;
overflow-y: auto;
}
@keyframes fadeIn {
from { opacity: 0; transform: translateY(20px); }
to { opacity: 1; transform: translateY(0); }
}
/* Stats Badge */
.stats-badge {
display: inline-block;
background: rgba(255, 255, 255, 0.25);
backdrop-filter: blur(10px);
padding: 8px 20px;
border-radius: 20px;
color: white;
font-weight: 600;
border: 1px solid rgba(255, 255, 255, 0.3);
margin: 5px;
text-shadow: 0 1px 3px rgba(0, 0, 0, 0.3);
}
/* Success/Error Messages */
.stSuccess {
background: rgba(72, 187, 120, 0.25) !important;
backdrop-filter: blur(10px);
border-left: 4px solid #48bb78 !important;
border-radius: 12px !important;
color: white !important;
}
.stError {
background: rgba(245, 101, 101, 0.25) !important;
backdrop-filter: blur(10px);
border-left: 4px solid #f56565 !important;
border-radius: 12px !important;
color: white !important;
}
.stInfo {
background: rgba(66, 153, 225, 0.25) !important;
backdrop-filter: blur(10px);
border-left: 4px solid #4299e1 !important;
border-radius: 12px !important;
color: white !important;
}
/* Sidebar */
.css-1d391kg, [data-testid="stSidebar"] {
background: rgba(20, 20, 40, 0.9);
backdrop-filter: blur(20px);
border-right: 1px solid rgba(255, 255, 255, 0.2);
}
/* Ensure text wraps properly */
.stTabs h3 {
word-break: break-word;
overflow-wrap: anywhere;
white-space: normal;
max-width: 100%;
margin: 0;
padding: 0.5rem 0;
color: white;
text-shadow: 0 2px 4px rgba(0, 0, 0, 0.3);
}
.css-1d391kg h2, [data-testid="stSidebar"] h2 {
color: white;
font-weight: 700;
text-shadow: 0 2px 4px rgba(0, 0, 0, 0.3);
}
.css-1d391kg p, [data-testid="stSidebar"] p {
color: rgba(255, 255, 255, 0.9);
}
/* Spinner */
.stSpinner > div {
border-top-color: white !important;
}
/* Selectbox */
.stSelectbox > div > div {
background: rgba(255, 255, 255, 0.2) !important;
backdrop-filter: blur(10px);
border-radius: 12px !important;
color: white !important;
border: 2px solid rgba(255, 255, 255, 0.3) !important;
}
.stSelectbox label {
color: white !important;
font-weight: 600 !important;
text-shadow: 0 1px 3px rgba(0, 0, 0, 0.3);
}
/* Footer */
.premium-footer {
text-align: center;
padding: 2rem;
margin-top: 3rem;
background: rgba(20, 20, 40, 0.85);
backdrop-filter: blur(15px);
border-radius: 20px;
border: 2px solid rgba(255, 255, 255, 0.3);
box-shadow: 0 8px 32px rgba(0, 0, 0, 0.3);
}
.premium-footer p {
color: rgba(255, 255, 255, 0.9);
margin: 0.5rem 0;
text-shadow: 0 1px 3px rgba(0, 0, 0, 0.3);
}
/* Hide Streamlit Branding */
#MainMenu {visibility: hidden;}
footer {visibility: hidden;}
header {visibility: hidden;}
/* Custom scrollbar */
::-webkit-scrollbar {
width: 10px;
}
::-webkit-scrollbar-track {
background: rgba(255, 255, 255, 0.1);
}
::-webkit-scrollbar-thumb {
background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
border-radius: 5px;
}
::-webkit-scrollbar-thumb:hover {
background: linear-gradient(135deg, #764ba2 0%, #667eea 100%);
}
</style>
""", unsafe_allow_html=True)
# New Simple Header
st.markdown("""
<div class="hero-header">
<div class="hero-title">π§ AI Study Helper Pro</div>
<div class="hero-subtitle">β‘ Supercharge Your Learning with Advanced AI Technology</div>
</div>
""", unsafe_allow_html=True)
# Sidebar
with st.sidebar:
st.markdown("### π― Dashboard")
st.markdown("---")
# Stats
col1, col2 = st.columns(2)
with col1:
st.markdown('<div class="stats-badge">π 247 Processed</div>', unsafe_allow_html=True)
with col2:
st.markdown('<div class="stats-badge">β‘ 2.3s Avg</div>', unsafe_allow_html=True)
st.markdown("---")
st.markdown("### β¨ Features")
features = [
"π AI Summarization",
"π¬ Smart Q&A",
"π― Quiz Generator",
"π Multi-Language",
"π Keyword Extraction",
"π¨ Lightning Fast"
]
for feat in features:
st.markdown(f"**{feat}**")
st.markdown("---")
st.markdown("### π©βπ» Developer")
st.markdown("**Umaima Qureshi**")
st.markdown("[GitHub](https://github.com/Umaima122)")
# Session state
for key in ["summary", "quiz", "translation", "keywords"]:
if key not in st.session_state:
st.session_state[key] = "" if key not in ["quiz", "keywords"] else []
# Tabs
tab1, tab2, tab3, tab4, tab5, tab6 = st.tabs([
"π Summarize", "π¬ Q&A", "π― Quiz", "π Translate", "π Keywords", "π₯ Download"
])
# SUMMARIZE TAB
with tab1:
st.markdown("### π Intelligent Summarization")
text = st.text_area("βοΈ Your notes or textbook:", value="", height=250, key="sum_txt",
placeholder="Paste your content here and watch AI magic happen...")
col1, col2, col3 = st.columns([1, 1, 1])
with col2:
if st.button("β¨ Generate Summary", key="sum_btn"):
if not text.strip():
st.error("β οΈ Please provide text to summarize")
else:
trunc, was_trunc = truncate_text(text, 400)
if was_trunc:
st.info("π Text optimized to 400 words")
if len(trunc.split()) < 20:
st.error("β οΈ Need at least 20 words")
else:
with st.spinner("π§ AI is thinking..."):
try:
summarizer = get_summarizer()
result = summarizer(trunc, max_length=130, min_length=30, do_sample=False, truncation=True)
summary = result[0]['summary_text']
st.markdown(f"""
<div class="result-card">
<h4 style="color: #667eea; margin-bottom: 1rem;">π AI-Generated Summary</h4>
<p style="font-size: 1.1rem; line-height: 1.8; color: #2d3748;">{summary}</p>
<div style="margin-top: 1rem; padding-top: 1rem; border-top: 1px solid #e2e8f0;">
<span class="stats-badge" style="background: #667eea; color: white;">
{len(summary.split())} words
</span>
<span class="stats-badge" style="background: #48bb78; color: white;">
β Completed
</span>
</div>
</div>
""", unsafe_allow_html=True)
st.session_state["summary"] = summary
except Exception as e:
st.error(f"β Error: {str(e)}")
# Q&A TAB
with tab2:
st.markdown("### π¬ Intelligent Q&A System")
context = st.text_area("π Context (Your notes):", value="", height=200, key="qa_ctx",
placeholder="Paste your study material here...")
question = st.text_input("β Ask your question:", key="qa_q",
placeholder="What would you like to know?")
col1, col2, col3 = st.columns([1, 1, 1])
with col2:
if st.button("π Get Answer", key="qa_btn"):
if not context.strip() or not question.strip():
st.error("β οΈ Please provide both context and question")
else:
trunc_ctx, _ = truncate_text(context, 400)
with st.spinner("π€ Analyzing..."):
try:
qa_model = get_qa()
answer = qa_model(question=question, context=trunc_ctx)['answer']
st.markdown(f"""
<div class="result-card">
<h4 style="color: #667eea; margin-bottom: 1rem;">π‘ AI Answer</h4>
<p style="font-size: 1.2rem; line-height: 1.8; color: #2d3748; font-weight: 500;">{answer}</p>
<div style="margin-top: 1rem; padding-top: 1rem; border-top: 1px solid #e2e8f0;">
<span class="stats-badge" style="background: #48bb78; color: white;">
β Answer Found
</span>
</div>
</div>
""", unsafe_allow_html=True)
except Exception as e:
st.error(f"β Error: {str(e)}")
# QUIZ TAB
with tab3:
st.markdown("### π― AI Quiz Generator")
quiz_ctx = st.text_area("π Study material:", value="", height=200, key="quiz_ctx",
placeholder="Paste content for quiz generation...")
col1, col2, col3 = st.columns([1, 1, 1])
with col2:
if st.button("π Generate Quiz", key="quiz_btn"):
if not quiz_ctx.strip():
st.error("β οΈ Please provide text")
else:
trunc_quiz, _ = truncate_text(quiz_ctx, 200)
with st.spinner("π² Creating questions..."):
sentences = sent_tokenize(trunc_quiz)[:5]
questions = [f"What is the main concept in: '{s[:70]}...'?" for s in sentences]
st.markdown('<div class="result-card">', unsafe_allow_html=True)
st.markdown("<h4 style='color: #667eea;'>π Generated Quiz Questions</h4>", unsafe_allow_html=True)
for i, q in enumerate(questions, 1):
st.markdown(f"""
<div style='background: #f7fafc; padding: 1rem; margin: 0.5rem 0; border-radius: 12px; border-left: 4px solid #667eea;'>
<strong style='color: #667eea;'>Question {i}:</strong> {q}
</div>
""", unsafe_allow_html=True)
st.markdown('</div>', unsafe_allow_html=True)
st.session_state["quiz"] = questions
# TRANSLATE TAB
with tab4:
st.markdown("### π AI Translation")
trans_text = st.text_area("βοΈ Text to translate:", height=200, key="trans_txt",
placeholder="Enter text to translate...")
col1, col2 = st.columns(2)
with col1:
lang = st.selectbox("π― Target language:", ["French", "German", "Spanish", "Italian", "Hindi"])
with col2:
st.write("")
st.write("")
if st.button("π Translate Now", key="trans_btn"):
if not trans_text.strip():
st.error("β οΈ Please provide text")
else:
model_map = {
"French": "Helsinki-NLP/opus-mt-en-fr",
"German": "Helsinki-NLP/opus-mt-en-de",
"Spanish": "Helsinki-NLP/opus-mt-en-es",
"Italian": "Helsinki-NLP/opus-mt-en-it",
"Hindi": "Helsinki-NLP/opus-mt-en-hi"
}
trunc_trans, _ = truncate_text(trans_text, 200)
with st.spinner(f"π Translating to {lang}..."):
try:
translator = load_translator(model_map[lang])
translation = translator(trunc_trans, max_length=256)[0]['translation_text']
st.markdown(f"""
<div class="result-card">
<h4 style="color: #667eea; margin-bottom: 1rem;">π Translation ({lang})</h4>
<p style="font-size: 1.2rem; line-height: 1.8; color: #2d3748;">{translation}</p>
<div style="margin-top: 1rem; padding-top: 1rem; border-top: 1px solid #e2e8f0;">
<span class="stats-badge" style="background: #48bb78; color: white;">
β Translated
</span>
</div>
</div>
""", unsafe_allow_html=True)
st.session_state["translation"] = translation
except Exception as e:
st.error(f"β Error: {str(e)}")
# KEYWORDS TAB
with tab5:
st.markdown("### π AI Keyword Extraction")
keyword_input = st.text_area("π Text for analysis:", value="", height=200, key="kw_txt",
placeholder="Paste text to extract key concepts...")
col1, col2, col3 = st.columns([1, 1, 1])
with col2:
if st.button("π Extract Keywords", key="kw_btn"):
if not keyword_input.strip():
st.error("β οΈ Please provide text")
else:
trunc_kw, _ = truncate_text(keyword_input, 200)
with st.spinner("π Analyzing concepts..."):
try:
classifier = get_classifier()
labels = ["technology", "science", "education", "health", "business", "finance", "medical"]
result = classifier(trunc_kw, labels)
keywords = [lbl for lbl, score in zip(result['labels'], result['scores']) if score > 0.3][:5]
if keywords:
st.markdown('<div class="result-card">', unsafe_allow_html=True)
st.markdown("<h4 style='color: #667eea;'>π― Extracted Keywords</h4>", unsafe_allow_html=True)
kw_html = " ".join([
f"<span style='display: inline-block; background: linear-gradient(135deg, #667eea, #764ba2); color: white; padding: 12px 24px; border-radius: 25px; margin: 8px; font-size: 1rem; font-weight: 600; box-shadow: 0 4px 12px rgba(102, 126, 234, 0.3);'>{kw}</span>"
for kw in keywords
])
st.markdown(kw_html, unsafe_allow_html=True)
st.markdown('</div>', unsafe_allow_html=True)
st.session_state["keywords"] = keywords
else:
st.info("βΉοΈ No strong keywords found")
except Exception as e:
st.error(f"β Error: {str(e)}")
# DOWNLOAD TAB
with tab6:
st.markdown("### π₯ Download Results")
def download_link(text, filename, emoji):
b64 = base64.b64encode(text.encode()).decode()
return f"""
<a href="data:file/txt;base64,{b64}" download="{filename}"
style="display: inline-block; background: linear-gradient(135deg, #667eea, #764ba2);
color: white; padding: 16px 32px; border-radius: 16px; text-decoration: none;
font-weight: 700; font-size: 1.1rem; margin: 10px; box-shadow: 0 8px 24px rgba(102, 126, 234, 0.3);
transition: all 0.3s ease;">
{emoji} Download {filename}
</a>
"""
col1, col2 = st.columns(2)
with col1:
if st.session_state["summary"]:
st.markdown(download_link(st.session_state["summary"], "summary.txt", "π"), unsafe_allow_html=True)
if st.session_state["quiz"]:
st.markdown(download_link("\n".join(st.session_state["quiz"]), "quiz.txt", "π―"), unsafe_allow_html=True)
with col2:
if st.session_state["translation"]:
st.markdown(download_link(st.session_state["translation"], "translation.txt", "π"), unsafe_allow_html=True)
if st.session_state["keywords"]:
st.markdown(download_link(", ".join(st.session_state["keywords"]), "keywords.txt", "π"), unsafe_allow_html=True)
if not any([st.session_state["summary"], st.session_state["quiz"],
st.session_state["translation"], st.session_state["keywords"]]):
st.info("βΉοΈ Generate content in other tabs to enable downloads")
# Premium Footer
st.markdown("""
<div class="premium-footer">
<p style="font-size: 1.2rem; font-weight: 600;">Built with β€οΈ by <span style="background: linear-gradient(135deg, #ffffff, #e0e7ff); -webkit-background-clip: text; -webkit-text-fill-color: transparent; font-weight: 700;">Umaima Qureshi</span></p>
<p style="font-size: 0.9rem;">Β© 2025 AI Study Helper Pro. All Rights Reserved.</p>
<p style="margin-top: 1rem;">
<a href="https://github.com/Umaima122" target="_blank"
style="color: white; text-decoration: none; padding: 8px 20px; background: rgba(255, 255, 255, 0.15);
border-radius: 20px; backdrop-filter: blur(10px); border: 1px solid rgba(255, 255, 255, 0.3);
transition: all 0.3s ease;">
π GitHub
</a>
</p>
</div>
""", unsafe_allow_html=True) |