final / app.py
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import streamlit as st
import torch
from transformers import BertForSequenceClassification, BertTokenizerFast
from transformers import AutoModelForSequenceClassification, AutoTokenizer
import time
import pandas as pd
import base64
from PIL import Image, ImageDraw, ImageFont
import io
import streamlit.components.v1 as components
# Set page configuration
st.set_page_config(
page_title="SMS Spam Guard",
page_icon="🛡️",
layout="wide",
initial_sidebar_state="expanded"
)
# New function to create a tech-themed Spam Guard logo
def create_spam_guard_logo():
width, height = 200, 200
img = Image.new('RGBA', (width, height), (0,0,0,0)) # Transparent background
draw = ImageDraw.Draw(img)
# Flat Design Colors (slightly adjusted for modern flat look)
primary_blue = (20, 120, 220) # A strong, modern blue
accent_green = (0, 200, 150) # A vibrant, techy teal/green
light_accent_blue = (100, 180, 240) # Lighter blue for highlights or secondary elements
white_color = (255, 255, 255)
dark_gray_text = (50, 50, 50) # For subtle text if needed
# Background: A subtle gradient or a clean shape
# Option 1: Clean circle as base
# draw.ellipse([(10, 10), (width - 10, height - 10)], fill=primary_blue)
# Option 2: Modern, slightly rounded rectangle or abstract shape
# For a more abstract, less shield-like, but still contained feel:
# Let's try a stylized hexagon or a shape made of intersecting elements.
# Design: Abstract interlocking shapes suggesting SG or a data block / shield
# Main body - a dynamic shape
path = [
(width * 0.15, height * 0.2), (width * 0.85, height * 0.2),
(width * 0.75, height * 0.8), (width * 0.25, height * 0.8)
]
draw.polygon(path, fill=primary_blue)
# Accent element (e.g., a stylized 'S' or a connecting line)
draw.line([
(width * 0.3, height * 0.35),
(width * 0.7, height * 0.35),
(width * 0.7, height * 0.5),
(width * 0.3, height * 0.5),
(width * 0.3, height * 0.65),
(width * 0.7, height * 0.65)
], fill=accent_green, width=18, joint="miter")
# Adding a subtle highlight or secondary shape for depth (still flat)
draw.polygon([
(width * 0.18, height * 0.22), (width * 0.82, height * 0.22),
(width * 0.72, height * 0.78), (width * 0.28, height * 0.78)
], outline=light_accent_blue, width=4)
# Text "SG" - Clean, modern, sans-serif font
try:
# Attempt to load a more modern, geometric font if available
# For example, 'Montserrat-Bold.ttf' or 'Roboto-Medium.ttf'
# If not, Arial Bold is a safe fallback.
font = ImageFont.truetype("arialbd.ttf", 70) # Arial Bold as a fallback
except IOError:
font = ImageFont.load_default() # Fallback
text = "SG"
text_bbox = draw.textbbox((0,0), text, font=font)
text_width = text_bbox[2] - text_bbox[0]
text_height = text_bbox[3] - text_bbox[1]
text_x = (width - text_width) / 2
# text_y = (height - text_height) / 2
# Slightly adjust y if the accent green takes up visual center
text_y = (height - text_height) / 2 + 5 # Adjusted to better center with the green shape
# Make text white and prominent
draw.text((text_x, text_y), text, font=font, fill=white_color)
buffered = io.BytesIO()
img.save(buffered, format="PNG")
img_str = base64.b64encode(buffered.getvalue()).decode()
return f"data:image/png;base64,{img_str}"
# Custom CSS for styling with China Mobile colors
st.markdown("""
<style>
:root {
--cm-blue: #0072d0; /* 调深主蓝色 */
--cm-light-blue: #4aa3df;
--cm-green: #00a651; /* 调深绿色 */
--cm-bright-green: #70c050; /* 调整亮绿色 */
--cm-dark-blue: #004080; /* 更深的蓝色 */
--cm-gray: #f5f7fa;
--text-color: #222222; /* 更深的文本颜色 */
--card-bg: rgba(255, 255, 255, 0.92); /* 增加不透明度 */
--card-border: rgba(180, 180, 180, 0.5); /* 更明显的边框 */
}
body {
font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji";
line-height: 1.6;
color: var(--text-color);
-webkit-font-smoothing: antialiased; /* 改善文字渲染 */
-moz-osx-font-smoothing: grayscale; /* 改善文字渲染 */
}
.stApp {
background: linear-gradient(135deg, #c4e3ff 0%, #e8f4ff 60%, #ddf5dd 100%); /* 更亮的背景以增加对比度 */
}
/* 标题强化样式 - 提高对比度 */
.main-header {
font-size: 3.2rem !important;
font-weight: 800 !important;
margin-bottom: 0.3rem;
color: var(--cm-dark-blue); /* 纯色替代渐变 */
text-shadow: none; /* 移除阴影以增加锐利度 */
-webkit-text-fill-color: var(--cm-dark-blue); /* 覆盖之前的透明设置 */
-moz-text-fill-color: var(--cm-dark-blue);
text-fill-color: var(--cm-dark-blue);
letter-spacing: -0.5px;
}
.sub-header {
font-size: 1.25rem;
color: #333333; /* 更深的颜色 */
margin-bottom: 2rem;
font-weight: 500;
}
/* 各组件样式强化 - 更高对比度 */
.highlight {
background-color: var(--card-bg);
padding: 1.8rem;
border-radius: 16px;
margin-bottom: 1.5rem;
box-shadow: 0 8px 20px rgba(0, 0, 0, 0.15); /* 更深的阴影 */
transition: all 0.3s ease-out;
border: 1px solid var(--card-border);
}
.highlight:hover {
box-shadow: 0 12px 24px rgba(0, 0, 0, 0.18);
transform: translateY(-3px);
}
.result-card, .card-gradient, .card-shadow {
padding: 1.8rem;
border-radius: 16px;
margin-bottom: 1.2rem;
box-shadow: 0 8px 20px rgba(0, 0, 0, 0.15);
transition: transform 0.3s ease-out, box-shadow 0.3s ease-out;
border: 1px solid var(--card-border);
background-color: white; /* 纯白色背景 */
}
.result-card:hover, .card-gradient:hover, .card-shadow:hover {
box-shadow: 0 12px 24px rgba(0, 0, 0, 0.18);
transform: translateY(-4px) scale(1.01);
}
.spam-alert {
background: #fff0f0; /* 移除渐变,使用纯色 */
border-left: 8px solid #EF4444;
color: #aa0000; /* 更深的红色 */
}
.ham-alert {
background: #f0fff0; /* 移除渐变,使用纯色 */
border-left: 8px solid var(--cm-green);
color: #005500; /* 更深的绿色 */
}
/* 页脚加强 */
.footer {
text-align: center;
margin-top: 4rem;
padding-top: 2rem;
border-top: 1px solid var(--card-border);
font-size: 0.9rem;
color: #444444; /* 更深的灰色 */
}
/* 标签样式加强 */
.language-tag {
display: inline-block;
padding: 0.4rem 1rem;
background-color: var(--cm-dark-blue); /* 更深的蓝色 */
color: white;
border-radius: 20px;
font-size: 0.95rem;
font-weight: 600;
margin-right: 0.6rem;
box-shadow: 0 3px 6px rgba(0, 64, 128, 0.3); /* 更深的阴影 */
}
/* 按钮样式加强 */
.stButton > button {
border-radius: 12px;
padding: 0.7rem 1.4rem;
font-weight: 600;
transition: all 0.25s ease;
box-shadow: 0 4px 8px rgba(0,0,0,0.12);
font-size: 1rem;
border: 1px solid rgba(0,0,0,0.1); /* 添加边框 */
}
.stButton > button:hover {
transform: translateY(-3px);
box-shadow: 0 6px 12px rgba(0,0,0,0.15);
}
/* 分析按钮更加突出 */
div.stButton[key="analyze_btn"] > button,
button[kind="primary"]
{
background: var(--cm-blue); /* 纯色替代渐变 */
color: white !important;
font-weight: 700;
padding: 0.8rem 1.5rem;
font-size: 1.1rem;
letter-spacing: 0.5px;
text-transform: uppercase;
border: none;
}
div.stButton[key="analyze_btn"] > button:hover {
background: var(--cm-dark-blue);
box-shadow: 0 8px 15px rgba(0, 64, 128, 0.3);
}
/* 侧边栏按钮样式 */
.sidebar .stButton > button {
background-color: var(--cm-green);
text-transform: none;
}
.sidebar .stButton > button:hover {
background-color: var(--cm-bright-green);
}
/* 文本框样式加强 */
div.stTextArea > div > div > textarea {
border-color: #5599dd; /* 更鲜明的边框颜色 */
border-width: 2px;
border-radius: 12px;
background-color: white; /* 纯白色背景 */
font-size: 1.05rem;
padding: 12px;
color: #222; /* 确保文本为深色 */
}
div.stTextArea > div > div > textarea:focus {
border-color: var(--cm-blue);
box-shadow: 0 0 0 4px rgba(0, 114, 208, 0.25);
background-color: white;
}
/* 玻璃效果加强 - 减少模糊,增加清晰度 */
.glass-effect {
background: rgba(255, 255, 255, 0.92); /* 增加不透明度 */
backdrop-filter: blur(6px); /* 减少模糊程度 */
border-radius: 20px;
border: 1px solid rgba(255, 255, 255, 0.7); /* 更明显的边框 */
transition: all 0.3s ease-in-out;
box-shadow: 0 8px 32px rgba(31, 38, 135, 0.15);
}
.glass-effect:hover {
box-shadow: 0 15px 30px rgba(31, 38, 135, 0.25);
transform: translateY(-5px);
}
/* 加载动画加强 */
.loading-animation-container svg {
animation: spin 1.2s linear infinite, pulse-opacity 1.2s ease-in-out infinite alternate;
transform-origin: center center;
width: 70px;
height: 70px;
filter: drop-shadow(0 0 2px rgba(0,0,0,0.2)); /* 添加轻微阴影 */
}
/* 图表样式加强 */
.stChart > div > div > div > svg g rect {
fill: var(--cm-blue) !important;
transition: fill 0.3s ease;
}
.stChart > div > div > div > svg g rect:hover {
fill: var(--cm-dark-blue) !important;
}
/* 结果文本加强 - 提高对比度 */
.result-content {
font-size: 1.1rem;
color: #222; /* 确保深色文本 */
}
.result-value {
font-size: 1.2rem;
font-weight: 700;
color: var(--cm-dark-blue);
}
.result-title {
font-size: 1.4rem;
font-weight: 700;
color: var(--cm-dark-blue);
margin-bottom: 15px;
letter-spacing: 0.5px;
}
/* 强调主要文字内容 - 提高对比度 */
h3 {
font-size: 1.8rem !important;
font-weight: 700 !important;
color: var(--cm-dark-blue) !important;
letter-spacing: -0.5px;
margin-bottom: 20px !important;
}
h4 {
font-size: 1.4rem !important;
font-weight: 700 !important;
letter-spacing: -0.3px;
color: #222 !important;
}
h5 {
font-size: 1.2rem !important;
font-weight: 600 !important;
color: #333 !important;
}
p, li {
font-size: 1.05rem !important;
color: #333 !important;
}
strong {
font-weight: 700;
color: var(--cm-dark-blue);
}
</style>
""", unsafe_allow_html=True)
@st.cache_resource
def load_language_model():
"""Load the language detection model"""
model_name = "papluca/xlm-roberta-base-language-detection"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)
return tokenizer, model
@st.cache_resource
def load_spam_model():
"""Load the fine-tuned BERT spam detection model"""
model_path = "chjivan/final"
tokenizer = BertTokenizerFast.from_pretrained(model_path)
model = BertForSequenceClassification.from_pretrained(model_path)
return tokenizer, model
def detect_language(text, tokenizer, model):
"""Detect the language of the input text"""
inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
with torch.no_grad():
outputs = model(**inputs)
logits = outputs.logits
probabilities = torch.softmax(logits, dim=1)[0]
predicted_class_id = torch.argmax(probabilities).item()
predicted_language = model.config.id2label[predicted_class_id]
confidence = probabilities[predicted_class_id].item()
top_3_indices = torch.topk(probabilities, 3).indices.tolist()
top_3_probs = torch.topk(probabilities, 3).values.tolist()
top_3_langs = [(model.config.id2label[idx], prob) for idx, prob in zip(top_3_indices, top_3_probs)]
return predicted_language, confidence, top_3_langs
def classify_spam(text, tokenizer, model):
"""Classify the input text as spam or ham"""
inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=128)
with torch.no_grad():
outputs = model(**inputs)
logits = outputs.logits
probabilities = torch.softmax(logits, dim=1)[0]
predicted_class_id = torch.argmax(probabilities).item()
confidence = probabilities[predicted_class_id].item()
is_spam = predicted_class_id == 1
return is_spam, confidence
# Get the new Spam Guard logo
logo_data = create_spam_guard_logo()
# Add custom CSS animations (ensure this is defined before use)
st.markdown("""
<style>
@keyframes fadeIn {
from { opacity: 0; transform: translateY(20px); }
to { opacity: 1; transform: translateY(0); }
}
@keyframes pulse {
0% { transform: scale(1); }
50% { transform: scale(1.03); }
100% { transform: scale(1); }
}
@keyframes slideInLeft {
from { opacity: 0; transform: translateX(-30px); }
to { opacity: 1; transform: translateX(0); }
}
@keyframes slideInRight {
from { opacity: 0; transform: translateX(30px); }
to { opacity: 1; transform: translateX(0); }
}
.animated-fadeIn {
animation: fadeIn 0.8s ease-out forwards;
}
.animated-pulse-subtle {
animation: pulse 2.5s infinite ease-in-out;
}
.animated-slideInLeft {
animation: slideInLeft 0.7s cubic-bezier(0.25, 0.46, 0.45, 0.94) forwards;
}
.animated-slideInRight {
animation: slideInRight 0.7s cubic-bezier(0.25, 0.46, 0.45, 0.94) forwards;
}
.neon-text {
text-shadow: 0 0 3px rgba(0, 134, 209, 0.2), 0 0 6px rgba(0, 134, 209, 0.15);
}
</style>
""", unsafe_allow_html=True)
# Load both models
with st.spinner("Loading models... This may take a moment."):
lang_tokenizer, lang_model = load_language_model()
spam_tokenizer, spam_model = load_spam_model()
# App Header with new logo
st.markdown(f"""
<div style="display: flex; align-items: center; margin-bottom: 2.5rem; padding: 1.5rem; background: rgba(255,255,255,0.92); border-radius: 20px; box-shadow: 0 8px 24px rgba(0,0,0,0.12);" class="animated-fadeIn">
<img src="{logo_data}" style="height: 100px; margin-right: 30px; border-radius: 16px; box-shadow: 0 5px 15px rgba(0,0,0,0.15);" class="animated-pulse-subtle">
<div>
<h1 class="main-header">SMS Spam Guard</h1>
<p class="sub-header">Intelligent SMS Filtering Assistant by China Mobile Communications Group Co.,Ltd</p>
</div>
</div>
""", unsafe_allow_html=True)
# Create a two-column layout
col1, col2 = st.columns([1, 2]) # Adjusted column ratio for better balance
# Sidebar content in col1 (styled as a card)
with col1:
st.markdown(f"""
<div class="glass-effect animated-slideInLeft" style="padding: 25px; border-radius: 12px; margin-bottom: 25px; animation-delay: 0.1s;">
<img src="{logo_data}" style="width: 60%; margin: 0 auto 20px auto; display: block; border-radius: 8px;">
<h3 style="color: var(--cm-blue); text-align: center; margin-bottom:15px;">About Us</h3>
<p style="font-size:0.9rem; color: #444;">China Mobile Communications Group Co.,Ltd provides intelligent communication security solutions to protect users from spam and fraudulent messages.</p>
</div>
""", unsafe_allow_html=True)
st.markdown("""
<div class="glass-effect animated-slideInLeft" style="padding: 25px; border-radius: 12px; margin-bottom: 25px; animation-delay: 0.2s;">
<h4 style="color: var(--cm-blue); margin-bottom:15px;">Our Technology</h4>
<ul style="padding-left: 20px; font-size:0.9rem; color: #444;">
<li style="margin-bottom:8px;">✅ Advanced AI-powered spam detection</li>
<li style="margin-bottom:8px;">🌐 Multi-language support</li>
<li style="margin-bottom:8px;">🔒 Secure and private processing</li>
<li>⚡ Real-time analysis</li>
</ul>
</div>
""", unsafe_allow_html=True)
st.markdown("<h4 style='color: var(--cm-blue); margin-left: 5px; margin-bottom:10px;' class='animated-slideInLeft' data-animation-delay='0.3s'>Sample Messages</h4>", unsafe_allow_html=True)
# Sample buttons with unique keys and improved help text
button_style = "margin-bottom: 8px; width: 100%;"
if st.button("Sample Spam (English)", key="spam_btn_en", help="Load a sample English spam message", type="secondary"):
st.session_state.sms_input = "URGENT: You have won a $1,000 Walmart gift card. Go to http://bit.ly/claim-prize to claim now before it expires!"
if st.button("Sample Legitimate (English)", key="ham_btn_en", help="Load a sample English legitimate message", type="secondary"):
st.session_state.sms_input = "Your Amazon package will be delivered today. Thanks for ordering from Amazon!"
if st.button("Sample Message (French)", key="french_btn_fr", help="Load a sample French message", type="secondary"):
st.session_state.sms_input = "Bonjour! Votre réservation pour le restaurant est confirmée pour ce soir à 20h. À bientôt!"
if st.button("Sample Message (Spanish)", key="spanish_btn_es", help="Load a sample Spanish message", type="secondary"):
st.session_state.sms_input = "Hola, tu cita médica está programada para mañana a las 10:00. Por favor llega 15 minutos antes."
# Main content in col2
with col2:
st.markdown("""
<div class="glass-effect animated-fadeIn" style="padding: 30px; border-radius: 16px; margin-bottom: 30px; animation-delay: 0.1s;">
<h3 style="color: var(--cm-blue); margin-bottom: 20px; text-align:center;">Analyze Your Message</h3>
</div>
""", unsafe_allow_html=True)
sms_input = st.text_area(
"", # Label removed for cleaner look, relying on header
value=st.session_state.get("sms_input", ""),
height=120, # Increased height
key="sms_input",
placeholder="Enter the SMS message you want to analyze here...",
help="Paste or type the SMS message to check if it's spam or legitimate."
)
analyze_button = st.button("📱 Analyze Message", use_container_width=True, key="analyze_btn", type="primary")
if analyze_button and sms_input:
with st.spinner(""):
st.markdown("""
<div class="loading-animation-container animated-fadeIn" style="text-align: center; color: var(--cm-blue); margin: 25px 0;">
<svg width="60" height="60" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
<path d="M12 2C17.5228 22 22 17.5228 22 12C22 6.47715 17.5228 2 12 2V2Z" stroke="var(--cm-blue)" stroke-width="2.5" stroke-linecap="round" stroke-linejoin="round" />
<path d="M12 2C6.47715 2 2 6.47715 2 12H2Z" stroke="var(--cm-light-blue)" stroke-width="2.5" stroke-linecap="round" stroke-linejoin="round" />
</svg>
<p style="font-size: 1.1rem; margin-top: 10px;">Analyzing your message...</p>
</div>
""", unsafe_allow_html=True)
time.sleep(0.5) # Simulate some work
lang_start_time = time.time()
lang_code, lang_confidence, top_langs = detect_language(sms_input, lang_tokenizer, lang_model)
lang_time = time.time() - lang_start_time
lang_names = {
"ar": "Arabic", "bg": "Bulgarian", "de": "German", "el": "Greek", "en": "English",
"es": "Spanish", "fr": "French", "hi": "Hindi", "it": "Italian", "ja": "Japanese",
"nl": "Dutch", "pl": "Polish", "pt": "Portuguese", "ru": "Russian", "sw": "Swahili",
"th": "Thai", "tr": "Turkish", "ur": "Urdu", "vi": "Vietnamese", "zh": "Chinese"
}
lang_name = lang_names.get(lang_code, lang_code.capitalize())
spam_start_time = time.time()
is_spam, spam_confidence = classify_spam(sms_input, spam_tokenizer, spam_model)
spam_time = time.time() - spam_start_time
st.markdown("<h3 style='color: var(--cm-blue); margin-top: 30px; text-align:center;' class='animated-fadeIn'>Analysis Results</h3>", unsafe_allow_html=True)
res_col1, res_col2 = st.columns(2)
with res_col1:
st.markdown(f"""
<div class="result-card animated-slideInLeft" style="animation-delay: 0.2s; background: linear-gradient(135deg, #e6f7ff 0%, #f0faff 100%);">
<h4 class="result-title">📊 Language Detection</h4>
<div class="result-content">
<div style="display: flex; align-items: center; margin-bottom: 15px;">
<span class="language-tag">{lang_name}</span>
<span>Detected with <span class="result-value">{lang_confidence:.1%}</span> confidence</span>
</div>
<h5 style="color: var(--cm-dark-blue); margin-bottom: 10px; font-size:0.95rem;">Top language probabilities:</h5>
<ul style="font-size:0.9rem; padding-left:18px;">
""", unsafe_allow_html=True)
for l_code, l_prob in top_langs:
st.markdown(f"<li>{lang_names.get(l_code, l_code.capitalize())}: {l_prob:.1%}</li>", unsafe_allow_html=True)
st.markdown(f"""
</ul>
<p style="margin-top: 15px; font-size:0.85rem; color:#555;">⏱️ Processing time: {lang_time:.3f} seconds</p>
</div>
""", unsafe_allow_html=True)
with res_col2:
result_confidence = spam_confidence if is_spam else (1 - spam_confidence)
if is_spam:
st.markdown(f"""
<div class="result-card spam-alert animated-slideInRight" style="animation-delay: 0.3s;">
<h4 class="result-title">🔍 Spam Detection</h4>
<div class="result-content">
<div style="font-size: 1.1rem; font-weight: bold; color: #b91c1c; margin-bottom: 10px;">⚠️ SPAM DETECTED</div>
<p style="margin-bottom:10px;">Confidence: <span class="result-value">{result_confidence:.1%}</span></p>
<p style="font-size:0.9rem;">This message shows strong indicators of being spam.</p>
<p style="margin-top: 15px; font-size:0.85rem; color:#555;">⏱️ Processing time: {spam_time:.3f} seconds</p>
</div>
</div>
""", unsafe_allow_html=True)
else:
st.markdown(f"""
<div class="result-card ham-alert animated-slideInRight" style="animation-delay: 0.3s;">
<h4 class="result-title">🔍 Spam Detection</h4>
<div class="result-content">
<div style="font-size: 1.1rem; font-weight: bold; color: #047857; margin-bottom: 10px;">✅ LEGITIMATE MESSAGE</div>
<p style="margin-bottom:10px;">Confidence: <span class="result-value">{result_confidence:.1%}</span></p>
<p style="font-size:0.9rem;">This message appears to be legitimate.</p>
<p style="margin-top: 15px; font-size:0.85rem; color:#555;">⏱️ Processing time: {spam_time:.3f} seconds</p>
</div>
</div>
""", unsafe_allow_html=True)
st.markdown("""
<div class="glass-effect animated-fadeIn" style="padding: 25px; border-radius: 12px; margin: 30px 0; animation-delay: 0.4s;">
<h3 style="color: var(--cm-blue); margin-bottom: 15px; text-align:center;">📋 Summary & Recommendations</h3>
""", unsafe_allow_html=True)
if is_spam:
st.warning("📵 **Recommended Action**: This message should be treated with caution, blocked, or moved to the spam folder.")
st.markdown("""
**Potential reasons for spam classification:**
<ul style="font-size:0.9rem;">
<li>Contains suspicious language patterns or urgency.</li>
<li>May include unsolicited offers or links to untrusted sites.</li>
<li>Resembles known spam message structures.</li>
</ul>
""", unsafe_allow_html=True)
else:
st.success("✅ **Recommended Action**: This message seems safe and can be delivered to the inbox.")
st.markdown("</div>", unsafe_allow_html=True)
st.markdown("""
<div class="glass-effect animated-fadeIn" style="padding: 25px; border-radius: 12px; margin: 30px 0; animation-delay: 0.5s;">
<h3 style="color: var(--cm-blue); margin-bottom: 20px; text-align:center;">📈 Confidence Visualization</h3>
""", unsafe_allow_html=True)
chart_data = pd.DataFrame({
'Task': ['Language Detection Confidence', 'Spam Classification Certainty'],
'Confidence': [lang_confidence, result_confidence]
})
st.bar_chart(chart_data.set_index('Task'), height=300, use_container_width=True)
st.markdown("</div>", unsafe_allow_html=True)
# Footer
st.markdown(f"""
<div class="footer animated-fadeIn" style="animation-delay: 0.8s;">
<div style="display: flex; justify-content: center; align-items: center; margin-bottom: 10px;">
<img src="{logo_data}" style="height: 25px; margin-right: 12px; border-radius:4px;">
<span>© {time.strftime('%Y')} China Mobile Communications Group Co.,Ltd | <a href="http://www.chinamobile.com" target="_blank" style="color: var(--cm-blue); text-decoration:none;">www.chinamobile.com</a></span>
</div>
<p style="font-size:0.8rem; color:#888;">SMS Spam Guard: Your intelligent shield against unwanted communications.</p>
</div>
""", unsafe_allow_html=True)