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import streamlit as st
import pandas as pd
import random
import time
import requests
# Function to load Lottie animations (optional, if you still want to use JSON data in future)
def load_lottieurl(url: str):
r = requests.get(url)
if r.status_code != 200:
return None
return r.json()
# Set page config
st.set_page_config(page_title="EdgeWise Content Moderation", page_icon="🤖", layout="wide")
# Custom CSS for black background text area with white text
st.markdown("""
<style>
.main {
background-color: #f0f2f6;
}
.stTextInput > div > div > input {
background-color: #ffffff;
}
.stTextArea > div > div > textarea {
background-color: #000000;
color: #ffffff;
}
.stButton > button {
background-color: #4CAF50;
color: white;
font-weight: bold;
}
</style>
""", unsafe_allow_html=True)
# Sidebar
with st.sidebar:
st.title("EdgeWise")
# Optional: Add a static image or remove the animation
st.image("https://via.placeholder.com/200", caption="Content Moderation Bot")
st.write("---")
st.write("This application is designed for content moderation and works best with local deployment.")
st.write("[GitHub Repository](https://github.com/Ashar086/EdgeWise)")
# Main content
st.title("Edge Device Content Moderation Bot 🤖")
# Load the CSV to get the sentiment classes
@st.cache_data
def load_data():
filename = "synData.csv"
df = pd.read_csv(filename, names=["sentiment", "text"], encoding="utf-8", encoding_errors="replace")
return df
df = load_data()
# Get unique sentiments from the CSV file
sentiments = sorted(df.sentiment.unique())
# Display sentiment categories
st.write("### Detectable Text Categories:")
cols = st.columns(4)
for i, sentiment in enumerate(sentiments):
cols[i % 4].write(f"- {sentiment}")
st.write("---")
# User input with black background and white text
user_input = st.text_area("Enter text to analyze:", height=150)
if st.button("Analyze Sentiment"):
if user_input:
with st.spinner("Analyzing sentiment..."):
# Simulate analysis with a progress bar
progress_bar = st.progress(0)
for i in range(100):
time.sleep(0.01)
progress_bar.progress(i + 1)
# Simulate a random response
sentiment_detected = random.choice(sentiments)
# Display the result
st.write("---")
col1, col2 = st.columns([1, 2])
with col1:
# Optional: Add a static image instead of animation
st.image("https://via.placeholder.com/200", caption="Analysis in Progress")
with col2:
st.write("## Analysis Result")
st.write(f"Detected text category: **{sentiment_detected}**")
st.info("This is a simulated response. The actual analysis is best performed locally for privacy and efficiency.")
else:
st.warning("Please enter some text to analyze.")
# Footer
st.write("---")
st.write("EdgeWise Content Moderation Bot - Powered by AI")
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