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import streamlit as st |
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st.set_page_config(page_title="YouTube Sentiment Analyzer 🎬", layout="wide") |
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import pandas as pd |
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from multilingual_sentiment_model import ( |
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extract_video_id, get_video_title, get_comments, |
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analyze_sentiment, plot_pie_chart, get_overall_sentiment |
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) |
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st.markdown(""" |
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<style> |
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.video-row { display: flex; align-items: center; justify-content: space-between; margin-bottom: 5px; } |
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.video-row button { margin-left: 10px; } |
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</style> |
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""", unsafe_allow_html=True) |
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st.markdown(""" |
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<h2 style='text-align: center; margin-bottom: 0;'>🎬 YouTube Sentiment Analyzer</h2> |
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<p style='text-align: center; font-size: 16px; margin-top: 0;'>Analyze viewer sentiments — Positive, Neutral or Negative</p> |
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<hr style="margin-top: 0; margin-bottom: 1.5rem;"> |
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""", unsafe_allow_html=True) |
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example_videos = { |
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"https://www.youtube.com/watch?v=JGwWNGJdvx8": "Ed Sheeran - Shape of You", |
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"https://www.youtube.com/watch?v=dvgZkm1xWPE": "Coldplay - Viva La Vida", |
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"https://www.youtube.com/watch?v=YQHsXMglC9A": "Adele - Hello", |
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"https://www.youtube.com/watch?v=09R8_2nJtjg": "Maroon 5 - Sugar", |
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"https://www.youtube.com/watch?v=7wtfhZwyrcc": "Imagine Dragons - Believer" |
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} |
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col1, col2 = st.columns([1.2, 1.8]) |
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with col1: |
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st.markdown("### 📥 Input") |
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if "url" not in st.session_state: |
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st.session_state["url"] = "" |
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url = st.text_input("YouTube Video URL", value=st.session_state["url"], key="youtube_url") |
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num_comments = st.slider("Number of Comments ", 10, 50, value=20, step=5) |
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analyze_btn = st.button("🔍 Analyze") |
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st.markdown("##### 🔗 Example YouTube Videos") |
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st.text("Copy the links if you don't have any") |
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for link, title in example_videos.items(): |
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st.markdown(f"{link}") |
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with col2: |
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if analyze_btn: |
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video_id = extract_video_id(url) |
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if not video_id: |
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st.error("❌ Invalid YouTube URL.") |
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else: |
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with st.spinner("Fetching video title, comments and analyzing sentiment..."): |
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video_title = get_video_title(video_id) |
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comments, error = get_comments(video_id, max_results=num_comments) |
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if error: |
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st.error(f"❌ {error}") |
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elif not comments: |
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st.warning("⚠️ No comments found for this video.") |
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else: |
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st.markdown(f"### 🎥 {video_title}", unsafe_allow_html=True) |
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results, counts = analyze_sentiment(comments) |
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sentiment_summary = get_overall_sentiment(counts) |
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pie_chart = plot_pie_chart(counts, video_title) |
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color = '#66bb6a' if 'Positive' in sentiment_summary else '#ef5350' if 'Negative' in sentiment_summary else "#2cb1f4" |
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st.markdown( |
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f"<h4 style='color: {color}; text-align: center;'>{sentiment_summary}</h4>", |
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unsafe_allow_html=True |
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) |
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left, center, right = st.columns([1, 2, 1]) |
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with center: |
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st.plotly_chart(pie_chart, use_container_width=False) |
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st.markdown("##### 💬 Top 5 Comments") |
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df_sample = pd.DataFrame(results).head(5) |
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st.table(df_sample[['Comment', 'Sentiment']]) |
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csv = df_sample.to_csv(index=False).encode('utf-8') |
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st.download_button( |
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label="📥 Download Top Comments as CSV", |
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data=csv, |
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file_name='top_comments.csv', |
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mime='text/csv' |
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) |
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st.markdown("<hr>", unsafe_allow_html=True) |
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st.markdown( |
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"<p style='text-align: center; font-size: 12px; color: gray;'>© 2025 YouTube Sentiment Analyzer | Built with ❤️ using Streamlit</p>", |
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unsafe_allow_html=True |
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) |
