| import gradio as gr |
| from transformers import pipeline |
|
|
| |
| sentiment_pipeline = pipeline("sentiment-analysis") |
|
|
|
|
| |
| def predict_sentiment(movie_name, review, history): |
| result = sentiment_pipeline(review)[0] |
| label = result["label"] |
| score = result["score"] |
|
|
| sentiment_text = "🌟 Positive Review" if label == "POSITIVE" else "💔 Negative Review" |
| emoji = "😊" if label == "POSITIVE" else "😞" |
| sentiment_result = f"{sentiment_text} {emoji} | Confidence: {score:.2f}" |
|
|
| |
| history.append((movie_name, review, sentiment_result, label)) |
|
|
| |
| history_display = "" |
| for m_name, review_text, result_text, sentiment_label in reversed(history): |
| bg_color = "#D1F2EB" if sentiment_label == "POSITIVE" else "#FADBD8" |
| history_display += f""" |
| <div class="fade-card" style="background-color: {bg_color}; padding: 12px; margin-bottom: 10px; |
| border-radius: 8px; box-shadow: 0 0 5px rgba(0,0,0,0.1); color: #000;"> |
| <strong style="color:#000;">Movie:</strong> <span style="color:#000;">{m_name}</span><br> |
| <strong style="color:#000;">Review:</strong><br><span style="color:#000;">{review_text}</span><br><br> |
| <strong style="color:#000;">Result:</strong><br><span style="color:#000;">{result_text}</span> |
| </div> |
| """ |
|
|
| return sentiment_result, history_display, history |
|
|
|
|
| |
| def clear_history(): |
| return "", "", "", [] |
|
|
|
|
| |
| with gr.Blocks(css=""" |
| body { |
| background-color: #FFF8E1; |
| } |
| .fade-card { |
| animation: fadeIn 1s ease-in-out; |
| } |
| @keyframes fadeIn { |
| 0% { opacity: 0; transform: translateY(20px); } |
| 100% { opacity: 1; transform: translateY(0); } |
| } |
| """, theme=gr.themes.Default(primary_hue="purple")) as demo: |
| gr.HTML( |
| """ |
| <div style=' |
| background: linear-gradient(to right, #FFF1EB, #ACE0F9); |
| padding: 30px; |
| border-radius: 12px; |
| box-shadow: 0 0 10px rgba(0,0,0,0.1); |
| '> |
| <h1 style='text-align: center; color: #6C63FF;'>🎥 Movie Review Sentiment Analyzer</h1> |
| <p style='text-align: center; color: black;'> |
| Analyze your review below to see if it feels 💔 Negative or 🌟 Positive.<br> |
| Previous reviews appear as colorful cards below. |
| </p> |
| </div> |
| <hr> |
| """ |
| ) |
|
|
| review_history = gr.State([]) |
|
|
| with gr.Row(): |
| with gr.Column(scale=2): |
| movie_name = gr.Textbox( |
| label="🎬 Enter Your Movie Name", |
| placeholder="Ex: Leo, Don, Vikram, etc..." |
| ) |
| review_input = gr.Textbox( |
| label="🎬 Your Movie Review", |
| placeholder="Type your movie review here...", |
| lines=5 |
| ) |
| with gr.Row(): |
| clear_button = gr.Button("❌ Clear Input") |
| submit_button = gr.Button("✅ Analyze Review") |
| clear_history_button = gr.Button("🗑️ Clear All History") |
|
|
| with gr.Column(scale=1): |
| sentiment_output = gr.Textbox( |
| label="🔍 Sentiment Result", |
| interactive=False |
| ) |
|
|
| history_box = gr.HTML(label="📝 Review History") |
|
|
| submit_button.click( |
| fn=predict_sentiment, |
| inputs=[movie_name, review_input, review_history], |
| outputs=[sentiment_output, history_box, review_history] |
| ) |
|
|
| clear_button.click( |
| lambda: ("", "",), |
| None, |
| [movie_name, review_input], |
| queue=False |
| ) |
|
|
| clear_history_button.click( |
| fn=clear_history, |
| inputs=None, |
| outputs=[sentiment_output, history_box, review_history], |
| queue=False |
| ) |
|
|
|
|
| |
| demo.launch() |
|
|
