app.py

import gradio as gr
from transformers import pipeline

# Load the sentiment analysis model
model_name = "AventIQ-AI/bert-movie-review-sentiment-analysis"
sentiment_analyzer = pipeline("sentiment-analysis", model=model_name)

# Mapping labels (Adjust based on actual model output)
label_mapping = {
    "LABEL_0": "Negative",
    "LABEL_1": "Positive"
}

def analyze_sentiment(review_text):
    """Analyzes the sentiment of a given movie review."""
    if not review_text.strip():
        return "⚠️ Please enter a movie review."
    
    result = sentiment_analyzer(review_text)[0]
    label = label_mapping.get(result['label'], result['label'])  # Convert label
    confidence = round(result['score'] * 100, 2)

    emoji = "😃" if label == "Positive" else "😞"
    return f"{emoji} Sentiment: **{label}** (Confidence: {confidence}%)"

# Example movie reviews
example_reviews = [
    "This movie was absolutely fantastic! The story was gripping, and the acting was top-notch.",
    "I was really disappointed. The plot was dull, and the characters were not relatable at all.",
    "An entertaining experience with great visuals and a compelling story!",
    "One of the worst movies I've ever seen. Total waste of time."
]

# Create Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("## 🎬 Movie Review Sentiment Analysis")
    gr.Markdown("Enter a movie review, and the AI will determine if the sentiment is **positive** or **negative**!")

    with gr.Row():
        input_text = gr.Textbox(label="✍️ Enter your movie review:", 
                                placeholder="Example: 'The movie was thrilling with an amazing plot twist!'")

    analyze_button = gr.Button("🔍 Analyze Sentiment")
    output_text = gr.Textbox(label="🎭 Sentiment Result:")

    gr.Markdown("### 🎥 Example Reviews")
    example_buttons = [gr.Button(example) for example in example_reviews]

    for btn in example_buttons:
        btn.click(fn=lambda text=btn.value: text, outputs=input_text)

    analyze_button.click(analyze_sentiment, inputs=input_text, outputs=output_text)

# Launch the Gradio app
demo.launch()