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app.py

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+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()

requirements.txt

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+torch
+transformers
+gradio
+sentencepiece
+torchvision
+huggingface_hub
+pillow
+numpy