Add Gradio app

app.py

@@ -0,0 +1,192 @@
+"""
+Myanmar Ghost - Gradio Demo for HuggingFace Spaces
+
+This app provides an interactive demo for Myanmar sentiment analysis.
+"""
+
+import gradio as gr
+import sys
+from pathlib import Path
+
+# Add src to path
+sys.path.insert(0, str(Path(__file__).parent))
+
+# Try to import the model components
+try:
+    from src.data_processing.text_normalizer import MyanmarTextNormalizer
+    from src.augmentation.synonym_replacer import MyanmarSynonymReplacer
+    MODULES_LOADED = True
+except ImportError as e:
+    MODULES_LOADED = False
+    print(f"Warning: Some modules not loaded: {e}")
+
+
+# Sentiment labels
+SENTIMENT_LABELS = ["negative", "neutral", "positive", "sarcastic"]
+
+# Initialize components
+normalizer = MyanmarTextNormalizer() if MODULES_LOADED else None
+replacer = MyanmarSynonymReplacer() if MODULES_LOADED else None
+
+
+def analyze_sentiment(text: str) -> dict:
+    """Analyze sentiment of Myanmar text."""
+    if not text.strip():
+        return {
+            "text": text,
+            "sentiment": "neutral",
+            "confidence": 0.0,
+            "probabilities": {label: 0.25 for label in SENTIMENT_LABELS},
+        }
+    
+    # Normalize text
+    if normalizer:
+        normalized = normalizer.normalize_line(text)
+    else:
+        normalized = text
+    
+    # Mock prediction (replace with actual model)
+    # In production, load the trained model here
+    import random
+    probs = [random.random() for _ in SENTIMENT_LABELS]
+    total = sum(probs)
+    probs = [p/total for p in probs]
+    
+    pred_idx = probs.index(max(probs))
+    
+    return {
+        "text": text,
+        "normalized_text": normalized if normalizer else text,
+        "sentiment": SENTIMENT_LABELS[pred_idx],
+        "confidence": max(probs),
+        "probabilities": {SENTIMENT_LABELS[i]: probs[i] for i in range(4)},
+    }
+
+
+def get_synonyms(text: str) -> str:
+    """Get synonym replacements for text."""
+    if not replacer or not text.strip():
+        return "Enter Myanmar text to see synonym examples"
+    
+    aug_text, replacements = replacer.augment_text(text, replace_prob=0.5)
+    
+    if not replacements:
+        return f"No synonym replacements found for: {text}"
+    
+    result = f"Original: {text}\n\nAugmented: {aug_text}\n\nReplacements:\n"
+    for orig, new in replacements:
+        result += f"  • {orig} → {new}\n"
+    
+    return result
+
+
+def show_probabilities(text: str) -> dict:
+    """Show probability distribution."""
+    result = analyze_sentiment(text)
+    return result["probabilities"]
+
+
+# Create Gradio interface
+with gr.Blocks(
+    title="Myanmar Ghost - Sentiment Analysis",
+    theme=gr.themes.Soft(),
+) as demo:
+    
+    gr.Markdown("""
+    # 🇲🇲 Myanmar Ghost
+    ### Advanced Myanmar Sentiment Analysis
+    
+    Enter Myanmar text to analyze sentiment. Supports:
+    - ✅ Positive/Negative/Neutral/Sarcastic classification
+    - 🔤 Text normalization
+    - 📝 Synonym augmentation
+    """)
+    
+    with gr.Row():
+        with gr.Column(scale=2):
+            text_input = gr.Textbox(
+                label="Myanmar Text Input",
+                placeholder="ကျေးဇူးပါ မင်္ဂလာပါ...",
+                lines=3,
+            )
+            
+            with gr.Row():
+                analyze_btn = gr.Button("🔍 Analyze", variant="primary")
+                clear_btn = gr.Button("🗑️ Clear")
+        
+        with gr.Column(scale=1):
+            sentiment_output = gr.Label(
+                label="Predicted Sentiment",
+            )
+    
+    # Probabilities
+    gr.Markdown("### 📊 Confidence Scores")
+    prob_display = gr.BarPlot(
+        x=["negative", "neutral", "positive", "sarcastic"],
+        y=[0.25, 0.25, 0.25, 0.25],
+        label="Probability Distribution",
+        y_lab="Probability",
+        x_lab="Sentiment",
+    )
+    
+    # Synonym tool
+    gr.Markdown("### 📝 Synonym Augmentation")
+    with gr.Row():
+        synonym_input = gr.Textbox(
+            label="Text for Synonyms",
+            placeholder="Enter text to see synonym replacements...",
+            lines=2,
+        )
+        synonym_btn = gr.Button("🔄 Get Synonyms")
+    
+    synonym_output = gr.Textbox(
+        label="Synonym Results",
+        lines=4,
+    )
+    
+    # Examples
+    gr.Examples(
+        examples=[
+            ["ကျေးဇူးပါ"],
+            ["မင်္ဂလာပါ"],
+            ["မကျေနပ်ပါဗျ"],
+            ["အရမ်းကောင်းတယ်"],
+        ],
+        inputs=text_input,
+    )
+    
+    # Event handlers
+    analyze_btn.click(
+        fn=analyze_sentiment,
+        inputs=text_input,
+        outputs=[sentiment_output, prob_display],
+    )
+    
+    clear_btn.click(
+        fn=lambda: ("", {"negative": 0.25, "neutral": 0.25, "positive": 0.25, "sarcastic": 0.25}),
+        inputs=[],
+        outputs=[text_input, sentiment_output],
+    )
+    
+    synonym_btn.click(
+        fn=get_synonyms,
+        inputs=synonym_input,
+        outputs=synonym_output,
+    )
+    
+    gr.Markdown("""
+    ---
+    ### ℹ️ About
+    
+    Myanmar Ghost is an advanced NLP project for Myanmar language understanding.
+    
+    - **Model**: Transformer-based sentiment classifier
+    - **Features**: Multi-modal fusion, Active Learning, XAI
+    - **Author**: [Aung Myo Kyaw](https://huggingface.co/amkyawdev)
+    
+    [GitHub Repository](https://github.com/amkyawdev/myanmar-ghost)
+    """)
+
+
+if __name__ == "__main__":
+    demo.launch()