Delete app.py

app.py

@@ -1,168 +0,0 @@
-"""
-Gradio App for Multilingual Sentiment Analysis
-Deploy this to Hugging Face Spaces
-"""
-
-import gradio as gr
-from sentiment_analyzer import MultilingualSentimentAnalyzer
-
-def analyze_sentiment(text, language, method):
-    """Analyze sentiment and return formatted results"""
-    if not text or not text.strip():
-        return "Please enter some text to analyze."
-    
-    try:
-        analyzer = MultilingualSentimentAnalyzer(language=language, method=method)
-        result = analyzer.analyze(text)
-        
-        # Format the output nicely
-        output = f"""
-## Sentiment Analysis Results
-
-**Polarity:** {result['polarity'].upper()}
-**Confidence:** {result['confidence']*100:.1f}%
-
-**Scores:**
-- Positive: {result['positive_score']:.2f}
-- Negative: {result['negative_score']:.2f}
-
-**Details:**
-- Method: {result['method']}
-- Language: {result['language']}
-- Words analyzed: {result.get('word_count', 0)}
-"""
-        
-        return output
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-def batch_analyze(texts, language, method):
-    """Analyze multiple texts"""
-    if not texts:
-        return "Please enter texts to analyze (one per line)."
-    
-    text_list = [t.strip() for t in texts.split('\n') if t.strip()]
-    if not text_list:
-        return "No valid texts found."
-    
-    try:
-        analyzer = MultilingualSentimentAnalyzer(language=language, method=method)
-        results = analyzer.analyze_batch(text_list)
-        stats = analyzer.get_statistics(text_list)
-        
-        output = f"""
-## Batch Analysis Results
-
-**Statistics:**
-- Total texts: {stats['total_texts']}
-- Average confidence: {stats['average_confidence']*100:.1f}%
-
-**Polarity Distribution:**
-"""
-        for polarity, percentage in stats['polarity_percentages'].items():
-            output += f"- {polarity.capitalize()}: {percentage}%\n"
-        
-        output += "\n**Individual Results:**\n"
-        for i, (text, result) in enumerate(zip(text_list, results), 1):
-            output += f"\n{i}. \"{text[:50]}...\" → {result['polarity']} ({result['confidence']*100:.1f}%)\n"
-        
-        return output
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-# Create Gradio interface
-with gr.Blocks(title="Multilingual Sentiment Analysis", theme=gr.themes.Soft()) as demo:
-    gr.Markdown("""
-    # 🌍 Multilingual Sentiment Analysis Tool
-    
-    Analyze sentiment in **English**, **Turkish**, and **Persian** text using non-deep-learning approaches.
-    
-    This tool uses lexicon-based, rule-based, and hybrid methods for interpretable sentiment analysis.
-    """)
-    
-    with gr.Tabs():
-        with gr.TabItem("Single Text Analysis"):
-            with gr.Row():
-                with gr.Column():
-                    text_input = gr.Textbox(
-                        label="Enter Text",
-                        placeholder="Type your text here...",
-                        lines=5
-                    )
-                    language = gr.Dropdown(
-                        choices=["english", "turkish", "persian"],
-                        value="english",
-                        label="Language"
-                    )
-                    method = gr.Dropdown(
-                        choices=["lexicon", "rule", "hybrid"],
-                        value="hybrid",
-                        label="Analysis Method"
-                    )
-                    analyze_btn = gr.Button("Analyze Sentiment", variant="primary")
-                
-                with gr.Column():
-                    output = gr.Markdown(label="Results")
-            
-            analyze_btn.click(
-                fn=analyze_sentiment,
-                inputs=[text_input, language, method],
-                outputs=output
-            )
-        
-        with gr.TabItem("Batch Analysis"):
-            with gr.Row():
-                with gr.Column():
-                    batch_texts = gr.Textbox(
-                        label="Enter Texts (one per line)",
-                        placeholder="Enter multiple texts, one per line...",
-                        lines=10
-                    )
-                    batch_language = gr.Dropdown(
-                        choices=["english", "turkish", "persian"],
-                        value="english",
-                        label="Language"
-                    )
-                    batch_method = gr.Dropdown(
-                        choices=["lexicon", "rule", "hybrid"],
-                        value="hybrid",
-                        label="Analysis Method"
-                    )
-                    batch_btn = gr.Button("Analyze Batch", variant="primary")
-                
-                with gr.Column():
-                    batch_output = gr.Markdown(label="Batch Results")
-            
-            batch_btn.click(
-                fn=batch_analyze,
-                inputs=[batch_texts, batch_language, batch_method],
-                outputs=batch_output
-            )
-        
-        with gr.TabItem("Examples"):
-            gr.Markdown("""
-            ### Example Texts to Try:
-            
-            **English:**
-            - "I love this product! It's absolutely amazing!!! 😊"
-            - "This is terrible. I hate it."
-            - "Not bad, actually it's quite good!"
-            
-            **Turkish:**
-            - "Bu ürünü çok seviyorum! Harika!"
-            - "Berbat bir deneyim. Hiç beğenmedim."
-            
-            **Persian:**
-            - "این محصول عالی است!"
-            - "خیلی بد بود"
-            """)
-    
-    gr.Markdown("""
-    ---
-    **About:** This tool uses lexicon-based, rule-based, and hybrid approaches (without deep learning) 
-    for interpretable sentiment analysis. Supports English, Turkish, and Persian languages.
-    """)
-
-if __name__ == "__main__":
-    demo.launch()
-