Create app

app

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+import gradio as gr
+import joblib
+import os
+import logging
+from datetime import datetime
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+class SMSScamDetector:
+    """Enhanced SMS Scam Detection System"""
+    
+    def __init__(self):
+        self.model = None
+        self.vectorizer = None
+        self.load_models()
+    
+    def load_models(self):
+        """Load machine learning models with error handling"""
+        try:
+            if os.path.exists("scam_classifier_model.joblib"):
+                self.model = joblib.load("scam_classifier_model.joblib")
+                logger.info("Model loaded successfully")
+            else:
+                logger.error("Model file not found")
+                
+            if os.path.exists("tfidf_vectorizer.joblib"):
+                self.vectorizer = joblib.load("tfidf_vectorizer.joblib")
+                logger.info("Vectorizer loaded successfully")
+            else:
+                logger.error("Vectorizer file not found")
+                
+        except Exception as e:
+            logger.error(f"Error loading models: {str(e)}")
+            self.model = None
+            self.vectorizer = None
+    
+    def preprocess_text(self, text):
+        """Clean and preprocess input text"""
+        if not text or not isinstance(text, str):
+            return ""
+        
+        # Basic cleaning
+        text = text.strip()
+        text = ' '.join(text.split())  # Remove extra whitespace
+        return text
+    
+    def get_confidence_level(self, prediction_proba):
+        """Determine confidence level based on prediction probability"""
+        max_prob = max(prediction_proba)
+        if max_prob >= 0.8:
+            return "Imara sana (Very High)", "🔴"
+        elif max_prob >= 0.65:
+            return "Imara (High)", "🟠"
+        elif max_prob >= 0.5:
+            return "Wastani (Medium)", "🟡"
+        else:
+            return "Haba (Low)", "🟢"
+    
+    def predict_sms(self, text):
+        """Enhanced prediction function with detailed output"""
+        # Input validation
+        if not text or len(text.strip()) == 0:
+            return "❌ **Kosa**: Tafadhali ingiza ujumbe wa SMS"
+        
+        if len(text.strip()) < 5:
+            return "⚠️ **Onyo**: Ujumbe mfupi sana. Ingiza ujumbe kamili."
+        
+        # Check if models are loaded
+        if self.model is None or self.vectorizer is None:
+            return "❌ **Kosa la Mfumo**: Mifumo ya AI haijapakiwa vizuri. Tafadhali rudia tena."
+        
+        try:
+            # Preprocess text
+            cleaned_text = self.preprocess_text(text)
+            
+            # Vectorize text
+            text_vector = self.vectorizer.transform([cleaned_text])
+            
+            # Make prediction
+            prediction = self.model.predict(text_vector)[0]
+            prediction_proba = self.model.predict_proba(text_vector)[0]
+            
+            # Get confidence level
+            confidence, emoji = self.get_confidence_level(prediction_proba)
+            
+            # Format prediction
+            if prediction.lower() == 'scam':
+                result_text = "**SCAM** 🚨"
+                result_color = "danger"
+                advice = "**Onyo**: Ujumbe huu unaweza kuwa wa udanganyifu. Usijibu au kutoa taarifa za kibinafsi."
+            else:
+                result_text = "**TRUST** ✅"
+                result_color = "success"
+                advice = "Ujumbe huu unaonekana kuwa wa kawaida, lakini bado kuwa makini."
+            
+            # Create detailed output
+            output = f"""
+## Matokeo ya Uchunguzi {emoji}
+
+**Ujumbe**: "{text[:100]}{'...' if len(text) > 100 else ''}"
+
+**Utabiri**: {result_text}
+
+**Kiwango cha Uhakika**: {confidence}
+
+**Maoni**: {advice}
+
+---
+*Tarehe*: {datetime.now().strftime("%Y-%m-%d %H:%M:%S")}
+*Urefu wa ujumbe*: {len(text)} herufi
+            """
+            
+            return output
+            
+        except Exception as e:
+            logger.error(f"Prediction error: {str(e)}")
+            return f"❌ **Kosa la Kihesabu**: {str(e)}"
+
+# Initialize detector
+detector = SMSScamDetector()
+
+# Sample SMS messages for testing
+sample_messages = [
+    "Hongera! Umeshinda Tsh 1,000,000. Piga *123# ili kupokea zawadi yako sasa hivi!",
+    "Habari za leo? Tutaonana kesho uwandani kama tulivyopanga.",
+    "URGENT: Your account will be closed. Click link to verify: http://fake-bank.com",
+    "Mama, nimepoteza simu yangu. Hii ni nambari yangu mpya. Nitakuja nyumbani jioni."
+]
+
+def load_sample(sample_text):
+    """Load sample message into the textbox"""
+    return sample_text
+
+# Create enhanced Gradio interface
+with gr.Blocks(
+    theme=gr.themes.Soft(),
+    title="Bongo SMS Scam Detector",
+    css="""
+    .gradio-container {
+        max-width: 800px !important;
+        margin: auto !important;
+    }
+    .warning {
+        background: linear-gradient(45deg, #ff6b6b, #feca57);
+        padding: 15px;
+        border-radius: 10px;
+        margin: 10px 0;
+    }
+    """
+) as demo:
+    
+    gr.Markdown("""
+    # 🛡️ Bongo SMS Scam Detector
+    
+    **Kiunga cha Usalama wa SMS** - Chunguza ujumbe wa SMS ili kujua kama ni wa udanganyifu
+    
+    ⚡ Ingiza ujumbe wa SMS hapo chini na upate matokeo ya haraka
+    """)
+    
+    with gr.Row():
+        with gr.Column(scale=2):
+            # Main input
+            sms_input = gr.Textbox(
+                lines=6,
+                placeholder="Nakili na ubandike ujumbe wa SMS hapa...\n\nMfano: 'Hongera! Umeshinda Tsh 500,000. Piga *150# ili kupokea pesa zako!'",
+                label="📱 Ujumbe wa SMS",
+                info="Ingiza ujumbe wowote wa SMS unaodai kushinda zawadi, pesa, au kutaka taarifa za kibinafsi"
+            )
+            
+            with gr.Row():
+                predict_btn = gr.Button("🔍 Chunguza SMS", variant="primary", size="lg")
+                clear_btn = gr.Button("🗑️ Futa", variant="secondary")
+        
+        with gr.Column(scale=1):
+            gr.Markdown("### 📋 Mifano ya SMS")
+            
+            # Sample buttons
+            for i, sample in enumerate(sample_messages, 1):
+                sample_btn = gr.Button(
+                    f"Mfano {i}",
+                    variant="outline",
+                    size="sm"
+                )
+                sample_btn.click(
+                    fn=lambda x=sample: x,
+                    outputs=sms_input
+                )
+    
+    # Output section
+    output_result = gr.Markdown(
+        label="📊 Matokeo",
+        value="Matokeo yataonyeshwa hapa baada ya kuchunguza ujumbe..."
+    )
+    
+    # Information section
+    with gr.Accordion("ℹ️ Maelezo ya Ziada", open=False):
+        gr.Markdown("""
+        ### Jinsi ya Kutumia:
+        1. **Nakili ujumbe** wa SMS kutoka kwa simu yako
+        2. **Ubandike hapa** kwenye kisanduku cha maandishi
+        3. **Bonyeza kitufe** cha "Chunguza SMS"
+        4. **Soma matokeo** na ufuate mapendekezo
+        
+        ### Dalili za SMS za Udanganyifu:
+        - 🎁 Inadai umeshinda zawadi kubwa
+        - 💰 Inahitaji malipo ya haraka
+        - 🔗 Ina viungo vya kugusia (links)
+        - ⚡ Inadai ni ya dharura
+        - 📞 Inaomba taarifa za kibinafsi
+        
+        ### Onyo Muhimu:
+        Mfumo huu ni wa kusaidia tu. Daima tumia busara zako na usijibu SMS zisizoeleweka.
+        """)
+    
+    # Event handlers
+    predict_btn.click(
+        fn=detector.predict_sms,
+        inputs=sms_input,
+        outputs=output_result
+    )
+    
+    clear_btn.click(
+        fn=lambda: ("", "Matokeo yataonyeshwa hapa baada ya kuchunguza ujumbe..."),
+        outputs=[sms_input, output_result]
+    )
+    
+    sms_input.submit(
+        fn=detector.predict_sms,
+        inputs=sms_input,
+        outputs=output_result
+    )
+
+# Launch configuration
+if __name__ == "__main__":
+    demo.launch(
+        share=False,
+        server_name="0.0.0.0",
+        server_port=7860,
+        show_error=True,
+        favicon_path=None,
+        inbrowser=True
+    )