Stable version 1

app.py

@@ -7,28 +7,60 @@ model = joblib.load('tunisian_arabiz_sentiment_analysis_model.pkl')
 vectorizer = joblib.load('tfidf_vectorizer.pkl')
 
 def predict_sentiment(text):
-    # Transform the input text using the loaded vectorizer
     text_vectorized = vectorizer.transform([text])
-    
-    # Make prediction
     prediction = model.predict(text_vectorized)[0]
-    
-    # Convert prediction to sentiment
-    sentiment = "Positive" if prediction == 1 else "Negative"
-    
-    # Get prediction probability
     probabilities = model.predict_proba(text_vectorized)[0]
     confidence = max(probabilities)
     
-    return f"Sentiment: {sentiment}\nConfidence: {confidence:.2f}"
+    sentiment = "Positive" if prediction == 1 else "Negative"
+    
+    return {
+        "Sentiment": sentiment,
+        "Confidence": f"{confidence:.2f}",
+        "Explanation": f"The model predicts this text is {sentiment.lower()} with {confidence:.2%} confidence."
+    }
+
+# Example texts
+examples = [
+    ["3ajbetni barcha el film hedhi"],
+    ["ma7abitch el akla mte3 el restaurant"],
+    ["el jaw fi tounes a7la 7aja"],
+    ["ennes el kol za3nin w ma3andhomch flous"]
+]
 
 # Create Gradio interface
 iface = gr.Interface(
     fn=predict_sentiment,
     inputs=gr.Textbox(lines=3, placeholder="Enter Tunisian Arabiz text here..."),
-    outputs="text",
+    outputs={
+        "Sentiment": gr.Label(label="Predicted Sentiment"),
+        "Confidence": gr.Label(label="Confidence Score"),
+        "Explanation": gr.Textbox(label="Explanation")
+    },
+    examples=examples,
     title="Tunisian Arabiz Sentiment Analysis",
-    description="This model predicts the sentiment of Tunisian Arabiz text as either Positive or Negative."
+    description="""
+    This model predicts the sentiment of Tunisian Arabiz text as either Positive or Negative.
+    
+    Tunisian Arabiz is a form of writing Arabic (specifically Tunisian dialect) using Latin characters and numbers.
+    
+    Example:
+    - "3ajbetni" means "I liked it"
+    - "7aja" means "thing"
+    
+    Try the examples below or enter your own text!
+    """,
+    article="""
+    <div style="text-align: center;">
+        <img src="https://upload.wikimedia.org/wikipedia/commons/c/ce/Flag_of_Tunisia.svg" alt="Tunisian Flag" style="width:150px;"/>
+    </div>
+    <h3>About the Model</h3>
+    <p>This sentiment analysis model was trained on a dataset combining TuniziDataset and the Tunisian Dialect Corpus. 
+    It uses TF-IDF vectorization for feature extraction and Logistic Regression for classification.</p>
+    <h3>Limitations</h3>
+    <p>The model may not perform well on very colloquial expressions or new slang terms not present in the training data. 
+    It's also important to note that sentiment can be nuanced and context-dependent, which may not always be captured by this model.</p>
+    """
 )
 
 # Launch the interface