let's debug

app.py

@@ -1,50 +1,92 @@
 # app.py
 import gradio as gr
 from transformers import pipeline
+import logging
+import sys
 
-# Initialize the emotion classification pipeline
-classifier = pipeline("text-classification", 
-                     model="bhadresh-savani/distilbert-base-uncased-emotion",
-                     return_all_scores=True)
+# Set up logging
+logging.basicConfig(level=logging.INFO, stream=sys.stdout,
+                   format='%(asctime)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+try:
+    logger.info("Initializing emotion classification pipeline...")
+    classifier = pipeline(
+        "text-classification",
+        model="bhadresh-savani/distilbert-base-uncased-emotion",
+        return_all_scores=True
+    )
+    logger.info("Pipeline initialized successfully")
+except Exception as e:
+    logger.error(f"Failed to initialize pipeline: {str(e)}")
+    raise
 
 def predict_emotion(text):
-    if not text:
+    try:
+        logger.info(f"Received input text: {text}")
+        
+        if not text:
+            logger.warning("Empty text received")
+            return {
+                "sadness": 0,
+                "joy": 0,
+                "love": 0,
+                "anger": 0,
+                "fear": 0,
+                "surprise": 0
+            }
+        
+        # Get predictions
+        logger.info("Running prediction...")
+        predictions = classifier(text)[0]
+        logger.info(f"Raw predictions: {predictions}")
+        
+        # Convert to dictionary format for the bar chart
+        scores = {pred['label']: float(pred['score']) for pred in predictions}
+        logger.info(f"Processed scores: {scores}")
+        
+        return scores
+        
+    except Exception as e:
+        logger.error(f"Error in prediction: {str(e)}")
         return {
-            "sadness": 0,
-            "joy": 0,
-            "love": 0,
-            "anger": 0,
-            "fear": 0,
-            "surprise": 0
+            "error": 1.0,
+            "message": f"An error occurred: {str(e)}"
         }
-    
-    # Get predictions
-    predictions = classifier(text)[0]
-    
-    # Convert to dictionary format for the bar chart
-    scores = {pred['label']: pred['score'] for pred in predictions}
-    return scores
 
-# Create the Gradio interface
-demo = gr.Interface(
-    fn=predict_emotion,
-    inputs=gr.Textbox(placeholder="Enter text to analyze...", label="Input Text"),
-    outputs=gr.BarPlot(
-        x="emotion",
-        y="probability",
-        title="Emotion Probabilities",
-        tooltip=["emotion", "probability"],
-        height=400
-    ),
-    title="Emotion Detection with DistilBERT",
-    description="This app uses the DistilBERT model fine-tuned for emotion detection. Enter any text to analyze its emotional content.",
-    examples=[
-        ["I am so happy to see you!"],
-        ["I'm really angry about what happened."],
-        ["The sunset was absolutely beautiful today."],
-        ["I'm worried about the upcoming exam."]
-    ],
-    allow_flagging="never"
-)
+# Create the Gradio interface with error handling
+try:
+    logger.info("Setting up Gradio interface...")
+    demo = gr.Interface(
+        fn=predict_emotion,
+        inputs=gr.Textbox(placeholder="Enter text to analyze...", label="Input Text"),
+        outputs=gr.BarPlot(
+            x="emotion",
+            y="probability",
+            title="Emotion Probabilities",
+            tooltip=["emotion", "probability"],
+            height=400
+        ),
+        title="Emotion Detection with DistilBERT",
+        description="This app uses the DistilBERT model fine-tuned for emotion detection. Enter any text to analyze its emotional content.",
+        examples=[
+            ["I am so happy to see you!"],
+            ["I'm really angry about what happened."],
+            ["The sunset was absolutely beautiful today."],
+            ["I'm worried about the upcoming exam."]
+        ],
+        allow_flagging="never"
+    )
+    logger.info("Gradio interface setup complete")
+except Exception as e:
+    logger.error(f"Failed to create Gradio interface: {str(e)}")
+    raise
 
-demo.launch()
+if __name__ == "__main__":
+    try:
+        logger.info("Launching Gradio app...")
+        demo.launch(debug=True)
+        logger.info("Gradio app launched successfully")
+    except Exception as e:
+        logger.error(f"Failed to launch Gradio app: {str(e)}")
+        raise