bar plot emptyy

app.py

@@ -20,8 +20,10 @@ def classify_emotion(text):
         emotion_scores[item["label"]] = item["score"]
     
     # Create a dataframe for the bar plot
-    df = pd.DataFrame.from_dict(emotion_scores, orient="index").reset_index()
-    df.columns = ["Emotion", "Score"]
+    df = pd.DataFrame({
+        "Emotion": list(emotion_scores.keys()),
+        "Score": list(emotion_scores.values())
+    })
     
     # Prepare a text-based table for display
     table = "Emotion Scores:\n"
@@ -40,8 +42,8 @@ gr.Interface(
     ),
     outputs=[
         gr.BarPlot(
-            x="Emotion",
-            y="Score",
+            x="Emotion",  # Correct column for x-axis
+            y="Score",    # Correct column for y-axis
             label="Emotion Scores Bar Plot",
             title="Emotion Probabilities",
             color="#2563eb",  # Color for the bars
@@ -50,10 +52,10 @@ gr.Interface(
         ),
         gr.Textbox(label="Emotion Scores Table")  # Text-based table output
     ],
-    title="CMACHINES25 | Emotion Detection with DistilBERT",
+    title="Emotion Detection with DistilBERT",
     description="This app uses the DistilBERT model fine-tuned for emotion detection. Enter a piece of text to analyze its emotional content! Both a bar plot and a text table of the scores will be displayed.",
     examples=[
-        "I like you. I love you. Sometimes I hate you.",
+        "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.",