Update app.py

app.py

@@ -1,56 +1,21 @@
 import gradio as gr
 from transformers import pipeline
 
-MODEL_ID = "j-hartmann/emotion-english-distilroberta-base"
-
-text_emotion = pipeline(
-    task="text-classification",
-    model=MODEL_ID,
-    return_all_scores=True
+text_emotion = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base", return_all_scores=True)
+
+def analyze_emotion(text):
+    results = text_emotion(text)[0]
+    results = sorted(results, key=lambda x: x['score'], reverse=True)
+    output = {r['label']: round(r['score'], 3) for r in results}
+    return output
+
+demo = gr.Interface(
+    fn=analyze_emotion,
+    inputs=gr.Textbox(lines=3, placeholder="Type something here..."),
+    outputs=gr.Label(num_top_classes=3),
+    title="Empath AI - Emotion Detection",
+    description="Type a sentence to see what emotions it contains!"
 )
 
-def analyze_text(text: str):
-    """Return top emotion, its confidence, and all scores."""
-    if not text or not text.strip():
-        return "—", 0.0, {"notice": "Please enter some text."}
-
-       result = text_emotion(text)[0]
-    sorted_pairs = sorted(
-        [(r["label"], float(r["score"])) for r in result],
-        key=lambda x: x[1],
-        reverse=True
-    )
-    top_label, top_score = sorted_pairs[0]
-    all_scores = {label.lower(): round(score, 4) for label, score in sorted_pairs}
-    return top_label, round(top_score, 4), all_scores
-
-with gr.Blocks(title="Empath AI — Text Emotions") as demo:
-    gr.Markdown("# Empath AI — Text Emotion Detection\nPaste text and click **Analyze**.")
-
-    with gr.Row():
-        inp = gr.Textbox(
-            label="Enter text",
-            placeholder="Example: I'm so happy with the result today!",
-            lines=4
-        )
-        btn = gr.Button("Analyze", variant="primary")
-
-    with gr.Row():
-        top = gr.Textbox(label="Top Emotion", interactive=False)
-        conf = gr.Number(label="Confidence (0–1)", interactive=False)
-
-    all_scores = gr.JSON(label="All Emotion Scores")
-
-    gr.Examples(
-        examples=[
-            ["I'm thrilled with how this turned out!"],
-            ["This is taking too long and I'm getting frustrated."],
-            ["I'm worried this might fail."],
-            ["Thanks so much—this really helped."]
-        ],
-        inputs=inp
-    )
-
-    btn.click(analyze_text, inputs=inp, outputs=[top, conf, all_scores])
-
-demo.launch()
+if __name__ == "__main__":
+    demo.launch()