Upload app_spaces.py

app_spaces.py

@@ -0,0 +1,30 @@
+import gradio as gr
+from transformers import pipeline
+
+# Simplified for Spaces
+classifier = pipeline(
+    "text-classification",
+    model="SiemonCha/thai-sentiment-phayabert",
+    return_all_scores=True
+)
+
+LABELS = {"LABEL_0": "Positive 😊", "LABEL_1": "Neutral 😐", "LABEL_2": "Negative 😞"}
+
+def predict(text):
+    results = classifier(text)[0]
+    return {LABELS[r['label']]: r['score'] for r in results}
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.Textbox(lines=3, placeholder="พิมพ์ข้อความภาษาไทย..."),
+    outputs=gr.Label(),
+    title="🇹🇭 Thai Sentiment Analysis",
+    description="Fine-tuned PhayaThaiBERT on 21k social media messages",
+    examples=[
+        ["อาหารอร่อยมาก บริการดีเยี่ยม"],
+        ["ราคาแพงไป คุณภาพไม่คุ้ม"],
+        ["ปกติครับ ไม่มีอะไรพิเศษ"],
+    ]
+)
+
+demo.launch()