Updated application file

app.py

@@ -1,11 +1,39 @@
-import gradio as gr
 from transformers import pipeline
+import gradio as gr
 
 model_path="matiss/Latvian-Twitter-Sentiment-Analysis"
 sentiment_task = pipeline("sentiment-analysis", model=model_path, tokenizer=model_path)
 
 def classify(text):
-    return sentiment_task(text)
+    output = sentiment_task(text)
+    return output[0]['label'], output[0]['score']
+
+#demo = gr.Interface(fn=classify, inputs="text", outputs="text")
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            textbox = gr.Textbox(label="Input text:", placeholder="Man garšo pankūkas ar kotletēm", lines=5)
+            greet_btn = gr.Button("Classify")
+        with gr.Column():
+            outbox = gr.Textbox(label="Prediction:", placeholder="positive")
+            runbox = gr.Textbox(label="Score")
+
+    greet_btn.click(    
+        fn=classify, 
+        inputs=textbox, 
+        outputs=[outbox, runbox]        
+   )
+    examples = gr.Examples(
+        examples=[
+                ["Lietus šodien līst kā pa Jāņiem."],
+                ["Es neciešu pirmdienas"],
+                ["Pusdienās Tev jāēd brokolis, steiks, biezpiensieriņš un jāuzdzer Dlight."],
+                ["Nesaprotu vairs kas te tagad notiek"],
+                ["Man garšo pankūkas ar kotletēm"],
+        ],
+        inputs=[textbox],
+    )
+
 
-demo = gr.Interface(fn=classify, inputs="text", outputs="text")
-demo.launch()
+demo.launch(server_name='local-alien.s.aist.go.jp', share=True, debug=True)