app.py

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):
    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.launch()