app.py

import gradio as gr
import spaces
from transformers import pipeline
import logging

# Configure logging
logging.basicConfig(level=logging.INFO)

# Load model and tokenizer using pipeline
logging.info("Loading model and tokenizer...")
model_name = "speakleash/Bielik-11B-v2.3-Instruct"
pipe = pipeline("text-generation", model=model_name)


@spaces.GPU
def process_text(input_text):
    messages = [{"role": "user", "content": input_text}]
    outputs = pipe(messages)
    # Process outputs as needed
    return outputs


def generate(text):
    hardcoded_prompt = "Stwórz zwięzłe podsumowanie tekstu, zachowując kluczowe punkty. Maksymalnie 3 zdania"
    combined_text = hardcoded_prompt + text
    return process_text(combined_text)


gr.Interface(
    fn=generate,
    inputs=gr.Text(),
    outputs=gr.Text(),
).launch()