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import gradio as gr | |
from openai import OpenAI | |
client = OpenAI() | |
def simplify_text(text): | |
if not text: | |
return "", "0 token贸w", "0 token贸w" | |
response = client.chat.completions.create( | |
model="gpt-4o-mini", | |
messages=[ | |
{"role": "system", "content": "Jeste艣 ekspertem w upraszczaniu tekst贸w. Twoim zadaniem jest uproszczenie podanego tekstu, zachowuj膮c jego g艂贸wne znaczenie, ale u偶ywaj膮c prostszego j臋zyka. Nie formatuj tekstu za pomoc膮 znacznik贸w Markdown."}, | |
{"role": "user", "content": f"Upro艣膰 ten tekst:\n{text}"} | |
], | |
temperature=0.7 | |
) | |
simplified_text = response.choices[0].message.content | |
input_tokens = response.usage.prompt_tokens | |
output_tokens = response.usage.completion_tokens | |
return ( | |
simplified_text, | |
f"{input_tokens} token贸w", | |
f"{output_tokens} token贸w" | |
) | |
with gr.Blocks() as demo: | |
gr.Markdown("# Prostownik - narz臋dzie do upraszczania tekst贸w") | |
with gr.Row(): | |
with gr.Column(): | |
input_area = gr.TextArea( | |
label="Tekst wej艣ciowy", | |
placeholder="Wklej tutaj tekst do uproszczenia...", | |
lines=10 | |
) | |
input_tokens = gr.Textbox(label="Liczba token贸w wej艣ciowych") | |
with gr.Column(): | |
output_area = gr.TextArea( | |
label="Tekst uproszczony", | |
lines=10, | |
show_copy_button=True | |
) | |
output_tokens = gr.Textbox(label="Liczba token贸w wyj艣ciowych") | |
input_area.change( | |
fn=simplify_text, | |
inputs=input_area, | |
outputs=[output_area, input_tokens, output_tokens] | |
) | |
demo.launch(share=True) |