import gradio as gr
from gradio import Textbox, Slider
from transformers import GPT2LMHeadModel, GPT2Tokenizer

# Initialisierung des Modells und des Tokenizers
tokenizer = GPT2Tokenizer.from_pretrained("Loewolf/GPT_1")
model = GPT2LMHeadModel.from_pretrained("Loewolf/GPT_1")

def generate_text(prompt, max_length, temperature, top_k, top_p):
    inputs = tokenizer.encode(prompt, return_tensors="pt")
    outputs = model.generate(inputs, 
                             max_length=max_length, 
                             temperature=temperature, 
                             top_k=top_k, 
                             top_p=top_p, 
                             num_return_sequences=1)
    text = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return text

iface = gr.Interface(
    fn=generate_text, 
    inputs=[
        Textbox(lines=2, placeholder="Geben Sie einen Prompt ein..."), 
        Slider(minimum=10, maximum=100, default=50, label="Maximale Länge"),
        Slider(minimum=0.1, maximum=1.0, step=0.1, default=0.7, label="Temperatur"),
        Slider(minimum=0, maximum=50, default=20, label="Top K"),
        Slider(minimum=0.0, maximum=1.0, step=0.1, default=0.9, label="Top P")
    ],
    outputs="text"
)
iface.launch()