app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer

# Wczytanie własnego modelu chatbota z Hugging Face
model_name = "pp3232133/pp3232133-distilgpt2-wikitext2"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Funkcja obsługująca wejście i wyjście dla interfejsu Gradio
def chatbot_interface(input_text):
    input_ids = tokenizer.encode(input_text, return_tensors="pt")
    chatbot_output = model.generate(input_ids, max_length=100)[0]
    response = tokenizer.decode(chatbot_output, skip_special_tokens=True)
    return response

# Interfejs Gradio dla chatbota
iface = gr.Interface(
    fn=chatbot_interface, 
    inputs="text", 
    outputs="text",
    title="Chatbot",
    description="Custom chatbot based on your Hugging Face model. Start typing to chat with the bot.",
    theme="compact"
)

# Uruchomienie interfejsu
iface.launch()