from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
import gradio as gr

model_path = 'kahennefer/fine_tuned_gpt2'

model = AutoModelForCausalLM.from_pretrained(model_path)
tokenizer = AutoTokenizer.from_pretrained(model_path)

text_gen_pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)

def generate_answer(question):
    result = text_gen_pipeline(question, max_length=100, num_return_sequences=1)
    return result[0]['generated_text']

iface = gr.Interface(
    fn=generate_answer,
    inputs=gr.Textbox(lines=2, placeholder="Ask a question about the case..."),
    outputs=gr.Text(label="Answer"),
    title="Case-Specific Question Answering System",
    description="Ask any question about the case, and the model will provide an answer based on its knowledge."
)

iface.launch()