app.py

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

# Load the model and tokenizer
MODEL_NAME = "ubiodee/Cardano_plutus"  # Your fine-tuned model
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)

# Function to generate response from the model
def generate_response(prompt):
    inputs = tokenizer(prompt, return_tensors="pt")
    with torch.no_grad():
        output = model.generate(**inputs, max_length=512)
    response = tokenizer.decode(output[0], skip_special_tokens=True)
    return response

# Gradio Interface
iface = gr.Interface(
    fn=generate_response,
    inputs=gr.Textbox(label="Enter your prompt"),
    outputs=gr.Textbox(label="Model Response"),
    title="Cardano Plutus AI",
    description="Type in your question or prompt related to Cardano Plutus and get a response from the AI model.",
    theme="default"
)

# Launch app
iface.launch()